65 results on '"Gihwan Lee"'
Search Results
2. New Class of Tyrosinase Inhibitors, Rotenoids, from Amorpha fruticosa
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Si Won Moon, Jeong Yoon Kim, Seung Hwan Lee, Se Young Im, Gihwan Lee, and Ki Hun Park
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Chemistry ,QD1-999 - Published
- 2023
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3. Investigation of bacterial neuraminidase inhibition of xanthones bearing geranyl and prenyl groups from Cratoxylum cochinchinense
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Jeong Yoon Kim, Zuo Peng Li, Gihwan Lee, Jeong Ho Kim, Abdul Bari Shah, Yong Hyun Lee, and Ki Hun Park
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bacterial neuraminidase inhibitors ,Cratoxylum cochinchinense ,new xanthones ,slow-binding competitive inhibitor ,molecular dynamics simulations ,Chemistry ,QD1-999 - Abstract
Introduction: The root of Cratoxylum cochinchinense has been widely used as Chinese folk medicine to cure fevers, burns, and abdominal complications because it contains various bioactive metabolites such as xanthones, triterpenes, and flavonoids. In this study, we estimated bacterial neuraminidase inhibition with a series of xanthones from C. cochinchinense. BNA has connected to various biological functions such as pathogenic bacteria infection inflammatory process after infection and biofilm formation.Methods: The identification of xanthones (1–6) bearing geranyl and prenyl groups was established by spectroscopic data using UV, IR, NMR, and HREIMS. BNA inhibitory modes of isolated xanthones were investigated by Double-reciprocal plots. Moreover, the competitive inhibitor was evaluated the additional kinetic modes determined by kinetic parameters (k3, k4, and Kiapp). The molecular docking (MD) and molecular dynamics simulations (MDS) studies also provided the critical information regarding the role of the geranyl and prenyl groups against BNA inhibition.Results: A series of xanthones (1–6) appended prenyl and geranyl groups on the A-ring were isolated, and compounds 1–3 were shown to be new xanthones. The analogues within this series were highly inhibited with excellent affinity against bacterial neuraminidase (BNA). A subtle change in the prenyl or geranyl motif affected the inhibitory potency and behavior significantly. For example, the inhibitory potency and binding affinity resulting from the geranyl group on C4: xanthone 1 (IC50 = 0.38 μM, KA = 2.4434 × 105 L·mol−1) were 100-fold different from those of xanthone 3 (IC50 = 35.8 μM, KA = 0.0002 × 105 L·mol−1). The most potent compound 1 was identified as a competitive inhibitor which interacted with BNA under reversible slow-binding inhibition: Kiapp = 0.1440 μM, k3 = 0.1410 μM−1s−1, and k4 = 0.0203 min−1. The inhibitory potencies (IC50) were doubly confirmed by the binding affinities (KA).Discussion: This study suggests the potential of xanthones derived from C. cochinchinense as promising candidates for developing novel BNA inhibitors. Further research and exploration of these xanthones may contribute to the development of effective treatments for bacterial infections and inflammatory processes associated with BNA activity.
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- 2023
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4. REDD1 promotes obesity-induced metabolic dysfunction via atypical NF-κB activation
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Dong-Keon Lee, Taesam Kim, Junyoung Byeon, Minsik Park, Suji Kim, Joohwan Kim, Seunghwan Choi, Gihwan Lee, Chanin Park, Keun Woo Lee, Yong Jung Kwon, Jeong-Hyung Lee, Young-Guen Kwon, and Young-Myeong Kim
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Science - Abstract
The stress response protein REDD1 is regulates inflammation and energy metabolism. Here the authors report that global or adipocyte-specific deletion of REDD1 inhibits diet induced obesity, insulin resistance, liver steatosis and inflammation in mice, at least in part via reduced atypical NF-κB activation.
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- 2022
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5. Computational Approaches to Discover Novel Natural Compounds for SARS‐CoV‐2 Therapeutics
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Dr. Shailima Rampogu, Gihwan Lee, Apoorva M. Kulkarni, Donghwan Kim, Sanghwa Yoon, Prof. Myeong Ok Kim, and Prof. Keun Woo Lee
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SARS-CoV-2 ,natural compounds ,COVID-19 ,molecular docking ,virtual screening ,computational studies ,Chemistry ,QD1-999 - Abstract
Abstract Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID‐19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug‐like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS‐CoV‐2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug‐like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N‐71493 and STOCK1N‐45683 as SARS‐CoV‐2 treatment regime.
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- 2021
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6. 3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Dynamics Simulations for the Identification of Spleen Tyrosine Kinase Inhibitors
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Vikas Kumar, Shraddha Parate, Danishuddin, Amir Zeb, Pooja Singh, Gihwan Lee, Tae Sung Jung, Keun Woo Lee, and Min Woo Ha
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SYK inhibitor ,3D QSAR ,pharmacophore ,autoimmune diseases ,molecular docking ,MD simulation ,Microbiology ,QR1-502 - Abstract
Spleen tyrosine kinase (SYK) is an essential mediator of immune cell signaling and has been anticipated as a therapeutic target for autoimmune diseases, notably rheumatoid arthritis, allergic rhinitis, asthma, and cancers. Significant attempts have been undertaken in recent years to develop SYK inhibitors; however, limited success has been achieved due to poor pharmacokinetics and adverse effects of inhibitors. The primary goal of this research was to identify potential inhibitors having high affinity, selectivity based on key molecular interactions, and good drug-like properties than the available inhibitor, fostamatinib. In this study, a 3D-QSAR model was built for SYK based on known inhibitor IC50 values. The best pharmacophore model was then used as a 3D query to screen a drug-like database to retrieve hits with novel chemical scaffolds. The obtained compounds were subjected to binding affinity prediction using the molecular docking approach, and the results were subsequently validated using molecular dynamics (MD) simulations. The simulated compounds were ranked according to binding free energy (ΔG), and the binding affinity was compared with fostamatinib. The binding mode analysis of selected compounds revealed that the hit compounds form hydrogen bond interactions with hinge region residue Ala451, glycine-rich loop residue Lys375, Ser379, and DFG motif Asp512. Identified hits were also observed to form a desirable interaction with Pro455 and Asn457, the rare feature observed in SYK inhibitors. Therefore, we argue that identified hit compounds ZINC98363745, ZINC98365358, ZINC98364133, and ZINC08789982 may help in drug design against SYK.
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- 2022
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7. Image Compression Based on a Partially Rotated Discrete Cosine Transform With a Principal Orientation
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Gihwan Lee and Yoonsik Choe
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Directional discrete cosine transform ,discrete cosine transform ,image transformation ,image compression ,sparse coding transform ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Image transforms are necessary for image and video compression. Analytic transforms are powerful in compacting natural signals for wider exploitation. Various methods have been introduced to represent such data as a small number of bases, and several of these methods use machine learning, usually based on sparse coding, to outperform analytic transforms. They show sufficient data compaction abilities. However, these methods focus only on data compaction and reconstruction performance, without considering computational issues during implementation. We introduce a new framework for a more efficient transform based on a two-dimensional discrete cosine transform (DCT) and its characteristics. We aimed to improve the data compaction ability of transforms to levels better or similar to that of the DCT and other data-driven transforms, with fast and efficient implementation. We focused on the properties of the DCT, including horizontal and vertical directional information, and approximated its direction using the transform. Our framework was designed by rotating some of the DCT bases to fit this direction. As expected, our framework achieves a transform design with minimized computation for efficient implementation. It does not require an iterative algorithm or brute-force methods to find the best transform matrix or other parameters, thereby making it much faster than other methods. Our framework is 10 times faster than the steerable DCT (SDCT) and twice as fast as the eight-level SDCT with minimum performance reduction. Experimental validation with various images indicates that the proposed method sufficiently approaches the performance of the other transforms despite faster implementation.
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- 2021
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8. Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches
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Vikas Kumar, Raj Kumar, Shraddha Parate, Danishuddin, Gihwan Lee, Moonhyuk Kwon, Seong-Hee Jeong, Hyeon-Su Ro, Keun Woo Lee, and Seon-Won Kim
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ACK1 ,pharmacophore modeling ,docking ,molecular dynamics simulations ,cancer ,inhibitor ,Microbiology ,QR1-502 - Abstract
Background: Activated Cdc42-associated kinase (ACK1) is essential for numerous cellular functions, such as growth, proliferation, and migration. ACK1 signaling occurs through multiple receptor tyrosine kinases; therefore, its inhibition can provide effective antiproliferative effects against multiple human cancers. A number of ACK1-specific inhibitors were designed and discovered in the previous decade, but none have reached the clinic. Potent and selective ACK1 inhibitors are urgently needed. Methods: In the present investigation, the pharmacophore model (PM) was rationally built utilizing two distinct inhibitors coupled with ACK1 crystal structures. The generated PM was utilized to screen the drug-like database generated from the four chemical databases. The binding mode of pharmacophore-mapped compounds was predicted using a molecular docking (MD) study. The selected hit-protein complexes from MD were studied under all-atom molecular dynamics simulations (MDS) for 500 ns. The obtained trajectories were ranked using binding free energy calculations (ΔG kJ/mol) and Gibb’s free energy landscape. Results: Our results indicate that the three hit compounds displayed higher binding affinity toward ACK1 when compared with the known multi-kinase inhibitor dasatinib. The inter-molecular interactions of Hit1 and Hit3 reveal that compounds form desirable hydrogen bond interactions with gatekeeper T205, hinge region A208, and DFG motif D270. As a result, we anticipate that the proposed scaffolds might help in the design of promising selective ACK1 inhibitors.
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- 2023
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9. Integration of virtual screening and computational simulation identifies photodynamic therapeutics against human Protoporphyrinogen Oxidase IX (hPPO)
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Amir Zeb, Chanin Park, Minky Son, Ayoung Baek, Yeongrae Cho, Donghwan Kim, Shailima Rampogu, Gihwan Lee, Youn-Sig Kwak, Seok Ju Park, and Keun Woo Lee
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Chemistry ,QD1-999 - Abstract
Photodynamic therapy (PDT) is a rapidly evolving area of cancer management against solid tumors. PDT is either administrated by injecting photosensitizer (porphyrins) or by accumulation of intracellular protoporphyrin IX via the inhibition of human Protoporphyrinogen Oxidase IX (hPPO). In this study, novel inhibitors of hPPO have been investigated by integrating virtual screening, molecular docking, and molecular dynamics (MD) simulation. A ligand-based pharmacophore was generated from a training set of 22 inhibitors of hPPO. The selected pharmacophore had four chemical features including three hydrogen bond acceptors and one hydrophobic. The pharmacophore was characterized by highest correlation coefficient of 0.96, cost difference of 53.20, and lowest root mean square deviation of 0.73. The resultant pharmacophore was validated by Fischer’s Randomization and Test Set Validation methods. The validated pharmacophore was used as a 3D query to screen chemical databases including NCI, Asinex, Chembridge, and Maybridge. The screening of chemical databases and the subsequent application of Lipinski’s Rule of Five, and ADMET Assessment Test, retrieved 1176 drug-like compounds. The drug-like compounds were subjected to molecular docking studies in the active site of hPPO to eliminate false positive hits and to elucidate their true binding orientation. Top three candidate molecules with high docking scores and hydrogen bond interactions with catalytic active residues were selected as best candidate inhibitors against hPPO. The binding stability of selected candidate inhibitors was evaluated by MD simulation. The MD simulation of hits portrayed strong hydrogen bonds and key hydrophobic interactions with catalytic active residues of hPPO including R59, R97, G159, G332 and flavin moiety of FAD (coenzyme of hPPO). Our study predicts three hit compounds against hPPO, which could possibly accumulate high concentration of protoporphyrinogen-IX, and thereby acting as an intracellular photosensitizer against tumor cells through photodynamic therapy. Keywords: Photodynamic therapy (PDT), hPPO Inhibition, Virtual screening, Pharmacophore modeling, Molecular docking simulation, Molecular dynamics (MD) simulation
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- 2020
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10. Pharmacophore-Oriented Identification of Potential Leads as CCR5 Inhibitors to Block HIV Cellular Entry
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Pooja Singh, Vikas Kumar, Gihwan Lee, Tae Sung Jung, Min Woo Ha, Jong Chan Hong, and Keun Woo Lee
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CCR5 ,HIV ,pharmacophore modeling ,molecular docking studies ,molecular dynamics simulations analysis ,inhibitors ,Biology (General) ,QH301-705.5 ,Chemistry ,QD1-999 - Abstract
Cysteine–cysteine chemokine receptor 5 (CCR5) has been discovered as a co-receptor for cellular entry of human immunodeficiency virus (HIV). Moreover, the role of CCR5 in a variety of cancers and various inflammatory responses was also discovered. Despite the fact that several CCR5 antagonists have been investigated in clinical trials, only Maraviroc has been licensed for use in the treatment of HIV patients. This indicates that there is a need for novel CCR5 antagonists. Keeping this in mind, the present study was designed. The active CCR5 inhibitors with known IC50 value were selected from the literature and utilized to develop a ligand-based common feature pharmacophore model. The validated pharmacophore model was further used for virtual screening of drug-like databases obtained from the Asinex, Specs, InterBioScreen, and Eximed chemical libraries. Utilizing computational methods such as molecular docking studies, molecular dynamics simulations, and binding free energy calculation, the binding mechanism of selected inhibitors was established. The identified Hits not only showed better binding energy when compared to Maraviroc, but also formed stable interactions with the key residues and showed stable behavior throughout the 100 ns MD simulation. Our findings suggest that Hit1 and Hit2 may be potential candidates for CCR5 inhibition, and, therefore, can be considered for further CCR5 inhibition programs.
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- 2022
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11. Novel Butein Derivatives Repress DDX3 Expression by Inhibiting PI3K/AKT Signaling Pathway in MCF-7 and MDA-MB-231 Cell Lines
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Shailima Rampogu, Seong Min Kim, Baji Shaik, Gihwan Lee, Ju Hyun Kim, Gon Sup Kim, Keun Woo Lee, and Myeong Ok Kim
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anticancer agents ,butein ,DDX3 ,cell cycle ,apoptosis ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
BackgroundBreast cancer is one of the major causes of mortalities noticed in women globally. DDX3 has emerged as a potent target for several cancers, including breast cancer to which currently there are no reported or approved drugs.MethodsTo find effective cancer therapeutics, three compounds were computationally designed tweaking the structure of natural compound butein. These compounds were synthesized and evaluated for their anticancer property in MCF-7 and MDA-MB-231 cell lines targeting DDX3. The in silico molecular docking studies have shown that the compounds have occupied the binding site of the human DDX3 target. Furthermore, to investigate the cell viability effect of 3a, 3b, and 3c on MCF-7 and MDA-MB-231 cell lines, the cell lines were treated with different concentrations of compounds for 24 and 48 h and measured using MTT assay.ResultsThe cell viability results showed that the have induced dose dependent suppression of DDX3 expression. Additionally, 3b and 3c have reduced the expression of DDX3 in MCF-7 and MDA-MD-231 cell lines. 3b or 3c treated cell lines increased apoptotic protein expression. Both the compounds have induced the apoptotic cell death by elevated levels of cleaved PARP and cleaved caspase 3 and repression of the anti-apoptosis protein BCL-xL. Additionally, they have demonstrated the G2/M phase cell cycle arrest in both the cell lines. Additionally, 3c decreased PI3K and AKT levels.ConclusionsOur results shed light on the anticancer ability of the designed compounds. These compounds can be employed as chemical spaces to design new prospective drug candidates. Additionally, our computational method can be adapted to design new chemical scaffolds as plausible inhibitors.
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- 2021
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12. Exploring the Binding Interaction of Raf Kinase Inhibitory Protein With the N-Terminal of C-Raf Through Molecular Docking and Molecular Dynamics Simulation
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Shraddha Parate, Shailima Rampogu, Gihwan Lee, Jong Chan Hong, and Keun Woo Lee
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RKIP ,C-Raf ,protein-protein docking ,HADDOCK ,ZDOCK ,molecular dynamics simulation ,Biology (General) ,QH301-705.5 - Abstract
Protein-protein interactions are indispensable physiological processes regulating several biological functions. Despite the availability of structural information on protein-protein complexes, deciphering their complex topology remains an outstanding challenge. Raf kinase inhibitory protein (RKIP) has gained substantial attention as a favorable molecular target for numerous pathologies including cancer and Alzheimer’s disease. RKIP interferes with the RAF/MEK/ERK signaling cascade by endogenously binding with C-Raf (Raf-1 kinase) and preventing its activation. In the current investigation, the binding of RKIP with C-Raf was explored by knowledge-based protein-protein docking web-servers including HADDOCK and ZDOCK and a consensus binding mode of C-Raf/RKIP structural complex was obtained. Molecular dynamics (MD) simulations were further performed in an explicit solvent to sample the conformations for when RKIP binds to C-Raf. Some of the conserved interface residues were mutated to alanine, phenylalanine and leucine and the impact of mutations was estimated by additional MD simulations and MM/PBSA analysis for the wild-type (WT) and constructed mutant complexes. Substantial decrease in binding free energy was observed for the mutant complexes as compared to the binding free energy of WT C-Raf/RKIP structural complex. Furthermore, a considerable increase in average backbone root mean square deviation and fluctuation was perceived for the mutant complexes. Moreover, per-residue energy contribution analysis of the equilibrated simulation trajectory by HawkDock and ANCHOR web-servers was conducted to characterize the key residues for the complex formation. One residue each from C-Raf (Arg398) and RKIP (Lys80) were identified as the druggable “hot spots” constituting the core of the binding interface and corroborated by additional long-time scale (300 ns) MD simulation of Arg398Ala mutant complex. A notable conformational change in Arg398Ala mutant occurred near the mutation site as compared to the equilibrated C-Raf/RKIP native state conformation and an essential hydrogen bonding interaction was lost. The thirteen binding sites assimilated from the overall analysis were mapped onto the complex as surface and divided into active and allosteric binding sites, depending on their location at the interface. The acquired information on the predicted 3D structural complex and the detected sites aid as promising targets in designing novel inhibitors to block the C-Raf/RKIP interaction.
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- 2021
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13. Computational Simulations Identified Marine-Derived Natural Bioactive Compounds as Replication Inhibitors of SARS-CoV-2
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Vikas Kumar, Shraddha Parate, Sanghwa Yoon, Gihwan Lee, and Keun Woo Lee
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COVID-19 ,3CLcpsdummypro ,PLcpsdummypro ,RdRp ,molecular dynamics simulations (MD) ,MM/PBSA binding free energy ,Microbiology ,QR1-502 - Abstract
The rapid spread of COVID-19, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide health emergency. Unfortunately, to date, a very small number of remedies have been to be found effective against SARS-CoV-2 infection. Therefore, further research is required to achieve a lasting solution against this deadly disease. Repurposing available drugs and evaluating natural product inhibitors against target proteins of SARS-CoV-2 could be an effective approach to accelerate drug discovery and development. With this strategy in mind, we derived Marine Natural Products (MNP)-based drug-like small molecules and evaluated them against three major target proteins of the SARS-CoV-2 virus replication cycle. A drug-like database from MNP library was generated using Lipinski’s rule of five and ADMET descriptors. A total of 2,033 compounds were obtained and were subsequently subjected to molecular docking with 3CLpro, PLpro, and RdRp. The docking analyses revealed that a total of 14 compounds displayed better docking scores than the reference compounds and have significant molecular interactions with the active site residues of SARS-CoV-2 virus targeted proteins. Furthermore, the stability of docking-derived complexes was analyzed using molecular dynamics simulations and binding free energy calculations. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, binding affinity, and molecular interactions. Our investigation identified two hit compounds against each targeted proteins displaying stable behavior, higher binding affinity and key residual molecular interactions, with good in silico pharmacokinetic properties, therefore can be considered for further in vitro studies.
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- 2021
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14. Molecular Docking and Molecular Dynamics Simulations Discover Curcumin Analogue as a Plausible Dual Inhibitor for SARS-CoV-2
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Shailima Rampogu, Gihwan Lee, Jun Sung Park, Keun Woo Lee, and Myeong Ok Kim
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natural compound analogues ,main protease ,SARS-CoV-2 ,DDX3 ,dual inhibitor ,Biology (General) ,QH301-705.5 ,Chemistry ,QD1-999 - Abstract
Recently, the world has been witnessing a global pandemic with no effective therapeutics yet, while cancer continues to be a major disease claiming many lives. The natural compound curcumin is bestowed with multiple medicinal applications in addition to demonstrating antiviral and anticancer activities. In order to elucidate the impact of curcumin on COVID-19 and cancer, the current investigation has adapted several computational techniques to unfold its possible inhibitory activity. Accordingly, curcumin and similar compounds and analogues were retrieved and assessed for their binding affinities at the binding pocket of SARS-CoV-2 main protease and DDX3. The best binding pose was escalated to molecular dynamics simulation (MDS) studies to assess the time dependent stability. Our findings have rendered one compound that has demonstrated good molecular dock score complemented by key residue interactions and have shown stable MDS results inferred by root mean square deviation (RMSD), radius of gyration (Rg), binding mode, hydrogen bond interactions, and interaction energy. Essential dynamics results have shown that the systemadapts minimum energy conformation to attain a stable state. The discovered compound (curA) could act as plausible inhibitor against SARS-CoV-2 and DDX3. Furthermore, curA could serve as a chemical scaffold for designing and developing new compounds.
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- 2022
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15. Computational Simulations Highlight the IL2Rα Binding Potential of Polyphenol Stilbenes from Fenugreek
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Apoorva M. Kulkarni, Shraddha Parate, Gihwan Lee, Yongseong Kim, Tae Sung Jung, Keun Woo Lee, and Min Woo Ha
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phytochemicals ,stilbenes ,IL2Rα ,rhaponticin ,fenugreek ,drug discovery ,Organic chemistry ,QD241-441 - Abstract
Widely used in global households, fenugreek is well known for its culinary and medicinal uses. The various reported medicinal properties of fenugreek are by virtue of the different natural phytochemicals present in it. Regarded as a promising target, interleukin 2 receptor subunit alpha (IL2Rα) has been shown to influence immune responses. In the present research, using in silico techniques, we have demonstrated the potential IL2Rα binding properties of three polyphenol stilbenes (desoxyrhaponticin, rhaponticin, rhapontigenin) from fenugreek. As the first step, molecular docking was performed to assess the binding potential of the fenugreek phytochemicals with IL2Rα. All three phytochemicals demonstrated interactions with active site residues. To confirm the reliability of our molecular docking results, 100 ns molecular dynamics simulations studies were undertaken. As discerned by the RMSD and RMSF analyses, IL2Rα in complex with the desoxyrhaponticin, rhaponticin, and rhapontigenin indicated stability. The RMSD analysis of the phytochemicals alone also demonstrated no significant structural changes. Based on the stable molecular interactions and comparatively slightly better MM/PBSA binding free energy, rhaponticin seems promising. Additionally, ADMET analysis performed for the stilbenes indicated that all of them obey the ADMET rules. Our computational study thus supports further in vitro IL2Rα binding studies on these stilbenes, especially rhaponticin.
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- 2022
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16. Fast and Efficient Union of Sparse Orthonormal Transforms via DCT and Bayesian Optimization
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Gihwan Lee and Yoonsik Choe
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sparse coding ,orthogonal sparse coding ,dictionary learning ,image transform ,sparse orthonormal transform ,Technology ,Engineering (General). Civil engineering (General) ,TA1-2040 ,Biology (General) ,QH301-705.5 ,Physics ,QC1-999 ,Chemistry ,QD1-999 - Abstract
Sparse orthonormal transform is based on orthogonal sparse coding, which is relatively fast and suitable in image compression such as analytic transforms with better performance. However, because of the constraints on its dictionary, it has performance limitations. This paper proposes an extension of a sparse orthonormal transform based on unions of orthonormal dictionaries for image compression. Unlike unions of orthonormal bases (UONB), which implement an overcomplete dictionary with several orthonormal dictionaries, the proposed method allocates patches to an orthonormal dictionary based on their directions. The dictionaries are constructed into a discrete cosine transform and an orthonormal matrix. To determine a trade-off parameter between the reconstruction error and sparsity, which hinders efficient implementation, the proposed method adapts Bayesian optimization. The framework exhibits an improved performance with fast implementation to determine the optimal parameter. It is verified that the proposed method performs similar to an overcomplete dictionary with a faster speed via experiments.
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- 2022
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17. Identification of New KRAS G12D Inhibitors through Computer-Aided Drug Discovery Methods
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Apoorva M. Kulkarni, Vikas Kumar, Shraddha Parate, Gihwan Lee, Sanghwa Yoon, and Keun Woo Lee
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KRAS ,in silico ,pharmacophore ,virtual screening ,molecular docking ,molecular dynamics simulations ,Biology (General) ,QH301-705.5 ,Chemistry ,QD1-999 - Abstract
Owing to several mutations, the oncogene Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) is activated in the majority of cancers, and targeting it has been pharmacologically challenging. In this study, using an in silico approach comprised of pharmacophore modeling, molecular docking, and molecular dynamics simulations, potential KRAS G12D inhibitors were investigated. A ligand-based common feature pharmacophore model was generated to identify the framework necessary for effective KRAS inhibition. The chemical features in the selected pharmacophore model comprised two hydrogen bond donors, one hydrogen bond acceptor, two aromatic rings and one hydrophobic feature. This model was used for screening in excess of 214,000 compounds from InterBioScreen (IBS) and ZINC databases. Eighteen compounds from the IBS and ten from the ZINC database mapped onto the pharmacophore model and were subjected to molecular docking. Molecular docking results highlighted a higher affinity of four hit compounds towards KRAS G12D in comparison to the reference inhibitor, BI-2852. Sequential molecular dynamics (MD) simulation studies revealed all four hit compounds them possess higher KRAS G12D binding free energy and demonstrate stable polar interaction with key residues. Further, Principal Component Analysis (PCA) analysis of the hit compounds in complex with KRAS G12D also indicated stability. Overall, the research undertaken provides strong support for further in vitro testing of these newly identified KRAS G12D inhibitors, particularly Hit1 and Hit2.
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- 2022
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18. Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations
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Vikas Kumar, Shraddha Parate, Gunjan Thakur, Gihwan Lee, Hyeon-Su Ro, Yongseong Kim, Hong Ja Kim, Myeong Ok Kim, and Keun Woo Lee
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CDK7 ,cancer ,pharmacophore ,molecular docking ,MD simulation ,MM-PBSA ,Biology (General) ,QH301-705.5 - Abstract
The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits—ZINC20392430, SN00112175, SN00004718, and SN00262261—having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.
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- 2021
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19. Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer
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Danishuddin, Vikas Kumar, Shraddha Parate, Ashutosh Bahuguna, Gihwan Lee, Myeong Ok Kim, and Keun Woo Lee
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cancer ,epigenetic ,PRC2 ,machine learning ,multi-class models ,Medicine ,Pharmacy and materia medica ,RS1-441 - Abstract
Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is an important drug target for controlling cancer via epigenetic processes. In the present study, we have developed various predictive models for modeling the inhibitory activity of EZH2. Binary and multiclass models were built using SVM, random forest and XGBoost methods. Rigorous validation approaches including predictiveness curve, Y-randomization and applicability domain (AD) were employed for evaluation of the developed models. Eighteen descriptors selected from Boruta methods have been used for modeling. For binary classification, random forest and XGBoost achieved an accuracy of 0.80 and 0.82, respectively, on external test set. Contrastingly, for multiclass models, random forest and XGBoost achieved an accuracy of 0.73 and 0.75, respectively. 500 Y-randomization runs demonstrate that the models were robust and the correlations were not by chance. Evaluation metrics from predictiveness curve show that the selected eighteen descriptors predict active compounds with total gain (TG) of 0.79 and 0.59 for XGBoost and random forest, respectively. Validated models were further used for virtual screening and molecular docking in search of potential hits. A total of 221 compounds were commonly predicted as active with above the set probability threshold and also under the AD of training set. Molecular docking revealed that three compounds have reasonable binding energy and favorable interactions with critical residues in the active site of EZH2. In conclusion, we highlighted the potential of rigorously validated models for accurately predicting and ranking the activities of lead molecules against cancer epigenetic targets. The models presented in this study represent the platform for development of EZH2 inhibitors.
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- 2021
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20. Marine-Derived Natural Products as ATP-Competitive mTOR Kinase Inhibitors for Cancer Therapeutics
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Shraddha Parate, Vikas Kumar, Gihwan Lee, Shailima Rampogu, Jong Chan Hong, and Keun Woo Lee
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mTOR kinase ,marine natural products ,ATP-competitive inhibitors ,structure-based pharmacophore modeling ,virtual screening ,molecular docking ,Medicine ,Pharmacy and materia medica ,RS1-441 - Abstract
The mammalian target of rapamycin (mTOR) is a serine/threonine kinase portraying a quintessential role in cellular proliferation and survival. Aberrations in the mTOR signaling pathway have been reported in numerous cancers including thyroid, lung, gastric and ovarian cancer, thus making it a therapeutic target. To attain this objective, an in silico investigation was designed, employing a pharmacophore modeling approach. A structure-based pharmacophore (SBP) model exploiting the key features of a selective mTOR inhibitor, Torkinib directed at the ATP-binding pocket was generated. A Marine Natural Products (MNP) library was screened using SBP model as a query. The retrieved compounds after consequent drug-likeness filtration were subjected to molecular docking with mTOR, thus revealing four MNPs with better scores than Torkinib. Successive refinement via molecular dynamics simulations demonstrated that the hits formed crucial interactions with key residues of the pocket. Furthermore, the four identified hits exhibited good binding free energy scores through MM-PBSA calculations and the subsequent in silico toxicity assessments displayed three hits deemed essentially non-carcinogenic and non-mutagenic. The hits presented in this investigation could act as potent ATP-competitive mTOR inhibitors, representing a platform for the future discovery of drugs from marine natural origin.
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- 2021
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21. In Silico Study Identified Methotrexate Analog as Potential Inhibitor of Drug Resistant Human Dihydrofolate Reductase for Cancer Therapeutics
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Rabia Mukhtar Rana, Shailima Rampogu, Noman Bin Abid, Amir Zeb, Shraddha Parate, Gihwan Lee, Sanghwa Yoon, Yumi Kim, Donghwan Kim, and Keun Woo Lee
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methotrexate ,drug resistance ,human dihydrofolate reductase ,pharmacophore modeling ,virtual screening ,molecular docking ,Organic chemistry ,QD241-441 - Abstract
Drug resistance is a core issue in cancer chemotherapy. A known folate antagonist, methotrexate (MTX) inhibits human dihydrofolate reductase (hDHFR), the enzyme responsible for the catalysis of 7,8-dihydrofolate reduction to 5,6,7,8-tetrahydrofolate, in biosynthesis and cell proliferation. Structural change in the DHFR enzyme is a significant cause of resistance and the subsequent loss of MTX. In the current study, wild type hDHFR and double mutant (engineered variant) F31R/Q35E (PDB ID: 3EIG) were subject to computational study. Structure-based pharmacophore modeling was carried out for wild type (WT) and mutant (MT) (variant F31R/Q35E) hDHFR structures by generating ten models for each. Two pharmacophore models, WT-pharma and MT-pharma, were selected for further computations, and showed excellent ROC curve quality. Additionally, the selected pharmacophore models were validated by the Guner-Henry decoy test method, which yielded high goodness of fit for WT-hDHFR and MT-hDHFR. Using a SMILES string of MTX in ZINC15 with the selections of ‘clean’, in vitro and in vivo options, 32 MTX-analogs were obtained. Eight analogs were filtered out due to their drug-like properties by applying absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment tests and Lipinski’s Rule of five. WT-pharma and MT-pharma were further employed as a 3D query in virtual screening with drug-like MTX analogs. Subsequently, seven screening hits along with a reference compound (MTX) were subjected to molecular docking in the active site of WT- and MT-hDHFR. Through a clustering analysis and examination of protein-ligand interactions, one compound was found with a ChemPLP fitness score greater than that of MTX (reference compound). Finally, a simulation of molecular dynamics (MD) identified an MTX analog which exhibited strong affinity for WT- and MT-hDHFR, with stable RMSD, hydrogen bonds (H-bonds) in the binding site and the lowest MM/PBSA binding free energy. In conclusion, we report on an MTX analog which is capable of inhibiting hDHFR in wild type form, as well as in cases where the enzyme acquires resistance to drugs during chemotherapy treatment.
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- 2020
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22. A Computational Approach with Biological Evaluation: Combinatorial Treatment of Curcumin and Exemestane Synergistically Regulates DDX3 Expression in Cancer Cell Lines
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Shailima Rampogu, Seong Min Kim, Minky Son, Ayoung Baek, Chanin Park, Gihwan Lee, Yumi Kim, Gon Sup Kim, Ju Hyun Kim, and Keun Woo Lee
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DDX3 ,cancers ,natural compounds ,combinatorial treatment ,Microbiology ,QR1-502 - Abstract
DDX3 belongs to RNA helicase family that demonstrates oncogenic properties and has gained wider attention due to its role in cancer progression, proliferation and transformation. Mounting reports have evidenced the role of DDX3 in cancers making it a promising target to abrogate DDX3 triggered cancers. Dual pharmacophore models were generated and were subsequently validated. They were used as 3D queries to screen the InterBioScreen database, resulting in the selection of curcumin that was escalated to molecular dynamics simulation studies. In vitro anti-cancer analysis was conducted on three cell lines such as MCF-7, MDA-MB-231 and HeLa, which were evaluated along with exemestane. Curcumin was docked into the active site of the protein target (PDB code 2I4I) to estimate the binding affinity. The compound has interacted with two key residues and has displayed stable molecular dynamics simulation results. In vitro analysis has demonstrated that both the candidate compounds have reduced the expression of DDX3 in three cell lines. However, upon combinatorial treatment of curcumin (10 and 20 μM) and exemestane (50 μM) a synergism was exhibited, strikingly downregulating the DDX3 expression and has enhanced apoptosis in three cell lines. The obtained results illuminate the use of curcumin as an alternative DDX3 inhibitor and can serve as a chemical scaffold to design new small molecules.
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- 2020
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23. In Silico Study Probes Potential Inhibitors of Human Dihydrofolate Reductase for Cancer Therapeutics
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Rabia Mukhtar Rana, Shailima Rampogu, Amir Zeb, Minky Son, Chanin Park, Gihwan Lee, Sanghwa Yoon, Ayoung Baek, Sarvanan Parameswaran, Seok Ju Park, and Keun Woo Lee
- Subjects
dihydrofolate reductase inhibition ,pharmacophore modeling ,molecular docking ,molecular dynamics simulation ,binding free energy ,Medicine - Abstract
Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes the reduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of human DHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cell proliferation. In the current study, ligand-based pharmacophore modeling identified and evaluated the critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generated from known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS) deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features, including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and one hydrophobic (HYP). Hypo1 was validated using Fischer’s randomization, test set, and decoy set validations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex, National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered by an absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test and Lipinski’s rule of five, where the drug-like hit compounds were identified. The hit compounds were docked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67 (docking score for the reference compound), clustering analysis, and hydrogen bond interactions were identified. Furthermore, molecular dynamics (MD) simulation identified three compounds as the best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogen bond interactions with hDHFR, and low binding free energy (−127 kJ/mol to −178 kJ/mol). Finally, the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFR in human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoid arthritis chemotherapeutics.
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- 2019
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24. Discovery of Non-Peptidic Compounds against Chagas Disease Applying Pharmacophore Guided Molecular Modelling Approaches
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Shailima Rampogu, Gihwan Lee, Ayoung Baek, Minky Son, Chanin Park, Amir Zeb, Sang Hwa Yoon, Suhyeon Park, and Keun Woo Lee
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Chagas disease ,Trypanosome cruzi ,cruzipian ,cysteine protease ,molecular docking simulations ,molecular dynamics simulations ,Organic chemistry ,QD241-441 - Abstract
Chagas disease is one of the primary causes of heart diseases accounting to 50,000 lives annually and is listed as the neglected tropical disease. Because the currently available therapies have greater toxic effects with higher resistance, there is a dire need to develop new drugs to combat the disease. In this pursuit, the 3D QSAR ligand-pharmacophore (pharm 1) and receptor-based pharmacophore (pharm 2) search was initiated to retrieve the candidate compounds from universal natural compounds database. The validated models were allowed to map the universal natural compounds database. The obtained lead candidates were subjected to molecular docking against cysteine protease (PDB code: 1ME3) employing -Cdocker available on the discovery studio. Subsequently, two Hits have satisfied the selection criteria and were escalated to molecular dynamics simulation and binding free energy calculations. These Hits have demonstrated higher dock scores, displayed interactions with the key residues portraying an ideal binding mode complemented by mapping to all the features of pharm 1 and pharm 2. Additionally, they have rendered stable root mean square deviation (RMSD) and potential energy profiles illuminating their potentiality as the prospective antichagastic agents. The study further demonstrates the mechanism of inhibition by tetrad residues compromising of Gly23 and Asn70 holding the ligand at each ends and the residues Gly65 and Gly160 clamping the Hits at the center. The notable feature is that the Hits lie in close proximity with the residues Glu66 and Leu67, accommodating within the S1, S2 and S3 subsites. Considering these findings, the study suggests that the Hits may be regarded as effective therapeutics against Chagas disease.
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- 2018
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25. Fast and Efficient Union of Sparse Orthonormal Transform for Image Compression.
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Gihwan Lee and Yoonsik Choe
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- 2021
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26. Unravelling the therapeutic potential of marine drugs as SARS-CoV-2 inhibitors: An insight from essential dynamics and free energy landscape.
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Shailima Rampogu, Rajesh Goud Gajula, Gihwan Lee, Myeong Ok Kim, and Keun Woo Lee
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- 2021
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27. Short communication for targeting natural compounds against HER2 kinase domain as potential anticancer drugs applying pharmacophore based molecular modelling approaches- part 2.
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Shailima Rampogu, Gihwan Lee, Ravinder Doneti, and Keun Woo Lee
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- 2020
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28. Gradient-Applied Weighted Loss for Details of 3D Shape in Single-View Reconstruction
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Jiho Lee, Taehyeon Kim, Gihwan Lee, and Yoonsik Choe
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electrical_electronic_engineering - Abstract
There has been considerable research on reconstructing 3D shapes from single-view images; however, preserving the detailed information of the input image remains difficult. In this paper, we propose the application of a gradient map to train a network, aimed at improving the visual quality of fine-grained details such as the thin and tiny components of generated shapes. Each gradient map was created from the original voxel data, and each value represented the amount of information per volume. Here, the gradient map was defined by several methods that mathematically quantify and represent the detailed structure of an object. By applying this map to the loss function in training, we could induce the network to intensively train partial details, such as thin and narrow parts. We demonstrated that the detailed information was well-recovered when a weight that is proportional to the gradient value was applied to the loss. Furthermore, it is expected that our method will contribute to the development of 3D technologies related to the construction of virtual space for simulation and new customer experience.
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- 2022
29. Soybean phytochemicals responsible for bacterial neuraminidase inhibition and their characterization by UPLC-ESI-TOF/MS
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Aizhamal Baiseitova, Yeong Jun Ban, Jeong Yoon Kim, Gihwan Lee, Abdul Bari Shah, Jeong Ho Kim, Yong Hyun Lee, and Ki Hun Park
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Molecular Docking Simulation ,Kinetics ,Plant Extracts ,Phytochemicals ,Neuraminidase ,Fabaceae ,General Medicine ,Soybeans ,Saponins ,Chromatography, High Pressure Liquid ,Food Science - Abstract
Ethanol extract of soybean (Glycine max (L.) Merr.) showed good inhibitory activity against bacterial neuraminidase (BNA), which plays a pivotal role in the pathogenesis of a number of microbial diseases.
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- 2022
30. Image Compression Based on a Partially Rotated Discrete Cosine Transform With a Principal Orientation
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Yoonsik Choe and Gihwan Lee
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Data compaction ,Directional discrete cosine transform ,General Computer Science ,Iterative method ,Computer science ,Orientation (computer vision) ,General Engineering ,image compression ,TK1-9971 ,Reduction (complexity) ,image transformation ,Discrete cosine transform ,sparse coding transform ,General Materials Science ,Electrical engineering. Electronics. Nuclear engineering ,discrete cosine transform ,Algorithm ,Sparse matrix ,Image compression ,Data compression - Abstract
Image transforms are necessary for image and video compression. Analytic transforms are powerful in compacting natural signals for wider exploitation. Various methods have been introduced to represent such data as a small number of bases, and several of these methods use machine learning, usually based on sparse coding, to outperform analytic transforms. They show sufficient data compaction abilities. However, these methods focus only on data compaction and reconstruction performance, without considering computational issues during implementation. We introduce a new framework for a more efficient transform based on a two-dimensional discrete cosine transform (DCT) and its characteristics. We aimed to improve the data compaction ability of transforms to levels better or similar to that of the DCT and other data-driven transforms, with fast and efficient implementation. We focused on the properties of the DCT, including horizontal and vertical directional information, and approximated its direction using the transform. Our framework was designed by rotating some of the DCT bases to fit this direction. As expected, our framework achieves a transform design with minimized computation for efficient implementation. It does not require an iterative algorithm or brute-force methods to find the best transform matrix or other parameters, thereby making it much faster than other methods. Our framework is 10 times faster than the steerable DCT (SDCT) and twice as fast as the eight-level SDCT with minimum performance reduction. Experimental validation with various images indicates that the proposed method sufficiently approaches the performance of the other transforms despite faster implementation.
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- 2021
31. New dihydrobenzoxanthone derivatives with bacterial neuraminidase inhibitory activity isolated from Artocarpus elasticus
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Aizhamal Baiseitova, Gihwan Lee, Abdul Bari Shah, Sanghwa Yoon, Jeong Ho Kim, Yong Hyun Lee, and Ki Hun Park
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Flavonoids ,Molecular Docking Simulation ,Bacteria ,Plant Extracts ,Organic Chemistry ,Drug Discovery ,Phytochemicals ,Neuraminidase ,Molecular Biology ,Biochemistry ,Artocarpus - Abstract
Artocarpus elasticus is a popular fruit tree in the tropical regions. Primary screenings of methanol extracts of the root bark confirmed its potent inhibition of bacterial neuraminidase (BNA), which plays an essential role in the pathogenesis of many microbial diseases. Assessments of the responsible phytochemicals were conducted by isolating eight compounds (1-8) and two of them (6 and 8) were identified as new compounds. Among the isolates, the dihydrobenzoxanthones attained the highest BNA inhibition with IC
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- 2022
32. Integration of virtual screening and computational simulation identifies photodynamic therapeutics against human Protoporphyrinogen Oxidase IX (hPPO)
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Seok Ju Park, Ayoung Baek, Amir Zeb, Yeongrae Cho, Minky Son, Gihwan Lee, Youn-Sig Kwak, Donghwan Kim, Keun Woo Lee, Shailima Rampogu, and Chanin Park
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Virtual screening ,Protoporphyrin IX ,biology ,Chemistry ,General Chemical Engineering ,Active site ,General Chemistry ,Combinatorial chemistry ,lcsh:Chemistry ,chemistry.chemical_compound ,lcsh:QD1-999 ,Docking (molecular) ,Lipinski's rule of five ,biology.protein ,Photosensitizer ,Protoporphyrinogen oxidase ,Pharmacophore - Abstract
Photodynamic therapy (PDT) is a rapidly evolving area of cancer management against solid tumors. PDT is either administrated by injecting photosensitizer (porphyrins) or by accumulation of intracellular protoporphyrin IX via the inhibition of human Protoporphyrinogen Oxidase IX (hPPO). In this study, novel inhibitors of hPPO have been investigated by integrating virtual screening, molecular docking, and molecular dynamics (MD) simulation. A ligand-based pharmacophore was generated from a training set of 22 inhibitors of hPPO. The selected pharmacophore had four chemical features including three hydrogen bond acceptors and one hydrophobic. The pharmacophore was characterized by highest correlation coefficient of 0.96, cost difference of 53.20, and lowest root mean square deviation of 0.73. The resultant pharmacophore was validated by Fischer’s Randomization and Test Set Validation methods. The validated pharmacophore was used as a 3D query to screen chemical databases including NCI, Asinex, Chembridge, and Maybridge. The screening of chemical databases and the subsequent application of Lipinski’s Rule of Five, and ADMET Assessment Test, retrieved 1176 drug-like compounds. The drug-like compounds were subjected to molecular docking studies in the active site of hPPO to eliminate false positive hits and to elucidate their true binding orientation. Top three candidate molecules with high docking scores and hydrogen bond interactions with catalytic active residues were selected as best candidate inhibitors against hPPO. The binding stability of selected candidate inhibitors was evaluated by MD simulation. The MD simulation of hits portrayed strong hydrogen bonds and key hydrophobic interactions with catalytic active residues of hPPO including R59, R97, G159, G332 and flavin moiety of FAD (coenzyme of hPPO). Our study predicts three hit compounds against hPPO, which could possibly accumulate high concentration of protoporphyrinogen-IX, and thereby acting as an intracellular photosensitizer against tumor cells through photodynamic therapy. Keywords: Photodynamic therapy (PDT), hPPO Inhibition, Virtual screening, Pharmacophore modeling, Molecular docking simulation, Molecular dynamics (MD) simulation
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- 2020
33. Identification of New KRAS G12D Inhibitors through Computer-Aided Drug Discovery Methods
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Apoorva M. Kulkarni, Vikas Kumar, Shraddha Parate, Gihwan Lee, Sanghwa Yoon, and Keun Woo Lee
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QH301-705.5 ,Quantitative Structure-Activity Relationship ,Molecular Dynamics Simulation ,Ligands ,Catalysis ,Inorganic Chemistry ,Proto-Oncogene Proteins p21(ras) ,Small Molecule Libraries ,Drug Discovery ,KRAS ,Humans ,Computer Simulation ,Physical and Theoretical Chemistry ,Biology (General) ,Molecular Biology ,QD1-999 ,Spectroscopy ,in silico ,pharmacophore ,virtual screening ,molecular docking ,molecular dynamics simulations ,Organic Chemistry ,Hydrogen Bonding ,General Medicine ,Computer Science Applications ,Molecular Docking Simulation ,Chemistry ,Drug Design ,Protein Binding - Abstract
Owing to several mutations, the oncogene Kirsten rat sarcoma 2 viral oncogene homolog (KRAS) is activated in the majority of cancers, and targeting it has been pharmacologically challenging. In this study, using an in silico approach comprised of pharmacophore modeling, molecular docking, and molecular dynamics simulations, potential KRAS G12D inhibitors were investigated. A ligand-based common feature pharmacophore model was generated to identify the framework necessary for effective KRAS inhibition. The chemical features in the selected pharmacophore model comprised two hydrogen bond donors, one hydrogen bond acceptor, two aromatic rings and one hydrophobic feature. This model was used for screening in excess of 214,000 compounds from InterBioScreen (IBS) and ZINC databases. Eighteen compounds from the IBS and ten from the ZINC database mapped onto the pharmacophore model and were subjected to molecular docking. Molecular docking results highlighted a higher affinity of four hit compounds towards KRAS G12D in comparison to the reference inhibitor, BI-2852. Sequential molecular dynamics (MD) simulation studies revealed all four hit compounds them possess higher KRAS G12D binding free energy and demonstrate stable polar interaction with key residues. Further, Principal Component Analysis (PCA) analysis of the hit compounds in complex with KRAS G12D also indicated stability. Overall, the research undertaken provides strong support for further in vitro testing of these newly identified KRAS G12D inhibitors, particularly Hit1 and Hit2.
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- 2021
34. REDD1 promotes obesity-induced metabolic dysfunction via atypical NF-κB activation
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Dong-Keon Lee, Taesam Kim, Junyoung Byeon, Minsik Park, Suji Kim, Joohwan Kim, Seunghwan Choi, Gihwan Lee, Chanin Park, Keun Woo Lee, Yong Jung Kwon, Jeong-Hyung Lee, Young-Guen Kwon, and Young-Myeong Kim
- Subjects
Inflammation ,Fatty Liver ,Mice ,Multidisciplinary ,NF-KappaB Inhibitor alpha ,NF-kappa B ,General Physics and Astronomy ,Animals ,Cytokines ,General Chemistry ,Obesity ,Amino Acids ,General Biochemistry, Genetics and Molecular Biology - Abstract
Regulated in development and DNA damage response 1 (REDD1) expression is upregulated in response to metabolic imbalance and obesity. However, its role in obesity-associated complications is unclear. Here, we demonstrate that the REDD1–NF-κB axis is crucial for metabolic inflammation and dysregulation. Mice lacking Redd1 in the whole body or adipocytes exhibited restrained diet-induced obesity, inflammation, insulin resistance, and hepatic steatosis. Myeloid Redd1-deficient mice showed similar results, without restrained obesity and hepatic steatosis. Redd1-deficient adipose-derived stem cells lost their potential to differentiate into adipocytes; however, REDD1 overexpression stimulated preadipocyte differentiation and proinflammatory cytokine expression through atypical IKK-independent NF-κB activation by sequestering IκBα from the NF-κB/IκBα complex. REDD1 with mutated Lys219/220Ala, key amino acid residues for IκBα binding, could not stimulate NF-κB activation, adipogenesis, and inflammation in vitro and prevented obesity-related phenotypes in knock-in mice. The REDD1-atypical NF-κB activation axis is a therapeutic target for obesity, meta-inflammation, and metabolic complications.
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- 2021
35. Identification of CDK7 Inhibitors from Natural Sources Using Pharmacoinformatics and Molecular Dynamics Simulations
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Gihwan Lee, Hong Ja Kim, Keun Woo Lee, Yongseong Kim, Shraddha Parate, Myeong Ok Kim, Gunjan Thakur, Hyeon-Su Ro, and Vikas Kumar
- Subjects
biology ,pharmacophore ,Chemistry ,QH301-705.5 ,In silico ,Pharmacoinformatics ,Cyclin-dependent kinase 2 ,CDK7 ,Medicine (miscellaneous) ,MD simulation ,Computational biology ,molecular docking ,Article ,General Biochemistry, Genetics and Molecular Biology ,MM-PBSA ,Protein kinase domain ,Docking (molecular) ,Cyclin-dependent kinase ,biology.protein ,cancer ,pharmacokinetic properties ,Cyclin-dependent kinase 7 ,Pharmacophore ,Biology (General) - Abstract
The cyclin-dependent kinase 7 (CDK7) plays a crucial role in regulating the cell cycle and RNA polymerase-based transcription. Overexpression of this kinase is linked with various cancers in humans due to its dual involvement in cell development. Furthermore, emerging evidence has revealed that inhibiting CDK7 has anti-cancer effects, driving the development of novel and more cost-effective inhibitors with enhanced selectivity for CDK7 over other CDKs. In the present investigation, a pharmacophore-based approach was utilized to identify potential hit compounds against CDK7. The generated pharmacophore models were validated and used as 3D queries to screen 55,578 natural drug-like compounds. The obtained compounds were then subjected to molecular docking and molecular dynamics simulations to predict their binding mode with CDK7. The molecular dynamics simulation trajectories were subsequently used to calculate binding affinity, revealing four hits—ZINC20392430, SN00112175, SN00004718, and SN00262261—having a better binding affinity towards CDK7 than the reference inhibitors (CT7001 and THZ1). The binding mode analysis displayed hydrogen bond interactions with the hinge region residues Met94 and Glu95, DFG motif residue Asp155, ATP-binding site residues Thr96, Asp97, and Gln141, and quintessential residue outside the kinase domain, Cys312 of CDK7. The in silico selectivity of the hits was further checked by docking with CDK2, the close homolog structure of CDK7. Additionally, the detailed pharmacokinetic properties were predicted, revealing that our hits have better properties than established CDK7 inhibitors CT7001 and THZ1. Hence, we argue that proposed hits may be crucial against CDK7-related malignancies.
- Published
- 2021
36. Novel Butein Derivatives Repress DDX3 Expression by Inhibiting PI3K/AKT Signaling Pathway in MCF-7 and MDA-MB-231 Cell Lines
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Gihwan Lee, Seong Min Kim, Baji Shaik, Keun Woo Lee, Shailima Rampogu, Myeong Ok Kim, Gon Sup Kim, and Ju Hyun Kim
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Cancer Research ,Chemistry ,apoptosis ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,butein ,Cell cycle ,anticancer agents ,chemistry.chemical_compound ,Oncology ,MCF-7 ,Cell culture ,DDX3 ,Cancer research ,cell cycle ,MTT assay ,Viability assay ,Protein kinase B ,RC254-282 ,PI3K/AKT/mTOR pathway ,Original Research ,Butein - Abstract
BackgroundBreast cancer is one of the major causes of mortalities noticed in women globally. DDX3 has emerged as a potent target for several cancers, including breast cancer to which currently there are no reported or approved drugs.MethodsTo find effective cancer therapeutics, three compounds were computationally designed tweaking the structure of natural compound butein. These compounds were synthesized and evaluated for their anticancer property in MCF-7 and MDA-MB-231 cell lines targeting DDX3. The in silico molecular docking studies have shown that the compounds have occupied the binding site of the human DDX3 target. Furthermore, to investigate the cell viability effect of 3a, 3b, and 3c on MCF-7 and MDA-MB-231 cell lines, the cell lines were treated with different concentrations of compounds for 24 and 48 h and measured using MTT assay.ResultsThe cell viability results showed that the have induced dose dependent suppression of DDX3 expression. Additionally, 3b and 3c have reduced the expression of DDX3 in MCF-7 and MDA-MD-231 cell lines. 3b or 3c treated cell lines increased apoptotic protein expression. Both the compounds have induced the apoptotic cell death by elevated levels of cleaved PARP and cleaved caspase 3 and repression of the anti-apoptosis protein BCL-xL. Additionally, they have demonstrated the G2/M phase cell cycle arrest in both the cell lines. Additionally, 3c decreased PI3K and AKT levels.ConclusionsOur results shed light on the anticancer ability of the designed compounds. These compounds can be employed as chemical spaces to design new prospective drug candidates. Additionally, our computational method can be adapted to design new chemical scaffolds as plausible inhibitors.
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- 2021
37. Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer
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Ashutosh Bahuguna, Shraddha Parate, Gihwan Lee, Keun Woo Lee, Vikas Kumar, Danishuddin, and Myeong Ok Kim
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Computer science ,multi-class models ,Pharmaceutical Science ,macromolecular substances ,Machine learning ,computer.software_genre ,Article ,Set (abstract data type) ,03 medical and health sciences ,Pharmacy and materia medica ,0302 clinical medicine ,Drug Discovery ,cancer ,030304 developmental biology ,0303 health sciences ,Virtual screening ,business.industry ,PRC2 ,Random forest ,RS1-441 ,Support vector machine ,machine learning ,Binary classification ,Ranking ,030220 oncology & carcinogenesis ,Test set ,Medicine ,Molecular Medicine ,Artificial intelligence ,business ,computer ,epigenetic ,Applicability domain - Abstract
Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is an important drug target for controlling cancer via epigenetic processes. In the present study, we have developed various predictive models for modeling the inhibitory activity of EZH2. Binary and multiclass models were built using SVM, random forest and XGBoost methods. Rigorous validation approaches including predictiveness curve, Y-randomization and applicability domain (AD) were employed for evaluation of the developed models. Eighteen descriptors selected from Boruta methods have been used for modeling. For binary classification, random forest and XGBoost achieved an accuracy of 0.80 and 0.82, respectively, on external test set. Contrastingly, for multiclass models, random forest and XGBoost achieved an accuracy of 0.73 and 0.75, respectively. 500 Y-randomization runs demonstrate that the models were robust and the correlations were not by chance. Evaluation metrics from predictiveness curve show that the selected eighteen descriptors predict active compounds with total gain (TG) of 0.79 and 0.59 for XGBoost and random forest, respectively. Validated models were further used for virtual screening and molecular docking in search of potential hits. A total of 221 compounds were commonly predicted as active with above the set probability threshold and also under the AD of training set. Molecular docking revealed that three compounds have reasonable binding energy and favorable interactions with critical residues in the active site of EZH2. In conclusion, we highlighted the potential of rigorously validated models for accurately predicting and ranking the activities of lead molecules against cancer epigenetic targets. The models presented in this study represent the platform for development of EZH2 inhibitors.
- Published
- 2021
38. Exploring the Binding Interaction of Raf Kinase Inhibitory Protein With the N-Terminal of C-Raf Through Molecular Docking and Molecular Dynamics Simulation
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Keun Woo Lee, Gihwan Lee, Shraddha Parate, Shailima Rampogu, and Jong Chan Hong
- Subjects
0301 basic medicine ,Conformational change ,QH301-705.5 ,Allosteric regulation ,Mutant ,protein-protein docking ,Biochemistry, Genetics and Molecular Biology (miscellaneous) ,Biochemistry ,RKIP ,03 medical and health sciences ,0302 clinical medicine ,MM/PBSA ,Native state ,Molecular Biosciences ,c-Raf ,Biology (General) ,Binding site ,Molecular Biology ,Original Research ,Alanine ,Chemistry ,ZDOCK ,binding sites prediction ,HADDOCK ,C-Raf ,molecular dynamics simulation ,030104 developmental biology ,Docking (molecular) ,030220 oncology & carcinogenesis ,Biophysics - Abstract
Protein-protein interactions are indispensable physiological processes regulating several biological functions. Despite the availability of structural information on protein-protein complexes, deciphering their complex topology remains an outstanding challenge. Raf kinase inhibitory protein (RKIP) has gained substantial attention as a favorable molecular target for numerous pathologies including cancer and Alzheimer’s disease. RKIP interferes with the RAF/MEK/ERK signaling cascade by endogenously binding with C-Raf (Raf-1 kinase) and preventing its activation. In the current investigation, the binding of RKIP with C-Raf was explored by knowledge-based protein-protein docking web-servers including HADDOCK and ZDOCK and a consensus binding mode of C-Raf/RKIP structural complex was obtained. Molecular dynamics (MD) simulations were further performed in an explicit solvent to sample the conformations for when RKIP binds to C-Raf. Some of the conserved interface residues were mutated to alanine, phenylalanine and leucine and the impact of mutations was estimated by additional MD simulations and MM/PBSA analysis for the wild-type (WT) and constructed mutant complexes. Substantial decrease in binding free energy was observed for the mutant complexes as compared to the binding free energy of WT C-Raf/RKIP structural complex. Furthermore, a considerable increase in average backbone root mean square deviation and fluctuation was perceived for the mutant complexes. Moreover, per-residue energy contribution analysis of the equilibrated simulation trajectory by HawkDock and ANCHOR web-servers was conducted to characterize the key residues for the complex formation. One residue each from C-Raf (Arg398) and RKIP (Lys80) were identified as the druggable “hot spots” constituting the core of the binding interface and corroborated by additional long-time scale (300 ns) MD simulation of Arg398Ala mutant complex. A notable conformational change in Arg398Ala mutant occurred near the mutation site as compared to the equilibrated C-Raf/RKIP native state conformation and an essential hydrogen bonding interaction was lost. The thirteen binding sites assimilated from the overall analysis were mapped onto the complex as surface and divided into active and allosteric binding sites, depending on their location at the interface. The acquired information on the predicted 3D structural complex and the detected sites aid as promising targets in designing novel inhibitors to block the C-Raf/RKIP interaction.
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- 2021
39. Computational Simulations Identified Marine-Derived Natural Bioactive Compounds as Replication Inhibitors of SARS-CoV-2
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Shraddha Parate, Sanghwa Yoon, Gihwan Lee, Keun Woo Lee, and Vikas Kumar
- Subjects
Microbiology (medical) ,RdRp ,In silico ,030303 biophysics ,Computational biology ,molecular dynamics simulations (MD) ,Microbiology ,03 medical and health sciences ,chemistry.chemical_compound ,3CLcpsdummypro ,030304 developmental biology ,Original Research ,MM/PBSA binding free energy ,0303 health sciences ,Natural product ,biology ,PLcpsdummypro ,Drug discovery ,Active site ,COVID-19 ,Small molecule ,In vitro ,QR1-502 ,chemistry ,Docking (molecular) ,biology.protein ,Lipinski's rule of five ,pharmacokinetic properties - Abstract
The rapid spread of COVID-19, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide health emergency. Unfortunately, to date, a very small number of remedies have been to be found effective against SARS-CoV-2 infection. Therefore, further research is required to achieve a lasting solution against this deadly disease. Repurposing available drugs and evaluating natural product inhibitors against target proteins of SARS-CoV-2 could be an effective approach to accelerate drug discovery and development. With this strategy in mind, we derived Marine Natural Products (MNP)-based drug-like small molecules and evaluated them against three major target proteins of the SARS-CoV-2 virus replication cycle. A drug-like database from MNP library was generated using Lipinski’s rule of five and ADMET descriptors. A total of 2,033 compounds were obtained and were subsequently subjected to molecular docking with 3CLpro, PLpro, and RdRp. The docking analyses revealed that a total of 14 compounds displayed better docking scores than the reference compounds and have significant molecular interactions with the active site residues of SARS-CoV-2 virus targeted proteins. Furthermore, the stability of docking-derived complexes was analyzed using molecular dynamics simulations and binding free energy calculations. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, binding affinity, and molecular interactions. Our investigation identified two hit compounds against each targeted proteins displaying stable behavior, higher binding affinity and key residual molecular interactions, with good in silico pharmacokinetic properties, therefore can be considered for further in vitro studies.
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- 2021
40. Investigation of novel chemical scaffolds targeting prolyl oligopeptidase for neurological therapeutics
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Shraddha Parate, Amir Zeb, Gihwan Lee, Saravanan Parameswaran, Rohit Bavi, Raj Kumar, Shailima Rampogu, Keun Woo Lee, Rabia Mukhtar Rana, Chanin Park, Minky Son, and Ayoung Baek
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Serine Proteinase Inhibitors ,Quantitative Structure-Activity Relationship ,Oligopeptidase ,Computational biology ,Molecular Dynamics Simulation ,01 natural sciences ,Workflow ,03 medical and health sciences ,Materials Chemistry ,Humans ,Physical and Theoretical Chemistry ,Spectroscopy ,030304 developmental biology ,0303 health sciences ,Virtual screening ,Binding Sites ,Training set ,Molecular Structure ,biology ,Chemistry ,Serine Endopeptidases ,Active site ,Hydrogen Bonding ,Computer Graphics and Computer-Aided Design ,0104 chemical sciences ,Molecular Docking Simulation ,010404 medicinal & biomolecular chemistry ,Docking (molecular) ,Drug Design ,biology.protein ,Cost analysis ,Nervous System Diseases ,Pharmacophore ,Prolyl Oligopeptidases ,Hydrophobic and Hydrophilic Interactions ,Databases, Chemical ,Chemical database ,Protein Binding - Abstract
Prolyl oligopeptidase (POP) is a potential therapeutic target for treatment of several neurological disorders and α-synucleinopathies including Parkinson's disease. Most of the known POP inhibitors failed in the clinical trials due to poor pharmacokinetic properties and blood-brain impermeability. Therefore, a training set of 30 structurally diverse compounds with a wide range of inhibitory activity against POP was used to generate a quantitative pharmacophore model, Hypo 3, to identify potential POP inhibitors with desirable drug-like properties. Validations through test set, cost analysis, and Fisher's randomization methods proved that Hypo 3 accurately predicted the known inhibitors among inactive compounds. Hypo 3 was employed as 3D query for virtual screening on an in-house drug-like chemical database containing compounds with good brain permeability and ADMET parameters. Database screening with Hypo 3 resulted in 99 compounds that were narrowed down to 21 compounds through molecular docking. Among them, five compounds were identified in our earlier studies, while two compounds showed in vitro POP inhibition. The current study proposed new 16 virtually screened compounds as potential inhibitors against POP that possess Gold docking score in the range of 64.61–75.74 and Chemscore of −32.25 to −38.35. Furthermore, the top scoring four hit compounds were subjected to molecular dynamics simulations to reveal their appropriate binding modes and assessing binding free energies. The hit compounds interacted with POP effectively via hydrogen bonds with important active site residues along with hydrophobic interactions. Moreover, the hit compounds had key inter-molecular interactions and better binding free energies as compared to the reference inhibitor. A potential new hydrogen bond interaction was discovered between Hit 2 with the Arg252 residue of POP. To conclude, we propose four hit compounds with new structural scaffolds against POP for the lead development of POP-based therapeutics for neurological disorders.
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- 2019
41. Pharmacotherapeutics and Molecular Mechanism of Phytochemicals in Alleviating Hormone-Responsive Breast Cancer
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Gihwan Lee, Minky Son, Raj Kumar, Shraddha Parate, Smita C. Pawar, Keun Woo Lee, Amir Zeb, Rohit Bavi, Yohan Park, Chanin Park, Seok Ju Park, D. Ravinder, Ayoung Baek, and Shailima Rampogu
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Hormone Responsive ,Drug ,Aging ,Article Subject ,media_common.quotation_subject ,Phytochemicals ,Breast Neoplasms ,Molecular Dynamics Simulation ,Pharmacology ,Biochemistry ,Molecular Docking Simulation ,Structure-Activity Relationship ,chemistry.chemical_compound ,Catalytic Domain ,Humans ,Structure–activity relationship ,lcsh:QH573-671 ,Aromatase ,media_common ,biology ,lcsh:Cytology ,Cell Biology ,General Medicine ,Hormones ,chemistry ,Curcumin ,biology.protein ,Thermodynamics ,Female ,Pharmacophore ,Research Article ,Discovery Studio - Abstract
Breast cancer (BC) is the leading cause of death among women worldwide devoid of effective treatment. It is therefore important to develop agents that can reverse, reduce, or slow the growth of BC. The use of natural products as chemopreventive agents provides enormous advantages. The aim of the current investigation is to determine the efficacy of the phytochemicals against BC along with the approved drugs to screen the most desirable and effective phytocompound. In the current study, 36 phytochemicals have been evaluated against aromatase to identify the potential candidate drug along with the approved drugs employing the Cdocker module accessible on the Discovery Studio (DS) v4.5 and thereafter analysing the stability of the protein ligand complex using GROningen MAchine for Chemical Simulations v5.0.6 (GROMACS). Additionally, these compounds were assessed for the inhibitory features employing the structure-based pharmacophore (SBP). The Cdocker protocol available with the DS has computed higher dock scores for the phytochemicals complemented by lower binding energies. The top-ranked compounds that have anchored with key residues located at the binding pocket of the protein were subjected to molecular dynamics (MD) simulations employing GROMACS. The resultant findings reveal the stability of the protein backbone and further guide to comprehend on the involvement of key residues Phe134, Val370, and Met374 that mechanistically inhibit BC. Among 36 compounds, curcumin, capsaicin, rosmarinic acid, and 6-shogaol have emerged as promising phytochemicals conferred with the highest Cdocker interaction energy, key residue interactions, stable MD results than reference drugs, and imbibing the key inhibitory features. Taken together, the current study illuminates the use of natural compounds as potential drugs against BC. Additionally, these compounds could also serve as scaffolds in designing and development of new drugs.
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- 2019
42. Modulation of aromatase by natural compounds—A pharmacophore guided molecular modelling simulations
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Gihwan Lee, Shailima Rampogu, Amir Zeb, Chanin Park, Ayoung Baek, Minky Son, and Keun Woo Lee
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0106 biological sciences ,Drug ,Quantitative structure–activity relationship ,biology ,Mechanism (biology) ,Chemistry ,media_common.quotation_subject ,Plant Science ,Computational biology ,Ligand (biochemistry) ,01 natural sciences ,0104 chemical sciences ,010404 medicinal & biomolecular chemistry ,DOCK ,biology.protein ,Aromatase ,Pharmacophore ,010606 plant biology & botany ,Discovery Studio ,media_common - Abstract
Globally, breast cancer is one of the primary reasons of death noticed in women. Despite continuous efforts to formulate effective treatments, search to identify promising therapeutics is underway. Consequently, a drug with low toxicity, high efficacy, and which can escape resistance mechanism is in a high demand. Natural compounds are bestowed with several medicinal properties demonstrating low toxicity. Therefore, the current research focuses on the use of several plant- derived chemical compounds against aromatase, a validated drug target for breast cancer. Correspondingly, employing the known inhibitors, a 3D QSAR pharmacophore model was generated and was subsequently validated. Using the three-featured pharmacophore as the 3D query, the alkaloids, flavonoids, coumarins and the AfroDB were scrupulously examined to retrieve the compounds with inhibitory activities complemented by the pharmacophore model. The obtained compounds were subjected to molecular docking studies executed employing the Cdocker accessible on discovery studio v4.5. The resultant ideal poses from the largest cluster conferred with key reside interactions and higher dock scores than the reference and the Food and Drug Administration (FDA) approved drugs were escalated to molecular dynamics simulation studies conducted employing GROMACS v5.0.6 for 30 ns. Correspondingly, the Hits (ZINC95486358, ZINC95486354, and ZINC90711737) have displayed stable root mean square deviations, coupled by appropriate positioning at the active site displaying greater number of hydrogen bonds. Moreover, the Hits (ZINC95486358, ZINC95486354, and ZINC90711737) were noticed to anchor with various key residues essential for clamping the ligand at the binding pocket. Therefore, these findings guide us to determine that the identified Hits can act effectively against breast cancer, thereby increasing the life expectancy. Furthermore, they can assist as scaffolds for designing novel drugs that aid in curing the cancer.
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- 2019
43. Computational Approaches to Discover Novel Natural Compounds for SARS-CoV-2 Therapeutics
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Gihwan Lee, Sanghwa Yoon, Keun Woo Lee, Shailima Rampogu, Myeong Ok Kim, Donghwan Kim, and Apoorva M Kulkarni
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Coronavirus disease 2019 (COVID-19) ,computational studies ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Computational biology ,Molecular Dynamics Simulation ,Viral Nonstructural Proteins ,010402 general chemistry ,01 natural sciences ,Molecular Docking Simulation ,Antiviral Agents ,Drug Discovery ,natural compounds ,Enzyme Inhibitors ,QD1-999 ,Virtual screening ,Biological Products ,Full Paper ,010405 organic chemistry ,Drug discovery ,Chemistry ,SARS-CoV-2 ,Natural compound ,COVID-19 ,General Chemistry ,Methyltransferases ,molecular docking ,Full Papers ,virtual screening ,0104 chemical sciences ,Docking (molecular) ,Lipinski's rule of five ,Software ,Protein Binding - Abstract
Scientists all over the world are facing a challenging task of finding effective therapeutics for the coronavirus disease (COVID‐19). One of the fastest ways of finding putative drug candidates is the use of computational drug discovery approaches. The purpose of the current study is to retrieve natural compounds that have obeyed to drug‐like properties as potential inhibitors. Computational molecular modelling techniques were employed to discover compounds with potential SARS‐CoV‐2 inhibition properties. Accordingly, the InterBioScreen (IBS) database was obtained and was prepared by minimizing the compounds. To the resultant compounds, the absorption, distribution, metabolism, excretion and toxicity (ADMET) and Lipinski's Rule of Five was applied to yield drug‐like compounds. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. In the current article, we have employed the docking based virtual screening method using InterBioScreen (IBS) natural compound database yielding two compounds has potential hits. These compounds have demonstrated higher binding affinity scores than the reference compound together with good pharmacokinetic properties. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results. Taken together, we advocate the use of two natural compounds, STOCK1N‐71493 and STOCK1N‐45683 as SARS‐CoV‐2 treatment regime., Computational molecular modelling techniques were employed to discover compounds with potential SARS‐CoV‐2 inhibition properties. The obtained compounds were subjected to molecular dynamics simulation studies to evaluate their stabilities. Additionally, the identified hits have displayed stable interaction results inferred by molecular dynamics simulation results.
- Published
- 2021
44. Fast and Efficient Union of Sparse Orthonormal Transform for Image Compression
- Author
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Yoonsik Choe and Gihwan Lee
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Computer science ,Orthonormal basis ,Algorithm ,Image compression - Published
- 2021
45. Soybean phytochemicals responsible for bacterial neuraminidase inhibition and their characterization by UPLC-ESI-TOF/MS.
- Author
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Baiseitova, Aizhamal, Yeong Jun Ban, Jeong Yoon Kim, Gihwan Lee, Shah, Abdul Bari, Jeong Ho Kim, Yong Hyun Lee, and Ki Hun Park
- Published
- 2022
- Full Text
- View/download PDF
46. Inhibitory mechanism of O-methylated quercetins, highly potent β-secretase inhibitors isolated from Caragana balchaschensis (Kom.) Pojark
- Author
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Jeong Yoon Kim, Abdul Bari Shah, Aizhamal Baiseitova, Keun Woo Lee, Kamila Zhumanova, Jeong Ho Kim, Ki Hun Park, and Gihwan Lee
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Spectrometry, Mass, Electrospray Ionization ,ADAM10 ,Caragana ,Methylation ,03 medical and health sciences ,chemistry.chemical_compound ,Structure-Activity Relationship ,0302 clinical medicine ,Non-competitive inhibition ,Glucoside ,Tandem Mass Spectrometry ,Drug Discovery ,Enzyme Inhibitors ,Medicinal plants ,IC50 ,Chromatography, High Pressure Liquid ,030304 developmental biology ,Pharmacology ,chemistry.chemical_classification ,0303 health sciences ,biology ,Chemistry ,Plant Extracts ,Plant Components, Aerial ,biology.organism_classification ,Molecular Docking Simulation ,Kinetics ,Enzyme ,Biochemistry ,030220 oncology & carcinogenesis ,Quercetin ,Amyloid Precursor Protein Secretases ,Protein Binding - Abstract
Ethnopharmacological relevance Caragana has a standing history of implementation in Traditional Chinese Medicine (TCM). Most species of this genus have been explored for multi-functional purposes, such as promoting blood circulation and curing neuralgia, fatigue, migraine, arthritis, and vascular hypertension (Meng et al., 2009). Among them, the well-known species C. sinica showed the most promising potential to increase the expression of ADAM10 among 313 tested medicinal plants, which is one of the promising approach for the treatment of Alzheimer's disease (AD). (Schuck et al., 2015). Aim of this study The aim of this work is to explore β-secretase inhibitory activity of compounds isolated from the aerial part of endemic Caragana balchaschensis (Kom.) Pojark. We provided a full characterization of their inhibitory mechanisms, binding affinities, and binding modes. Materials and methods The isolation of quercetin derivatives was accomplished by various chromatographical approaches and their structures were annotated by spectroscopic analysis. The detailed kinetic behavior of β-secretase inhibitors was determined by estimation of kinetic parameters (Km, Vmax, KI, and KIS). Binding affinities (KSV) and binding modes of inhibitors were elucidated by fluorescence quenching and molecular docking studies, respectively. Results O-methylated quercetins (2-7) were significantly effective in β-secretase inhibition with IC50 ranging from 1.2 to 6.5 μM. The most active one (6) was 20-fold effective than the mother skeleton, quercetin. The O-methyl motif was a critical factor in β-secretase inhibition: tri-O-methylated (1.2 μM) > di-O-methylated (3.5 μM) > mono-O-methylated (6.5 μM) > quercetin (25.2 μM). In the kinetic study, all quercetins (1–7) showed a noncompetitive inhibition, but glucoside ones (8 and 9) were mixed type I inhibitors. The binding affinities (KSV) were agreed with inhibitory potencies. The O-methylated quercetins were annotated as the most natural abundant metabolites in the aerial part by LC-ESI-TOF/MS. Binding modes of inhibitors to enzyme were elucidated by molecular docking experiments. Conclusion This study disclosed that most of the major phenolic metabolites of the aerial part of C. balchaschensis are O-methylated quercetins, which have a significant inhibitory effect on β-secretase, which is a critical factor for AD.
- Published
- 2020
47. 3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Dynamics Simulations for the Identification of Spleen Tyrosine Kinase Inhibitors.
- Author
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Kumar, Vikas, Parate, Shraddha, Danishuddin, Zeb, Amir, Singh, Pooja, Gihwan Lee, Tae Sung Jung, Keun Woo Lee, and Min Woo Ha
- Subjects
MOLECULAR dynamics ,PROTEIN-tyrosine kinase inhibitors ,SPLEEN ,PROTEIN-tyrosine kinases ,HYDROGEN bonding interactions ,MOLECULAR interactions - Abstract
Spleen tyrosine kinase (SYK) is an essential mediator of immune cell signaling and has been anticipated as a therapeutic target for autoimmune diseases, notably rheumatoid arthritis, allergic rhinitis, asthma, and cancers. Significant attempts have been undertaken in recent years to develop SYK inhibitors; however, limited success has been achieved due to poor pharmacokinetics and adverse effects of inhibitors. The primary goal of this research was to identify potential inhibitors having high affinity, selectivity based on key molecular interactions, and good drug-like properties than the available inhibitor, fostamatinib. In this study, a 3D-QSAR model was built for SYK based on known inhibitor IC50 values. The best pharmacophore model was then used as a 3D query to screen a drug-like database to retrieve hits with novel chemical scaffolds. The obtained compounds were subjected to binding affinity prediction using the molecular docking approach, and the results were subsequently validated using molecular dynamics (MD) simulations. The simulated compounds were ranked according to binding free energy (DG), and the binding affinity was compared with fostamatinib. The binding mode analysis of selected compounds revealed that the hit compounds form hydrogen bond interactions with hinge region residue Ala451, glycine-rich loop residue Lys375, Ser379, and DFG motif Asp512. Identified hits were also observed to form a desirable interaction with Pro455 and Asn457, the rare feature observed in SYK inhibitors. Therefore, we argue that identified hit compounds ZINC98363745, ZINC98365358, ZINC98364133, and ZINC08789982 may help in drug design against SYK. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
48. In Silico Study Identified Methotrexate Analog as Potential Inhibitor of Drug Resistant Human Dihydrofolate Reductase for Cancer Therapeutics
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Shraddha Parate, Gihwan Lee, Noman Bin Abid, Sanghwa Yoon, Rabia Mukhtar Rana, Yumi Kim, Donghwan Kim, Shailima Rampogu, Amir Zeb, and Keun Woo Lee
- Subjects
Pharmaceutical Science ,Molecular Dynamics Simulation ,Ligands ,Article ,methotrexate ,Analytical Chemistry ,lcsh:QD241-441 ,03 medical and health sciences ,0302 clinical medicine ,lcsh:Organic chemistry ,In vivo ,Catalytic Domain ,Neoplasms ,Drug Discovery ,Dihydrofolate reductase ,Humans ,Physical and Theoretical Chemistry ,030304 developmental biology ,0303 health sciences ,Virtual screening ,Binding Sites ,biology ,Chemistry ,Organic Chemistry ,Wild type ,molecular dynamics simulation ,Active site ,Hydrogen Bonding ,Methotrexate analog ,molecular docking ,virtual screening ,Molecular Docking Simulation ,Tetrahydrofolate Dehydrogenase ,ROC Curve ,Biochemistry ,Drug Resistance, Neoplasm ,Chemistry (miscellaneous) ,Area Under Curve ,030220 oncology & carcinogenesis ,Drug resistance ,Mutagenesis, Site-Directed ,biology.protein ,Lipinski's rule of five ,pharmacophore modeling ,Folic Acid Antagonists ,Thermodynamics ,Molecular Medicine ,Pharmacophore ,human dihydrofolate reductase - Abstract
Drug resistance is a core issue in cancer chemotherapy. A known folate antagonist, methotrexate (MTX) inhibits human dihydrofolate reductase (hDHFR), the enzyme responsible for the catalysis of 7,8-dihydrofolate reduction to 5,6,7,8-tetrahydrofolate, in biosynthesis and cell proliferation. Structural change in the DHFR enzyme is a significant cause of resistance and the subsequent loss of MTX. In the current study, wild type hDHFR and double mutant (engineered variant) F31R/Q35E (PDB ID: 3EIG) were subject to computational study. Structure-based pharmacophore modeling was carried out for wild type (WT) and mutant (MT) (variant F31R/Q35E) hDHFR structures by generating ten models for each. Two pharmacophore models, WT-pharma and MT-pharma, were selected for further computations, and showed excellent ROC curve quality. Additionally, the selected pharmacophore models were validated by the Guner-Henry decoy test method, which yielded high goodness of fit for WT-hDHFR and MT-hDHFR. Using a SMILES string of MTX in ZINC15 with the selections of &lsquo, clean&rsquo, in vitro and in vivo options, 32 MTX-analogs were obtained. Eight analogs were filtered out due to their drug-like properties by applying absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment tests and Lipinski&rsquo, s Rule of five. WT-pharma and MT-pharma were further employed as a 3D query in virtual screening with drug-like MTX analogs. Subsequently, seven screening hits along with a reference compound (MTX) were subjected to molecular docking in the active site of WT- and MT-hDHFR. Through a clustering analysis and examination of protein-ligand interactions, one compound was found with a ChemPLP fitness score greater than that of MTX (reference compound). Finally, a simulation of molecular dynamics (MD) identified an MTX analog which exhibited strong affinity for WT- and MT-hDHFR, with stable RMSD, hydrogen bonds (H-bonds) in the binding site and the lowest MM/PBSA binding free energy. In conclusion, we report on an MTX analog which is capable of inhibiting hDHFR in wild type form, as well as in cases where the enzyme acquires resistance to drugs during chemotherapy treatment.
- Published
- 2020
- Full Text
- View/download PDF
49. A Computational Approach with Biological Evaluation: Combinatorial Treatment of Curcumin and Exemestane Synergistically Regulates DDX3 Expression in Cancer Cell Lines
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Yumi Kim, Ayoung Baek, Shailima Rampogu, Gihwan Lee, Keun Woo Lee, Gon Sup Kim, Minky Son, Ju Hyun Kim, Seong Min Kim, and Chanin Park
- Subjects
0301 basic medicine ,Models, Molecular ,Curcumin ,Cell Survival ,combinatorial treatment ,lcsh:QR1-502 ,Protein Data Bank (RCSB PDB) ,Down-Regulation ,Apoptosis ,Biochemistry ,lcsh:Microbiology ,Article ,HeLa ,DEAD-box RNA Helicases ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,Exemestane ,DDX3 ,Tumor Cells, Cultured ,cancers ,natural compounds ,Humans ,Enzyme Inhibitors ,Molecular Biology ,Cell Proliferation ,biology ,Dose-Response Relationship, Drug ,Molecular Structure ,biology.organism_classification ,Small molecule ,In vitro ,Cell biology ,Androstadienes ,030104 developmental biology ,chemistry ,Cell culture ,030220 oncology & carcinogenesis ,Pharmacophore - Abstract
DDX3 belongs to RNA helicase family that demonstrates oncogenic properties and has gained wider attention due to its role in cancer progression, proliferation and transformation. Mounting reports have evidenced the role of DDX3 in cancers making it a promising target to abrogate DDX3 triggered cancers. Dual pharmacophore models were generated and were subsequently validated. They were used as 3D queries to screen the InterBioScreen database, resulting in the selection of curcumin that was escalated to molecular dynamics simulation studies. In vitro anti-cancer analysis was conducted on three cell lines such as MCF-7, MDA-MB-231 and HeLa, which were evaluated along with exemestane. Curcumin was docked into the active site of the protein target (PDB code 2I4I) to estimate the binding affinity. The compound has interacted with two key residues and has displayed stable molecular dynamics simulation results. In vitro analysis has demonstrated that both the candidate compounds have reduced the expression of DDX3 in three cell lines. However, upon combinatorial treatment of curcumin (10 and 20 &mu, M) and exemestane (50 &mu, M) a synergism was exhibited, strikingly downregulating the DDX3 expression and has enhanced apoptosis in three cell lines. The obtained results illuminate the use of curcumin as an alternative DDX3 inhibitor and can serve as a chemical scaffold to design new small molecules.
- Published
- 2020
50. Biochemical and Structural Insights Concerning Triclosan Resistance in a Novel YX7K Type Enoyl-Acyl Carrier Protein Reductase from Soil Metagenome
- Author
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Keun Woo Lee, Kihyuck Choi, Amir Zeb, Raees Khan, Gihwan Lee, and Seon-Woo Lee
- Subjects
0301 basic medicine ,Enoyl-acyl carrier protein reductase ,030106 microbiology ,lcsh:Medicine ,Dehydrogenase ,Reductase ,medicine.disease_cause ,Article ,03 medical and health sciences ,chemistry.chemical_compound ,Biosynthesis ,Bacterial Proteins ,Valine ,Drug Resistance, Bacterial ,medicine ,lcsh:Science ,Phylogeny ,Multidisciplinary ,Bacteria ,Microbiota ,Mutagenesis ,lcsh:R ,Pathogenic bacteria ,Environmental monitoring ,Enoyl-(Acyl-Carrier-Protein) Reductase (NADH) ,Triclosan ,030104 developmental biology ,Soil microbiology ,Biochemistry ,chemistry ,Metagenome ,lcsh:Q ,Intracellular - Abstract
Enoyl-acyl carrier protein reductase (ENR) catalyzes the last reduction step in the bacterial type II fatty acid biosynthesis cycle. ENRs include FabI, FabL, FabL2, FabK, and FabV. Previously, we reported a unique triclosan (TCL) resistant ENR homolog that was predominant in obligate intracellular pathogenic bacteria and Apicomplexa. Herein, we report the biochemical and structural basis of TCL resistance in this novel ENR. The purified protein revealed NADH-dependent ENR activity and shared similarity to prototypic FabI. Thus, this metagenome-derived ENR was designated FabI2. Unlike other prototypic bacterial ENRs with the YX6K type catalytic domain, FabI2 possessed a unique YX7K type catalytic domain. Computational modeling followed by site-directed mutagenesis revealed that mild resistance (20 µg/ml of minimum inhibitory concentration) of FabI2 to TCL was confined to the relatively less bulky side chain of A128. Substitution of A128 in FabI2 with bulky valine (V128) elevated TCL resistance. Phylogenetic analysis further suggested that the novel FabI2 and prototypical FabI evolved from a common short-chain dehydrogenase reductase family. To our best knowledge, FabI2 is the only known ENR shared by intracellular pathogenic prokaryotes, intracellular pathogenic lower eukaryotes, and a few higher eukaryotes. This suggests that the ENRs of prokaryotes and eukaryotes diverged from a common ancestral ENR of FabI2.
- Published
- 2019
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