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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.

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.

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.

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

ACK1, an intracellular non-receptor tyrosine kinase when abnormally activated and amplified causes numerous sorts of human cancers, therefore, act as a major target of cancer drug development. Currently, there are very small numbers of inhibitors reported for ACK1 inhibition and none of them are in clinical trials. In this study, to identify potential ACK1 inhibitors, a small dataset was prepared from already known inhibitors as a training set for ligand-based pharmacophore model generation using the Hip-Hop algorithm available in the Discovery Studio. Selected pharmacophore hypothesis, Hypo1 displayed the highest rank and consists of five features including two hydrogen bond acceptors (HBA), two-ring aromatic (RA) and one hydrophobic (HYP). Hypo1 was further validated by Receiver Operating Characteristic (ROC) curve and Guner-Henry (GH) approach which give an ROC value of 0.92 and highest GH score of 0.78. Drug-like database was generated from ZINC, ANX, NCI and Princeton database using Lipinski's rule of five and ADMET descriptors. Validated Hypo1 was used for searching new potential hit compounds from the generated drug-like database. From molecular docking analysis, ten potential inhibitor compounds were selected on the basis of Goldscore >67.72, the score of reference inhibitor Dasatinib. Furthermore, molecular dynamics simulation study was performed to study the stability of docking conformations. Subsequently, molecular dynamics simulation analyses revealed that the Hit1 and Hit2 compounds have desirable molecular interaction with key residues Thr205 and Ala208 in the hinge region of ACK1 with better binding affinity. Finally, various pharmacokinetic properties over the Hit1 and Hit2 compounds were analyzed using pkCSM tool and it was found that our hit compounds have shown comparable results with reference. Therefore, we propose the Hit1 and Hit2 compounds may be crucial against ACK1 as potential anticancer agents subjected to experimental validation.

The mitochondrial calcium uniporter (MCU) plays essential roles in mitochondrial calcium homeostasis and regulates cellular functions, such as energy synthesis, cell growth, and development. Thus, MCU activity is tightly controlled by its regulators as well as post-translational modification, including phosphorylation by protein kinases such as proline-rich tyrosine kinase 2 (Pyk2) and AMP-activated protein kinase (AMPK). In our in vitro kinase assay, the MCU N-terminal domain (NTD) was phosphorylated by protein kinase C isoforms (PKCβII, PKCδ, and PKCε) localized in the mitochondrial matrix. In addition, we found the conserved S92 was phosphorylated by the PKC isoforms. To reveal the structural effect of MCU S92 phosphorylation (S92p), we determined crystal structures of the MCU NTD of S92E and D119A mutants and analysed the molecular dynamics simulation of WT and S92p. We observed conformational changes of the conserved loop2-loop4 (L2-L4 loops) in MCU NTDS92E, NTDD119A, and NTDS92p due to the breakage of the S92-D119 hydrogen bond. The results suggest that the phosphorylation of S92 induces conformational changes as well as enhancements of the negative charges at the L2-L4 loops, which may affect the dimerization of two MCU-EMRE tetramers.

Breast cancer is one of the common causes of death noticed in women globally. In order to find effective therapeutics, the current investigation has focussed on identifying candidate compounds for EGFR and HER2. Accordingly, the pharmacophore modelling approaches were adapted to identify two prospective compounds and were docked against the target 3RCD that is complexed with TAK-285 a known dual inhibitor. Focussing on the target 3RCD, our results have showed that the compounds have demonstrated a good binding affinity towards the target occupying the binding pocket. They have established key residue interactions with stable molecular dynamics simulation results. The Hit compounds have demonstrated a potential to penetrate the blood brain barrier thereby enriching their therapeutics towards breast cancer brain metastasis. Taken together, our findings propose two candidate compounds as EGFR/HER2 inhibitors that might serve as novel chemical spaces for designing and developing new inhibitors.

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.

The transgenic rice cultivar of Oryza sativa spp. japonica cv. Hwa-Young, C1/R-S transgenic rice (C1/R-S rice), is a flavonoid-rich cultivar of rice. The grains of C1/R-S rice were extracted with aqueous MeOH, and the concentrated extract was partitioned with EtOAc, n-BuOH, and H2O, successively. Repeated silica gel, octadecyl silica gel (ODS), and Sephadex LH-20 column chromatographies for the EtOAc and n-BuOH fractions afforded four new flavonoids (compounds 2, 3, 7, and 8) along with four known flavonoids: (+)-3'-O-methyltaxifolin (1), brassicin (4), isorhamnetin-4'-O-β-D-glucosyranoside (5), and 3'-O-methyltaxifolin-5-O-β-D-glucopyranoside (6). The new flavonoids were identified as 3'-O-methyltaxifolin-7-O-β-D-glucopyranoside (2), 3'-O-methyltaxifolin-4'-O-β-D-glucopyranoside (3), isorhamnetin-7-O-β-D-cellobioside (brassicin-4″-O-β-D-glucopyranoside) (7), and brassicin-4'-O-β-D-glucosyranoside (8) from the result of spectroscopic data including nuclear magnetic resonance spectrometry (NMR), mass spectrometry (MS), and infrared spectroscopy (IR). Also, quantitative analysis of major flavonoids (compounds 2, 3, and 8) in C1/R-S rice, O. sativa spp. japonica cv. Hwa-Young (HY), and a hybrid of two cultivar (C1/R-S rice/HY) extracts was performed using HPLC experiment. The isolated flavonoids were evaluated for their radical-scavenging effect on DPPH and ABTS radicals.