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A series of 13 new 3-substituted 5-(5-nitro-2-furyl)-1,2,4-oxadiazoles was synthesized from different aminonitriles. All compounds were screened in the disc diffusion test at a 100 μg/mL concentration to determine the bacterial growth inhibition zone presence and diameter, and then the minimum inhibitory concentrations (MICs) were determined for the most active compounds by serial dilution. The compounds showed antibacterial activity against ESKAPE bacteria, predominantly suppressing the growth of 5 species out of the panel. Some compounds had similar or lower MICs against ESKAPE pathogens compared to ciprofloxacin, nitrofurantoin, and furazidin. In particular, 3-azetidin-3-yl-5-(5-nitro-2-furyl)-1,2,4-oxadiazole (2h) inhibited S. aureus at a concentration lower than all comparators. Compound 2e (5-(5-nitro-2-furyl)-3-[4-(pyrrolidin-3-yloxy)phenyl]-1,2,4-oxadiazole) was active against Gram-positive ESKAPE pathogens as well as M. tuberculosis. Differences in the molecular periphery led to high selectivity for the compounds. The induced-fit docking (IFD) modeling technique was applied to in silico research. Molecular docking results indicated the targeting of compounds against various nitrofuran-associated biological targets. [ABSTRACT FROM AUTHOR]

Protein–ligand docking plays a significant role in structure-based drug discovery. This methodology aims to estimate the binding mode and binding free energy between the drug-targeted protein and candidate chemical compounds, utilizing protein tertiary structure information. Reformulation of this docking as a quadratic unconstrained binary optimization (QUBO) problem to obtain solutions via quantum annealing has been attempted. However, previous studies did not consider the internal degrees of freedom of the compound that is mandatory and essential. In this study, we formulated fragment-based protein–ligand flexible docking, considering the internal degrees of freedom of the compound by focusing on fragments (rigid chemical substructures of compounds) as a QUBO problem. We introduced four factors essential for fragment–based docking in the Hamiltonian: (1) interaction energy between the target protein and each fragment, (2) clashes between fragments, (3) covalent bonds between fragments, and (4) the constraint that each fragment of the compound is selected for a single placement. We also implemented a proof-of-concept system and conducted redocking for the protein–compound complex structure of Aldose reductase (a drug target protein) using SQBM+, which is a simulated quantum annealer. The predicted binding pose reconstructed from the best solution was near-native (RMSD = 1.26 Å), which can be further improved (RMSD = 0.27 Å) using conventional energy minimization. The results indicate the validity of our QUBO problem formulation. [ABSTRACT FROM AUTHOR]

A series of eight 5-nitrofuran-tagged oxazolyl tetrahydropyrazolopyridines (THPPs) has been prepared in six stages with excellent regioselectivity. The testing of these compounds against pathogens of the ESKAPE panel showed a good activity of lead compound 1-(2-methoxyethyl)-5-(5-nitro-2-furoyl)-3-(1,3-oxazol-5-yl)-4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c] pyridine (13g), which is superior to nitrofurantoin. These results confirmed the benefit of combining a THPP scaffold with a nitrofuran warhead. Certain structure–activity relationships were established in the course of this study which were rationalized by the induced-fit docking experiments in silico. [ABSTRACT FROM AUTHOR]

Protein–ligand docking plays a significant role in structure-based drug discovery. This methodology aims to estimate the binding mode and binding free energy between the drug-targeted protein and candidate chemical compounds, utilizing protein tertiary structure information. Reformulation of this docking as a quadratic unconstrained binary optimization (QUBO) problem to obtain solutions via quantum annealing has been attempted. However, previous studies did not consider the internal degrees of freedom of the compound that is mandatory and essential. In this study, we formulated fragment-based protein–ligand flexible docking, considering the internal degrees of freedom of the compound by focusing on fragments (rigid chemical substructures of compounds) as a QUBO problem. We introduced four factors essential for fragment–based docking in the Hamiltonian: (1) interaction energy between the target protein and each fragment, (2) clashes between fragments, (3) covalent bonds between fragments, and (4) the constraint that each fragment of the compound is selected for a single placement. We also implemented a proof-of-concept system and conducted redocking for the protein–compound complex structure of Aldose reductase (a drug target protein) using SQBM+, which is a simulated quantum annealer. The predicted binding pose reconstructed from the best solution was near-native (RMSD = 1.26 Å), which can be further improved (RMSD = 0.27 Å) using conventional energy minimization. The results indicate the validity of our QUBO problem formulation.

A series of eight 5-nitrofuran-tagged oxazolyl tetrahydropyrazolopyridines (THPPs) has been prepared in six stages with excellent regioselectivity. The testing of these compounds against pathogens of the ESKAPE panel showed a good activity of lead compound 1-(2-methoxyethyl)-5-(5-nitro-2-furoyl)-3-(1,3-oxazol-5-yl)-4,5,6,7-tetrahydro-1H-pyrazolo[4,3-c] pyridine (13g), which is superior to nitrofurantoin. These results confirmed the benefit of combining a THPP scaffold with a nitrofuran warhead. Certain structure–activity relationships were established in the course of this study which were rationalized by the induced-fit docking experiments in silico.

A chemically diverse set of 13 5-nitrofuran-tagged heterocyclic compounds has been prepared via the Groebke–Blackburn–Bienaymé multicomponent reaction. The testing of these compounds against the so-called ESKAPE panel of pathogens identified an apparent lead compound—N-cyclohexyl-2-(5-nitrofuran-2-yl)imidazo[1,2-a]pyridine-3-amine (4a)—which showed an excellent profile against Enterobacter cloacae, Staphylococcus aureus, Klebsiella pneumoniae, and Enterococcus faecalis (MIC 0.25, 0.06, 0.25 and 0.25 µg/mL, respectively). Its antibacterial profile and practically convenient synthesis warrant further pre-clinical development. Certain structure-activity relationships were established in the course of this study which were rationalized by the flexible docking experiments in silico. The assessment of antitubercular potential of the compounds synthesized against drug sensitive H37v strain of Mycobacterium tuberculosis revealed little potential of the imidazo-fused products of the Groebke–Blackburn–Bienaymé multicomponent reaction as chemotherapeutic agents against this pathogen. [ABSTRACT FROM AUTHOR]

A group of new thiazolo[3,2‐b][1,2,4]triazol‐6(5H)‐one fenamate‐like derivatives designed by using hybrid strategy in order to explore analgesic/anti‐inflammatory activity of the hybrid structures. Some of the synthesized analogs showed comparable activities with mefenamic acid in abdominal constriction test and carrageenan induced rat paw edema test. 5‐(4‐nitrobenzylidene)‐2‐(2‐(2‐chlorophenoxy)phenyl)thiazolo[3,2‐b][1,2,4]triazol‐6(5H)‐one (8 e) and 5‐(3,5‐di‐tert‐butyl‐4‐hydroxybenzylidene)‐2‐(2‐(2‐chlorophenoxy)phenyl)thiazolo[3,2‐b][1,2,4]triazol‐6(5H)‐one (8 k) were determined as the most active agents with 53.1 and 49.3 percent of inhibition after 4 hrs of ip administration respectively. Flexible docking investigation indicated that the designed molecules interacted with cyclooxygenase 1 and 2 (COX‐1 and COX‐2) active sites. Moreover, the results suggest that thiazolo[3,2b][1,2,4]triazol‐6(5H)‐one moiety has the same effect as mefenamic acid COOH group over COX‐1,2 with a significant low or no ulcerogenic activity. Furthermore, the energetically favorable conformer Z, revealed as the active structural conformation due to the less steric hindrance. Based on the predicted ADME properties of high potent anti‐inflammatory agents, it is proposed that the applied modifications promote the rational drug design of novel analgesic and anti‐inflammatory candidates. [ABSTRACT FROM AUTHOR]

Considering that acetylcholinesterase (AChE) inhibition is the most important mode of action expected of a potential drug used for the treatment of symptoms of Alzheimer's disease (AD), our previous pilot study of 4-aminoquinolines as potential human cholinesterase inhibitors was extended to twenty-two new structurally distinct 4-aminoquinolines bearing an adamantane moiety. Inhibition studies revealed that all of the compounds were very potent inhibitors of AChE and butyrylcholinesterase (BChE), with inhibition constants (Ki) ranging between 0.075 and 25 µM. The tested compounds exhibited a modest selectivity between the two cholinesterases; the most selective for BChE was compound 14, which displayed a 10 times higher preference, while compound 19 was a 5.8 times more potent inhibitor of AChE. Most of the compounds were estimated to be able to cross the blood–brain barrier (BBB) by passive transport. Evaluation of druglikeness singled out fourteen compounds with possible oral route of administration. The tested compounds displayed modest but generally higher antioxidant activity than the structurally similar AD drug tacrine. Compound 19 showed the highest reducing power, comparable to those of standard antioxidants. Considering their simple structure, high inhibition of AChE and BChE, and ability to cross the BBB, 4-aminoquinoline-based adamantanes show promise as structural scaffolds for further design of novel central nervous system drugs. Among them, two compounds stand out: compound 5 as the most potent inhibitor of both cholinesterases with a Ki constant in low nano molar range and the potential to cross the BBB, and compound 8, which met all our requirements, including high cholinesterase inhibition, good oral bioavailability, and antioxidative effect. The QSAR model revealed that AChE and BChE inhibition was mainly influenced by the ring and topological descriptors MCD, Nnum, RP, and RSIpw3, which defined the shape, conformational flexibility, and surface properties of the molecules. [ABSTRACT FROM AUTHOR]

Lipases from Pseudomonas species are particularly useful due to their broader biocatalytic applications and temperature activity. In this study, we amplified the gene encoding wild-type cold-active lipase from the genome of psychrotrophic bacterium isolated from the Himalayan glacier. The isolated CRBC14 strain was identified as Pseudomonas sp. based on the 16S rRNA gene sequence. Lipase activity was determined by observing the hydrolysis zone on nutrient agar containing tributyrin (1%, v/v). The sequence analysis of cold-active lipase revealed a protein of 611 amino acids with a calculated molecular mass of 63.71 kDa. The three-dimensional structure of this lipase was generated through template-supported modeling. Distinct techniques stamped the model quality, following which the binding free energies of tributyrin and oleic acid in the complex state with this enzymatic protein were predicted through molecular mechanics generalized born surface area (MMGBSA). A relative comparison of binding free energy values of these substrates indicated tributyrin's comparatively higher binding propensity towards the lipase. Using molecular docking, we evaluated the binding activity of cold-active lipase against tributyrin and oleic acid. Our docking analysis revealed that the lipase had a higher affinity for tributyrin than oleic acid, as evidenced by our measurement of the hydrolysis zone on two media plates. This study will help to understand the bacterial diversity of unexplored Himalayan glaciers and the possible application of their cold-adapted enzymes. [ABSTRACT FROM AUTHOR]

RNA molecules play critical roles in cellular functions at the level of gene expression and regulation. The intricate 3D structures and the functional roles of RNAs make RNA molecules ideal targets for therapeutic drugs. The rational design of RNA-targeted drug requires accurate modeling of RNA-ligand interactions. Recently a new computational tool, RLDOCK, was developed to predict ligand binding sites and binding poses. Using an iterative multiscale sampling and search algorithm and a energy-based evaluation of ligand poses, the method enables efficient and accurate predictions for RNA-ligand interactions. Here we present a detailed illustration of the computational procedure for the practical implementation of the RLDOCK method. Using Flavin mononucleotide (FMN) docking to F. nucleatum FMN riboswitch as an example, we illustrate the computational protocol for RLDOCK-based prediction of RNA- ligand interactions. The RLDOCK software is freely accessible at http://https://github.com/Vfold-RNA/RLDOCK. [ABSTRACT FROM AUTHOR]

Elastic network model simulations were performed to investigate the conformational changes of MDM2 protein induced by its native substrate p53 and two small molecule inhibitor (NVP-CGM097 and HDM 201) bindings. Residues Phe 19, Trp 23, Leu 26 were observed to reside in the minima of slowest modes of p53, pointing to the accepted three finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct conserved regions are identified in MDM2. Regions I (residues 50–77) and III (residues 90–105) correspond to the binding interface of MDM2 including α helix-2 (α 2), Loop-2 (L2) and α helix-4 (α 4) domains which are stabilized during complex formation. Region II (residues 77–90) is a highly flexible region in both unbound and bound forms exhibiting high amplitude collective motion. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 pointing to induced-fit mechanism. Flexible docking using AutoDock Vina is performed to account for the flexible nature of the receptor and to elucidate the essential interactions in the binding cleft. α 4 domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states. Inhibitors studied in this work (NVP-CGM097 and HDM201), which are recently undergoing clinical trials, succeed in mimicking p53 behavior which would shed light on the rational design of novel anticancer drugs. Elastic network model simulations were performed to investigate the conformational changes of MDM2 protein induced by its native substrate p53 and two small molecule inhibitor (NVP-CGM097 and HDM 201) bindings. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 pointing to induced-fit mechanism. Flexible docking simulations indicated that helix-4 controls the size of the cleft by keeping it narrow in unbound MDM2; and open in the bound states and the two inhibitors studied in this work, which are currently undergoing clinical trials, succeed in mimicking p53 behaviour in the slowest modes of motion. [ABSTRACT FROM AUTHOR]

The conformational diversity of isomers of natural and synthetic steroids was analyzed on the basis of semi-empirical quantum chemical calculations and docking. The binding of various isomers and analogues of testosterone to the androgen receptor was modeled. Special attention was paid to the role of structural and thermodynamic factors in determining the preferred isomers of testosterone that might determine the best functioning of its complex with the androgen receptor. [ABSTRACT FROM AUTHOR]

Recent advances in high-resolution structural studies of protein amyloids have revealed parallel in-register cross-β-sheets with periodic arrays of closely spaced identical residues. What do these structures tell us about the mechanisms of action of common amyloid-promoting factors, such as heparan sulfate (HS), nucleic acids, polyphosphates, anionic phospholipids, and acidic pH? [ABSTRACT FROM AUTHOR]

The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein–peptide complex structures and model scoring. We evaluated the proposed protocol on the set of seven different GPCR–peptide complexes (including one containing a cyclic peptide), for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface root-mean-square-deviation measure. [ABSTRACT FROM AUTHOR]

CC chemokine receptor 2 (CCR2) antagonists that disrupt CCR2/MCP‐1 interaction are expected to treat a variety of inflammatory and autoimmune diseases. The lack of CCR2 crystal structure limits the application of structure‐based drug design (SBDD) to this target. Although a few three‐dimensional theoretical models have been reported, their accuracy remains to be improved in terms of templates and modeling approaches. In this study, we developed a unique ligand‐steered strategy for CCR2 homology modeling. It starts with an initial model based on the X‐ray structure of the closest homolog so far, that is, CXCR4. Then, it uses Elastic Network Normal Mode Analysis (EN‐NMA) and flexible docking (FD) by AutoDock Vina software to generate ligand‐induced fit models. It selects optimal model(s) as well as scoring function(s) via extensive evaluation of model performance based on a unique benchmarking set constructed by our in‐house tool, that is, MUBD‐DecoyMaker. The model of 81_04 presents the optimal enrichment when combined with the scoring function of PMF04, and the proposed binding mode between CCR2 and Teijin lead by this model complies with the reported mutagenesis data. To highlight the advantage of our strategy, we compared it with the only reported ligand‐steered strategy for CCR2 homology modeling, that is, Discovery Studio/Ligand Minimization. Lastly, we performed prospective virtual screening based on 81_04 and CCR2 antagonist bioassay. The identification of two hit compounds, that is, E859‐1281 and MolPort‐007‐767‐945, validated the efficacy of our model and the ligand‐steered strategy. [ABSTRACT FROM AUTHOR]

Abstract Background Ebola still remains as one of the most problematic infectious diseases in Africa with a high rate of mortality. Although this disease has been known for an almost half-century, there are no vaccines and drugs available in the market to treat Ebola. Zaire ebolavirus (EBOV), a single-stranded RNA virus which belongs to Filoviridae family and Mononegavirales order, is one of the virus causing Ebola. As one of seven proteins that EBOV encodes, Ebola virus nucleoprotein (EBOV NP) plays an imperative role in EBOV proliferation cycle. Therefore, the development of a new Ebola treatment can be targeted towards EBOV NP. Results In this work, we screened about 190,084 natural product compounds from ZINC15 database through in silico virtual screening and flexible docking simulation. Furthermore, the bioavailability and toxicity prediction have been conducted as well. Two best ligands according to the simulation and prediction tests were progressed into the molecular dynamics simulation. Conclusion In the end, we found that our proposed ligands, namely α-lipomycin (ZINC56874155) and 3-(((S)-1-amino-1,2,3,4-tetrahydroisoquinolin-5-yl)methyl)-5-((5-((5R,7S)-5,7-dihydroxy-3-oxodecyl)-2-hydroxyphenoxy) methyl)pyrrolo[3,4-b]pyrrol-5-ium (ZINC85628951), showed the promising results to be developed as a lead compounds for treating Ebola. Therefore, an experimental study is required to validate their inhibition activities against EBOV NP.

The Malaria Eradication Research Agenda (malERA) Consultative Group on Vector Control outline the research needed to ensure vector control at every stage of malaria eradication.Different challenges are presented by the variety of malaria transmission environments present in the world today. In each setting, improved control for reduction of morbidity is a necessary first step towards the long-range goal of malaria eradication and a priority for regions where the disease burden is high. For many geographic areas where transmission rates are low to moderate, sustained and well-managed application of currently available tools may be sufficient to achieve local elimination. The research needs for these areas will be to sustain and perhaps improve the effectiveness of currently available tools. For other low-to-moderate transmission regions, notably areas where the vectors exhibit behaviours such as outdoor feeding and resting that are not well targeted by current strategies, new interventions that target predictable features of the biology/ecologies of the local vectors will be required. To achieve elimination in areas where high levels of transmission are sustained by very efficient vector species, radically new interventions that significantly reduce the vectorial capacity of wild populations will be needed. Ideally, such interventions should be implemented with a one-time application with a long-lasting impact, such as genetic modification of the vectorial capacity of the wild vector population.

Abstract Background Many protein–protein interactions are mediated by a short linear motif. Usually, amino acid sequences of those motifs are known or can be predicted. It is much harder to experimentally characterize or predict their structure in the bound form. In this work, we test a possibility of using flexible docking of a short linear motif to predict the interaction interface of the EphB4-EphrinB2 complex (a system extensively studied for its significance in tumor progression). Methods In the modeling, we only use knowledge about the motif sequence and experimental structures of EphB4-EphrinB2 complex partners. The proposed protocol enables efficient modeling of significant conformational changes in the short linear motif fragment during molecular docking simulation. For the docking simulations, we use the CABS-dock method for docking fully flexible peptides to flexible protein receptors (available as a server at http://biocomp.chem.uw.edu.pl/CABSdock/ ). Based on the docking result, the protein–protein complex is reconstructed and refined. Results Using this novel protocol, we obtained an accurate EphB4-EphrinB2 interaction model. Conclusions The results show that the CABS-dock method may be useful as the primary docking tool in specific protein–protein docking cases similar to EphB4-EphrinB2 complex—that is, where a short linear motif fragment can be identified.

Abstract Background The characterization of protein–peptide interactions is a challenge for computational molecular docking. Protein–peptide docking tools face at least two major difficulties: (1) efficient sampling of large-scale conformational changes induced by binding and (2) selection of the best models from a large set of predicted structures. In this paper, we merge an efficient sampling technique with external information about side-chain contacts to sample and select the best possible models. Methods In this paper we test a new protocol that uses information about side-chain contacts in CABS-dock protein–peptide docking. As shown in our recent studies, CABS-dock enables efficient modeling of large-scale conformational changes without knowledge about the binding site. However, the resulting set of binding sites and poses is in many cases highly diverse and difficult to score. Results As we demonstrate here, information about a single side-chain contact can significantly improve the prediction accuracy. Importantly, the imposed constraints for side-chain contacts are quite soft. Therefore, the developed protocol does not require precise contact information and ensures large-scale peptide flexibility in the broad contact area. Conclusions The demonstrated protocol provides the extension of the CABS-dock method that can be practically used in the structure prediction of protein–peptide complexes guided by the knowledge of the binding interface.

CABS-dock is a computational method for protein–peptide molecular docking that does not require predefinition of the binding site. The peptide is treated as fully flexible, while the protein backbone undergoes small fluctuations and, optionally, large-scale rearrangements. Here, we present a specific CABS-dock protocol that enhances the docking procedure using fragmentary information about protein–peptide contacts. The contact information is used to narrow down the search for the binding peptide pose to the proximity of the binding site. We used information on a single-chosen and randomly chosen native protein–peptide contact to validate the protocol on the peptiDB benchmark. The contact information significantly improved CABS-dock performance. The protocol has been made available as a new feature of the CABS-dock web server (at http://biocomp.chem.uw.edu.pl/CABSdock/). Short abstract CABS-dock is a tool for flexible docking of peptides to proteins. In this article, we present a protocol for CABS-dock docking driven by information about protein–peptide contact(s). Using information on individual protein–peptide contacts allows to improve the accuracy of CABS-dock docking. [ABSTRACT FROM AUTHOR]

Advances in electron microscopy have provided unprecedented access to the structural characterization of large, flexible and heterogeneous complexes. Until recently, cryo-electron microscopy (cryo-EM) has been applied to understand molecular organization in either highly purified, isolated biomolecules or in situ. An emerging field is developing, bridging the gap between the two approaches, and focuses on studying molecular organization in native cell extracts. This field has demonstrated its potential by resolving the structure of fungal fatty acid synthase (FAS) at 4.7 Å [Fourier shell correlation (FSC) = 0.143]; FAS was not only less than 50% enriched, but also retained higher-order binders, previously unknown. Although controversial in the sense that the lysis step might introduce artifacts, cell extracts preserve aspects of cellular function. In addition, cell extracts are accessible, besides cryo-EM, to modern proteomic methods, chemical cross-linking, network biology and biophysical modeling. We expect that automation in imaging cell extracts, along with the integration of molecular/cell biology approaches, will provide remarkable achievements in the study of closer-to-life biomolecular states of pronounced biotechnological and medical importance. Such steps will, eventually, bring us a step closer to the biophysical description of cellular processes in an integrative, holistic approach. [ABSTRACT FROM AUTHOR]

P‐glycoprotein (P‐gp) is a multidrug resistance (MDR) transporter with unknown structural details. This macromolecule is normally responsible for extruding xenobiotics from normal cells. Overexpression of P‐gp in tumor cells is a major obstacle in cancer chemotherapy. In this study, human 3D model of P‐gp was built by homology modeling based on mouse P‐gp crystallographic structure and stabilized through 1 ns molecular dynamics (MD) simulation. Stabilized human P‐gp structure was used for flexible docking of 80 drugs into the putative active site of P‐gp. Accordingly, digoxin, itraconazole, risperidone, ketoconazole, prazosin, verapamil, cyclosporine A, and ranitidine were selected for further in vitro assay. Subsequently, cell‐based P‐gp inhibition assay was performed on Caco‐2 cells while 99mTc‐methoxyisobutylisonitrile (MIBI) was used as a P‐gp efflux substrate for calculating IC50 values. Results of the 99mTc‐MIBI uptake in drug‐treated Caco‐2 cells were in agreement with the previously reported activities. This study for the first time described the relation between molecular dynamics and flexible docking with cellular experiments using 99mTc‐MIBI radiotracer for evaluation of potencies of P‐gp inhibitors. Finally, results showed that our radiotracer–cell‐based assay is an accurate and fast screening tool for detecting P‐gp inhibitors and non‐inhibitors in drug development process. Flexible docking could substantially elucidate the main binding space of P‐glycoprotein (P‐gp) substrate or inhibitors, which is located at the tip of the P‐gp funnel‐shaped hydrophobic channel. Results showed that our 99mTc‐methoxyisobutylisonitrile radiotracer–cell‐based assay is an accurate and fast screening tool for detecting P‐gp inhibitors and non‐inhibitors in drug development process. [ABSTRACT FROM AUTHOR]

Qosay A Al-Balas,1 Mohammad A Hassan,1 Nizar A Al-Shar’i,1 Nizar M Mhaidat,2 Ammar M Almaaytah,3 Fatima M Al-Mahasneh,1 Israa H Isawi1 1Department of Medicinal Chemistry and Pharmacognosy, 2Department of Clinical Pharmacy, 3Department of Pharmaceutical Technology, Faculty of Pharmacy, Jordan University of Science and Technology, Irbid, Jordan Background: The glyoxalase system including two thiol-dependent enzymes, glyoxalase I (Glo-I) and glyoxalase II, plays an important role in a ubiquitous metabolic pathway involved in cellular detoxification of cytotoxic 2-oxoaldehydes. Tumor cells have high glycolytic activity, leading to increased cellular levels of these toxic metabolites. The increased activity of the detoxification system in cancerous cells makes this pathway a viable target for developing novel anticancer agents. In this study, we examined the potential utility of non-glutathione-based inhibitors of the Glo-I enzyme as novel anticancer drugs.Methods: Computer-aided drug design techniques, such as customized pharmacophoric features, virtual screening, and flexible docking, were used to achieve the project goals. Retrieved hits were extensively filtered and subsequently docked into the active site of the enzyme. The biological activities of retrieved hits were assessed using an in vitro assay against Glo-I.Results: Since Glo-I is a zinc metalloenzyme, a customized Zn-binding pharmacophoric feature was used to search for selective inhibitors via virtual screening of a small-molecule database. Seven hits were selected, purchased, and biologically evaluated. Three of the seven hits inhibited Glo-I activity, the most effective of which exerted 76.4% inhibition at a concentration of 25 µM.Conclusion: We successfully identified a potential Glo-I inhibitor that can serve as a lead compound for further optimization. Moreover, our in silico and experimental results were highly correlated. Hence, the docking protocol adopted in this study may be efficiently employed in future optimization steps. Keywords: cancer, glyoxalase-I, zinc-binding feature, flexible docking, Discovery Studio 3.5, ketol

Despite the development of methods for the experimental determination of protein structures, the dissonance between the number of known sequences and their solved structures is still enormous. This is particularly evident in protein-protein complexes. To fill this gap, diverse technologies have been developed to study protein-protein interactions (PPIs) in a cellular context including a range of biological and computational methods. The latter derive from techniques originally published and applied almost half a century ago and are based on interdisciplinary knowledge from the nexus of the fields of biology, chemistry, and physics about protein sequences, structures, and their folding. Protein-protein docking, the main protagonist of this chapter, is routinely treated as an integral part of protein research. Herein, we describe the basic foundations of the whole process in general terms, but step by step from protein representations through docking methods and evaluation of complexes to their final validation., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Most of the current docking procedures are focused on fine conformational adjustments of assembled complexes and fail to reproduce large-scale protein motion. In this paper, we test a new modeling approach developed to address this problem. CABS-dock is a versatile and efficient tool for modeling the structure, dynamics and interactions of protein complexes. The docking protocol employs a coarse-grained representation of proteins, a simplified model of interactions and advanced protocols for conformational sampling. CABS-dock is one of the very few tools that allow unrestrained docking with large conformational freedom of the receptor. In an example application we modeled the process of complex assembly between two proteins: Troponin C (TnC) and the N-terminal helix of Troponin I (TnI N-helix), which occurs in vivo during muscle contraction. Docking simulations illustrated how the TnC molecule undergoes significant conformational transition on complex formation, a phenomenon that can be modeled only when protein flexibility is properly accounted for. This way our procedure opens up a new possibility for studying mechanisms of protein complex assembly, which may be a supporting tool for rational drug design.

Background: Ebola still remains as one of the most problematic infectious diseases in Africa with a high rate of mortality. Although this disease has been known for an almost half-century, there are no vaccines and drugs available in the market to treat Ebola. Zaire ebolavirus (EBOV), a single-stranded RNA virus which belongs to Filoviridae family and Mononegavirales order, is one of the virus causing Ebola. As one of seven proteins that EBOV encodes, Ebola virus nucleoprotein (EBOV NP) plays an imperative role in EBOV proliferation cycle. Therefore, the development of a new Ebola treatment can be targeted towards EBOV NP. Results: In this work, we screened about 190,084 natural product compounds from ZINC15 database through in silico virtual screening and flexible docking simulation. Furthermore, the bioavailability and toxicity prediction have been conducted as well. Two best ligands according to the simulation and prediction tests were progressed into the molecular dynamics simulation. Conclusion: In the end, we found that our proposed ligands, namely α-lipomycin (ZINC56874155) and 3-(((S)-1-amino-1,2,3,4-tetrahydroisoquinolin-5-yl)methyl)-5-((5-((5R,7S)-5,7-dihydroxy-3-oxodecyl)-2-hydroxyphenoxy) methyl)pyrrolo[3,4-b]pyrrol-5-ium (ZINC85628951), showed the promising results to be developed as a lead compounds for treating Ebola. Therefore, an experimental study is required to validate their inhibition activities against EBOV NP. [ABSTRACT FROM AUTHOR]

Protein‐protein docking procedures typically perform the global scan of the proteins relative positions, followed by the local refinement of the putative matches. Because of the size of the search space, the global scan is usually implemented as rigid‐body search, using computationally inexpensive intermolecular energy approximations. An adequate refinement has to take into account structural flexibility. Since the refinement performs conformational search of the interacting proteins, it is extremely computationally challenging, given the enormous amount of the internal degrees of freedom. Different approaches limit the search space by restricting the search to the side chains, rotameric states, coarse‐grained structure representation, principal normal modes, and so on. Still, even with the approximations, the refinement presents an extreme computational challenge due to the very large number of the remaining degrees of freedom. Given the complexity of the search space, the advantage of the exhaustive search is obvious. The obstacle to such search is computational feasibility. However, the growing computational power of modern computers, especially due to the increasing utilization of Graphics Processing Unit (GPU) with large amount of specialized computing cores, extends the ranges of applicability of the brute‐force search methods. This proof‐of‐concept study demonstrates computational feasibility of an exhaustive search of side‐chain conformations in protein pocking. The procedure, implemented on the GPU architecture, was used to generate the optimal conformations in a large representative set of protein‐protein complexes. © 2018 Wiley Periodicals, Inc. Protein interactions are the key part of molecular mechanisms in living systems. Modeling of protein complexes requires refinement of the putative matches that takes into account structural flexibility. Given the complexity of the refinement protocols, the exhaustive search has clear advantage. The obstacle to such search is computational feasibility. In this proof‐of‐principle study, we address the problem of finding the optimal conformations of the side chains at protein‐protein interfaces by an exhaustive search procedure. [ABSTRACT FROM AUTHOR]

Clathrin-mediated endocytosis (CME) is a process that regulates selective internalization of important cellular cargo using clathrin-coated vesicles. Perturbation of this process has been linked to many diseases including cancer and neurodegenerative conditions. Chemical proteomics identified the marine metabolite, 2-hydroxy-5-methoxy-3-(((1S,4aS,8aS)-1,4a,5-trimethyl-1,2,3,4,4a,7,8,8a-octahydronaphthalen-2-yl)methyl)cyclohexa- 2,5-diene-1,4-dione (bolinaquinone) as a clathrin inhibitor. While being an attractive medicinal chemistry target, the lack of data about bolinaquinone’s mode of binding to the clathrin enzyme represents a major limitation for its structural optimization. We have used a molecular modeling approach to rationalize the observed activity of bolinaquinone and to predict its mode of binding with the clathrin terminal domain (CTD). The applied protocol started by global rigid-protein docking followed by flexible docking, molecular dynamics and linear interaction energy calculations. The results revealed the potential of bolinaquinone to interact with various pockets within the CTD, including the clathrin-box binding site. The results also highlight the importance of electrostatic contacts over van der Waals interactions for proper binding between bolinaquinone and its possible binding sites. This study provides a novel model that has the potential to allow rapid elaboration of bolinaquinone analogues as a new class of clathrin inhibitors.

Methicillin-resistant Staphylococcus auerus (MRSA) strains are having a major impact worldwide, and due to their resistance to all β-lactams, an urgent need for new drugs is emerging. In this regard, the shikimate pathway is considered to be one of the metabolic features of bacteria and is absent in humans. Therefore enzymes involved in this route, such as shikimate dehydrogenase (SDH), are considered excellent targets for discovery of novel antibacterial drugs. In this study, the SDH from MRSA (SaSDH) was characterized. The results showed that the enzyme is a monomer with a molecular weight of 29 kDa, an optimum temperature of 65 °C, and a maximal pH range of 9–11 for its activity. Kinetic studies revealed that SDH showed Michaelis-Menten kinetics toward both substrates (shikimate and NADP+). Initial velocity analysis suggested that SaSDH catalysis followed a sequential random mechanism. Additionally, a tridimensional model of SaSDH was obtained by homology modeling and validated. Through virtual screening three inhibitors of SaSDH were found (compounds 238, 766 and 894) and their inhibition constants and mechanism were obtained. Flexible docking studies revealed that these molecules make interactions with catalytic residues. The data of this study could serve as starting point in the search of new chemotherapeutic agents against MRSA.

The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein-ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many available experimental structures. We participated in the Stage 1 of the Challenge devoted to the docking pose predictions, with the mean RMSD value of our submission poses of 2.9 Å. Here we present a thorough analysis of our docking predictions made with AutoDock Vina and the Convex-PL rescoring potential by reproducing our submission protocol and running a series of additional molecular docking experiments. We conclude that a correct receptor structure, or more precisely, the structure of the binding pocket, plays the crucial role in the success of our docking studies. We have also noticed the important role of a local ligand geometry, which seems to be not well discussed in literature. We succeed to improve our results up to the mean RMSD value of 2.15-2.33 Å dependent on the models of the ligands, if docking these to all available homologous receptors. Overall, for docking of ligands of diverse chemical series we suggest to perform docking of each of the ligands to a set of multiple receptors that are homologous to the target. [ABSTRACT FROM AUTHOR]

Background: Many protein-protein interactions are mediated by a short linear motif. Usually, amino acid sequences of those motifs are known or can be predicted. It is much harder to experimentally characterize or predict their structure in the bound form. In this work, we test a possibility of using flexible docking of a short linear motif to predict the interaction interface of the EphB4-EphrinB2 complex (a system extensively studied for its significance in tumor progression).Methods: In the modeling, we only use knowledge about the motif sequence and experimental structures of EphB4-EphrinB2 complex partners. The proposed protocol enables efficient modeling of significant conformational changes in the short linear motif fragment during molecular docking simulation. For the docking simulations, we use the CABS-dock method for docking fully flexible peptides to flexible protein receptors (available as a server at http://biocomp.chem.uw.edu.pl/CABSdock/ ). Based on the docking result, the protein-protein complex is reconstructed and refined.Results: Using this novel protocol, we obtained an accurate EphB4-EphrinB2 interaction model.Conclusions: The results show that the CABS-dock method may be useful as the primary docking tool in specific protein-protein docking cases similar to EphB4-EphrinB2 complex-that is, where a short linear motif fragment can be identified. [ABSTRACT FROM AUTHOR]

Background: The characterization of protein-peptide interactions is a challenge for computational molecular docking. Protein-peptide docking tools face at least two major difficulties: (1) efficient sampling of large-scale conformational changes induced by binding and (2) selection of the best models from a large set of predicted structures. In this paper, we merge an efficient sampling technique with external information about side-chain contacts to sample and select the best possible models.Methods: In this paper we test a new protocol that uses information about side-chain contacts in CABS-dock protein-peptide docking. As shown in our recent studies, CABS-dock enables efficient modeling of large-scale conformational changes without knowledge about the binding site. However, the resulting set of binding sites and poses is in many cases highly diverse and difficult to score.Results: As we demonstrate here, information about a single side-chain contact can significantly improve the prediction accuracy. Importantly, the imposed constraints for side-chain contacts are quite soft. Therefore, the developed protocol does not require precise contact information and ensures large-scale peptide flexibility in the broad contact area.Conclusions: The demonstrated protocol provides the extension of the CABS-dock method that can be practically used in the structure prediction of protein-peptide complexes guided by the knowledge of the binding interface. [ABSTRACT FROM AUTHOR]

Molecular docking is a valuable in silico technique for discovery/design of bioactive compounds. A current challenge within docking simulations is the incorporation of receptor flexibility. A useful strategy toward solving such problem would be the docking of a typical ligand into the multiple conformations of the target. In this study, a multifactor response surface model was constructed to estimate the AutoDock based binding free energy of fluconazole within multiple conformations of 14α-demethylase (CYP51) (cross docking) as a validated antifungal target. On the basis of developed models, individual and interactive effects of important experimental parameters on cross docking of fluconazole were elucidated. For this purpose, a set of high-resolution holo crystallographic structures from CYP51 of human pathogen Trypanosoma cruzi were retrieved to statistically model the binding mode and affinity of fluconazole. The changes of AutoDock binding free energy for the complexes of CYP51-fluconazole were elucidated with the simultaneous variations of six independent variables including grid size, grid spacing, number of genetic algorithm (GA) runs, maximum number of energy evaluations, torsion degrees for ligand and quaternion degrees for ligand. It was revealed that grid spacing (distance between adjacent grid points) and maximum number of energy evaluations were two significant model terms. It was also revealed that grid size, torsion degrees for ligand and quaternion degrees for ligand had insignificant effects on estimated binding energy while the effect of GA runs was non-significant. The interactive effect of “torsion degrees for ligand” with number of GA runs was found to be the significant factor. Other important interactive effects were the interaction of “number of GA runs” with “grid spacing” and “number of energy evaluations” with “grid size”. Furthermore; results of modeling studies within several CYP51 conformations exhibited that “number of GA runs” and “number of energy evaluations” were less sensitive to varied target conformations. [ABSTRACT FROM AUTHOR]

Molecular docking methodology explores the behavior of small molecules in the binding site of a target protein. As more protein structures are determined experimentally using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy, molecular docking is increasingly used as a tool in drug discovery. Docking against homology-modeled targets also becomes possible for proteins whose structures are not known. With the docking strategies, the druggability of the compounds and their specificity against a particular target can be calculated for further lead optimization processes. Molecular docking programs perform a search algorithm in which the conformation of the ligand is evaluated recursively until the convergence to the minimum energy is reached. Finally, an affinity scoring function, ΔG [U total in kcal/mol], is employed to rank the candidate poses as the sum of the electrostatic and van der Waals energies. The driving forces for these specific interactions in biological systems aim toward complementarities between the shape and electrostatics of the binding site surfaces and the ligand or substrate. [ABSTRACT FROM AUTHOR]

Proteins and nucleic acids are key components in many processes in living cells, and interactions between proteins and nucleic acids are often crucial pathway components. In many cases, large flexibility of proteins as they interact with nucleic acids is key to their function. To understand the mechanisms of these processes, it is necessary to consider the 3D atomic structures of such protein-nucleic acid complexes. When such structures are not yet experimentally determined, protein docking can be used to computationally generate useful structure models. However, such docking has long had the limitation that the consideration of flexibility is usually limited to small movements or to small structures. We previously developed a method of flexible protein docking which could model ordered proteins which undergo large-scale conformational changes, which we also showed was compatible with nucleic acids. Here, we elaborate on the ability of that pipeline, Flex-LZerD, to model specifically interactions between proteins and nucleic acids, and demonstrate that Flex-LZerD can model more interactions and types of conformational change than previously shown., (© 2022 The Authors. Proteomics published by Wiley-VCH GmbH.)

Epigenetic alterations are associated with cancer and their targeting is a promising approach for treatment of this disease. Among current epigenetic drugs, histone deacetylase (HDAC) inhibitors induce changes in gene expression that can lead to cell death in tumors. Valproic acid (VPA) is a HDAC inhibitor that has antitumor activity at mM range. However, it is known that VPA is a hepatotoxic drug. Therefore, the aim of this study was to design a set of VPA derivatives adding the arylamine core of the suberoylanilide hydroxamic acid (SAHA) with different substituents at its carboxyl group. These derivatives were submitted to docking simulations to select the most promising compound. The compound 2 (N-(2-hydroxyphenyl)-2- propylpentanamide) was the best candidate to be synthesized and evaluated in vitro as an anticancer agent against HeLa, rhabdomyosarcoma and breast cancer cell lines. Compound 2 showed a better IC50 (mM range) than VPA (mM range) on these cancer cells. And also, 2 was particularly effective on triple negative breast cancer cells. In conclusion, 2 is an example of drugs designed in silico that show biological properties against human cancer difficult to treat as triple negative breast cancer. [ABSTRACT FROM AUTHOR]

Structure-based drug design starts with the collection, preparation, and initial analysis of protein structures. With more than 115,000 structures publically available in the Protein Data Bank (PDB), fully automated processes reliably performing these important preprocessing steps are needed. Several tools are available for these tasks, however, most of them do not address the special needs of scientists interested in protein-ligand interactions. In this paper, we summarize our research activities towards an automated processing pipeline from raw PDB data towards ready-to-use protein binding site ensembles. Starting from a single protein structure, the pipeline covers the following phases: Extracting structurally related binding sites from the PDB, aligning disconnected binding site sequences, resolving tautomeric forms and protonation, orienting hydrogens and flippable side-chains, structurally aligning the multitude of binding sites, and performing a reasonable reduction of ensemble structures. The pipeline, named SIENA, creates protein-structural ensembles for the analysis of protein flexibility, molecular design efforts like docking or de novo design within seconds. For the first time, we are able to process the whole PDB in order to create a large collection of protein binding site ensembles. SIENA is available as part of the ZBH ProteinsPlus webserver under http://proteinsplus.zbh.uni-hamburg.de. [ABSTRACT FROM AUTHOR]

Free fatty acid receptor 2 ( FFA2), also known as GPR43, is activated by short-chain fatty acids ( SCFAs) that are mainly produced by the gut microbiota through the fermentation of undigested carbohydrates and dietary fibers. FFA2 currently appears to be a potential target in the management of obesity, diabetes, inflammatory diseases, and cancer. In the study, a series of novel phenylthiazole-carboxamido acid derivatives has been synthesized and evaluated as potential orthosteric FFA2 ligands for the study of structure-activity relationships. Compound 6e was found to exhibit the twofold potent agonistic activity in the stable hFFA2-transfected CHO-K1 cells ( EC50 = 23.1 μ m) as that of positive control propionate ( EC50 = 43.3 μ m). We also reported the results of mutagenesis studies based on the crystal structure of hFFA1 bound to TAK-875 at 2.3 Å resolution to identify important residues for orthosteric agonist 6e inducing FFA2 activation. [ABSTRACT FROM AUTHOR]