Ensemble-based Virtual Screening Research Articles

Discovery of positive allosteric modulators of α7 nAChR by an ensemble-based virtual screening method, molecular dynamics simulation, and in vitro biological activity testing

Discovery of positive allosteric modulators of α7 nAChR by an ensemble-based virtual screening method, molecular dynamics simulation, and in vitro biological activity testing

Ensemble-Based Virtual Screening Led to the Discovery of Novel Lead Molecules as Potential NMBAs.

Neuromuscular blocking agents (NMBAs) are routinely used during anesthesia to relax skeletal muscle. Nicotinic acetylcholine receptors (nAChRs) are ligand-gated ion channels; NMBAs can induce muscle paralysis by preventing the neurotransmitter acetylcholine (ACh) from binding to nAChRs situated on the postsynaptic membranes. Despite widespread efforts, it is still a great challenge to find new NMBAs since the introduction of cisatracurium in 1995. In this work, an effective ensemble-based virtual screening method, including molecular property filters, 3D pharmacophore model, and molecular docking, was applied to discover potential NMBAs from the ZINC15 database. The results showed that screened hit compounds had better docking scores than the reference compound d-tubocurarine. In order to further investigate the binding modes between the hit compounds and nAChRs at simulated physiological conditions, the molecular dynamics simulation was performed. Deep analysis of the simulation results revealed that ZINC257459695 can stably bind to nAChRs' active sites and interact with the key residue Asp165. The binding free energies were also calculated for the obtained hits using the MM/GBSA method. In silico ADMET calculations were performed to assess the pharmacokinetic properties of hit compounds in the human body. Overall, the identified ZINC257459695 may be a promising lead compound for developing new NMBAs as an adjunct to general anesthesia, necessitating further investigations.

Discovery of novel Akt1 inhibitors by an ensemble-based virtual screening method, molecular dynamics simulation, and in vitro biological activity testing.

Akt1, as an important member of the Akt family, plays a controlled role in cancer cell growth and survival. Inhibition of Akt1 activity can promote cancer cell apoptosis and inhibit tumor growth. Therefore, in this investigation, a multilayer virtual screening approach, including receptor-ligand interaction-based pharmacophore, 3D-QSAR, molecular docking, and deep learning methods, was utilized to construct a virtual screening platform for Akt1 inhibitors. 17 representative compounds with different scaffolds were identified as potential Akt1 inhibitors from three databases. Among these 17 compounds, the Hit9 exhibited the best inhibitory activity against Akt1 with inhibition rate of 33.08% at concentration of 1μM. The molecular dynamics simulations revealed that Hit9 and Akt1 could form a compact and stable complex. Moreover, Hit9 interacted with some key residues by hydrophobic, electrostatic, and hydrogen bonding interactions and induced substantial conformation changes in the hinge region of the Akt1 active site. The average binding free energies for the Akt1-CQU, Akt1-Ipatasertib, and Akt1-Hit9 systems were - 34.44, - 63.37, and - 39.14kJ mol-1, respectively. In summary, the results obtained in this investigation suggested that Hit9 with novel scaffold may be a promising lead compound for developing new Akt1 inhibitor for treatment of various cancers with Akt1 overexpressed.

Discovery of Hit Compounds Targeting the P4 Allosteric Site of K-RAS, Identified through Ensemble-Based Virtual Screening.

Mutants of Ras are oncogenic drivers of a large number of human tumors. Despite being recognized as an attractive target for the treatment of cancer, the high affinity for its substrate tagged the protein as undruggable for a few years. The identification of cryptic pockets on the protein surface gave the opportunity to identify molecules capable of acting as allosteric modulators. Several molecules were disclosed in recent years, with sotorasib and adagrasib already approved for clinical use. The present study makes use of computational methods to characterize eight prospective allosteric pockets (P1-P8) in K-Ras, four of which (P1-P4) were previously characterized in the literature. The present study also describes the results of a virtual screening study focused on the discovery of hit compounds, binders of the P4 site that can be considered as peptidomimetics of a fragment of the SOS αI helix, a guanine exchange factor of Ras. After a detailed description of the computational procedure followed, we disclose five hit compounds, prospective binders of the P4 allosteric site that exhibit an inhibitory capability higher than 30% in a cell proliferation assay at 50 μM.

Probing the Activation Mechanisms of Agonist DPI-287 to Delta-Opioid Receptor and Novel Agonists Using Ensemble-Based Virtual Screening with Molecular Dynamics Simulations.

Pain drugs targeting mu-opioid receptors face major addiction problems that have caused an epidemic. The delta-opioid receptor (DOR) has shown to not cause addictive effects when bound to an agonist. While the active conformation of the DOR in complex with agonist DPI-287 has been recently solved, there are still no FDA-approved agonists targeting it, providing the opportunity for structure-based virtual screening. In this study, the conformational plasticity of the DOR was probed using molecular dynamics (MD) simulations, identifying two representative conformations from clustering analysis. The two MD conformations as well as the crystal conformation of DOR were used to screen novel compounds from the ZINC database (17 million compounds), in which 69 drugs were picked as potential compounds based on their docking scores. Notably, 37 out of the 69 compounds were obtained from the simulated conformations. The binding stability of the 69 compounds was further investigated using MD simulations. Based on the MM-GBSA binding energy and the predicted drug properties, eight compounds were chosen as the most favorable, six of which were from the simulated conformations. Using a dynamic network model, the communication between the crystal agonist and the top eight molecules with the receptor was analyzed to confirm if these novel compounds share a similar activation mechanism to the crystal ligand. Encouragingly, docking of these eight compounds to the other two opioid receptors (kappa and mu) suggests their good selectivity toward DOR.

Ensemble-based virtual screening of African natural products to target human thymidylate synthase

Human thymidylate synthase (hTS) is a validated drug target for chemotherapy. A virtual screening experiment was used to prioritize a list of compounds from African Natural Products Databases docked against the orthosteric binding pocket of hTS. Consensus scores of binding affinities from ensemble-based virtual screening, hydrated docking and MM-PBSA calculations ranked compounds NEA4433 and NEA4434 as the best candidates owing to binding affinity scores in the picomolar order, their excellent ADMET profiles and the good stability of the protein-ligand complexes formed. The current study demonstrates the role of water in small molecule binding to hTS in mediating protein-ligand interactions. Similarly, the robust ensemble docking (relaxed scheme complex) ranked NEA4433 and NEA4434 as the best candidates. Furthermore, the best candidates prioritized were shown to strongly interact with the same residues that interacted with hTS substrate and cofactor.

Discovery of novel S6K1 inhibitors by an ensemble-based virtual screening method and molecular dynamics simulation.

Ribosomal protein S6 kinase beta-1 (S6K1) is considered a potential target for the treatment of various diseases, such as obesity, type II diabetes, and cancer. Development of novel S6K1 inhibitors is an urgent and important task for the medicinal chemists. In this research, an effective ensemble-based virtual screening method, including common feature pharmacophore model, 3D-QSAR pharmacophore model, naïve Bayes classifier model, and molecular docking, was applied to discover potential S6K1 inhibitors from BioDiversity database with 29,158 compounds. Finally, 7 hits displayed considerable properties and considered as potential inhibitors against S6K1. Further, carefully analyzing the interactions between these 7 hits and key residues in the S6K1 active site, and comparing them with the reference compound PF-4708671, it was found that 2 hits exhibited better binding patterns. In order to further investigate the mechanism of the interactions between 2 hits and S6K1 at simulated physiological conditions, the molecular dynamics simulation was performed. The ΔGbind energies for S6K1-Hit1 and S6K1-Hit2 were - 111.47 ± 1.29 and - 54.29 ± 1.19kJmol-1, respectively. Furthermore, deep analysis of these results revealed that Hit1 was the most stable complex, which can stably bind to S6K1 active site, interact with all of the key residues, and induce H1, H2, and M-loop regions changes. Therefore, the identified Hit1 may be a promising lead compound for developing new S6K1 inhibitor for various metabolic diseases treatment.

Ensemble-based virtual screening of human PI4KIIIα inhibitors toward the Hepatitis C virus

The consideration of flexibility of protein structures in virtual screening still remains a challenge. In this work, an ensemble-based virtual screening method considering the dynamics and flexibility of the receptor protein is proposed. Representative structures of receptor protein are extracted from molecular dynamics simulations adopted to sample the protein’s conformational space, and used for the virtual screening in addition to the crystal structure. Ten potential inhibitors for PI4KIIIα were identified and MM/GBSA method was used to calculate the binding free energies and indentify the selective mechanisms. The method is expected to provide useful insights into the drug design.

Ensemble-based, high-throughput virtual screening of potential inhibitor targeting putative farnesol dehydrogenase of Metisa plana (Lepidoptera: Psychidae)

Metisa plana (Lepidoptera: Psychidae) bagworm is a leaf-eater caterpillar ubiquitously found as a damaging pest in oil palm plantations, specifically in Malaysia. Various strategies have been implemented, including the usage of chemical insecticides. However, the main challenges include the development of insecticide resistance and its detrimental effects on the environment and non-target organisms. Therefore, a biorational insecticide is introduced by targeting the juvenile hormone (JH) biosynthetic pathway, which is mainly present in the insect and vital for the insect's growth, diapause, metamorphosis, and adult reproduction. This study aimed to investigate the potential inhibitor for the rate-limiting enzyme involved in the JH pathway known as farnesol dehydrogenase. A 255 amino acids sequence encoded for the putative M. plana farnesol dehydrogenase (MpFolDH) open reading frame had been identified and isolated. The three-dimensional structure of MpFolDH was predicted to have seven β- sheets with α-helices at both sides, showing typical characteristics for classical short-chain dehydrogenase and associated with oxidoreductase activity. Then, the ensemble-based virtual screening was conducted based on the ZINC20 database, in which 43 768 compounds that fulfilled pesticide-likeness criteria were screened by site-specific molecular docking. After a short molecular dynamics simulation (5 ns) was conducted towards 102 compounds, only the top 10 compounds based on their most favourable binding energy were selected for a more extended simulation (100 ns). Based on the protein-ligand stability, protein compactness, residues rigidity, binding interaction, binding energy throughout the 100 ns simulation, and physicochemical analysis, ZINC000408743205 was selected as a potential inhibitor for this enzyme. Amino acids decomposition analysis indicates Ile18, Ala95, Val198 and Val202 were the critical contributor residues for MpFolDH-inhibitors(s) complex.

An ensemble docking-based virtual screening according to different TRPV1 pore states toward identifying phytochemical activators

Identifying phytochemical activators for TRPV1 using ensemble-based virtual screening, machine learning, and MD simulation.

Targeting human thymidylate synthase: Ensemble-based virtual screening for drug repositioning and the role of water

A drug repositioning computational approach was carried to search inhibitors for human thymidylate synthase. An ensemble-based virtual screening of FDA-approved drugs showed the drugs Imatinib, Lumacaftor and Naldemedine to be likely candidates for repurposing. The role of water in the drug-receptor interactions was revealed by the application of an extended AutoDock scoring function that included the water forcefield. The binding affinity scores when hydrated ligands were docked were improved in the drugs considered. Further binding free energy calculations based on the Molecular Mechanics Poisson-Boltzmann Surface Area method revealed that Imatinib, Lumacaftor and Naldemedine scored −130.7 ± 28.1, −210.6 ± 29.9 and −238.0 ± 25.4 kJ/mol, respectively, showing good binding affinity for the candidates considered. Overall, the analysis of the molecular dynamics trajectory of the receptor-drug complexes revealed stable structures for Imatinib, Lumacaftor and Naldemedine, for the entire simulation time.

Identification of Novel Inhibitors Targeting SGK1 via Ensemble-Based Virtual Screening Method, Biological Evaluation and Molecular Dynamics Simulation.

Serum and glucocorticoid-regulated kinase 1 (SGK1), as a serine threonine protein kinase of the AGC family, regulates different enzymes, transcription factors, ion channels, transporters, and cell proliferation and apoptosis. Inhibition of SGK1 is considered as a valuable approach for the treatment of various metabolic diseases. In this investigation, virtual screening methods, including pharmacophore models, Bayesian classifiers, and molecular docking, were combined to discover novel inhibitors of SGK1 from the database with 29,158 compounds. Then, the screened compounds were subjected to ADME/T, PAINS and drug-likeness analysis. Finally, 28 compounds with potential inhibition activity against SGK1 were selected for biological evaluation. The kinase inhibition activity test revealed that among these 28 hits, hit15 exhibited the highest inhibition activity against SGK1, which gave 44.79% inhibition rate at the concentration of 10 µM. In order to further investigate the interaction mechanism of hit15 and SGK1 at simulated physiological conditions, a molecular dynamics simulation was performed. The molecular dynamics simulation demonstrated that hit15 could bind to the active site of SGK1 and form stable interactions with key residues, such as Tyr178, ILE179, and VAL112. The binding free energy of the SGK1-hit15 was −48.90 kJ mol−1. Therefore, the identified hit15 with novel scaffold may be a promising lead compound for development of new SGK1 inhibitors for various diseases treatment.

Finding alternatives to 5-fluorouracil: application of ensemble-based virtual screening for drug repositioning against human thymidylate synthase

5-fluorouracil and analogs are used in the treatment of many solid tumours. However, there are many cases of resistance and high toxicity associated with 5-fluorouracil chemotherapy. Repurposing FDA drugs against human thymidylate synthase revealed a number of FDA drugs that have a potential to be further developed for the treatment of various cancers for which 5-fluorouracil and analogs have been used for chemotherapy. Four FDA drugs prioritized for further validation included Erismodegib, Irinotecan, Conivaptan and Ergotamine. The role of water in mediating drug interactions and its contribution to the total binding energy was also shown. MM-PBSA calculations revealed that the binding affinity was the lowest for the hTS-Ergotamine complex (–66.702 ± 1.807 kJ/mol) suggesting moderate inhibition despite a large energetic contribution from van der Waal interactions (–190.889 ± 1.027 kJ/mol). Communicated by Ramaswamy H. Sarma

Drug repurposing against SARS-CoV-2 receptor binding domain using ensemble-based virtual screening and molecular dynamics simulations

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused worldwide pandemic and is responsible for millions of worldwide deaths due to -a respiratory disease known as COVID-19. In the search for a cure of COVID-19, drug repurposing is a fast and cost-effective approach to identify anti-COVID-19 drugs from existing drugs. The receptor binding domain (RBD) of the SARS-CoV-2 spike protein has been a main target for drug designs to block spike protein binding to ACE2 proteins. In this study, we probed the conformational plasticity of the RBD using long molecular dynamics (MD) simulations, from which, representative conformations were identified using clustering analysis. Three simulated conformations and the original crystal structure were used to screen FDA approved drugs (2466 drugs) against the predicted binding site at the ACE2-RBD interface, leading to 18 drugs with top docking scores. Notably, 16 out of the 18 drugs were obtained from the simulated conformations, while the crystal structure suggests poor binding. The binding stability of the 18 drugs were further investigated using MD simulations. Encouragingly, 6 drugs exhibited stable binding with RBD at the ACE2-RBD interface and 3 of them (gonadorelin, fondaparinux and atorvastatin) showed significantly enhanced binding after the MD simulations. Our study shows that flexibility modeling of SARS-CoV-2 RBD using MD simulation is of great help in identifying novel agents which might block the interaction between human ACE2 and the SARS-CoV-2 RBD for inhibiting the virus infection.

Inhibition of SARS-CoV-2 main protease: a repurposing study that targets the dimer interface of the protein

Coronavirus disease-2019 (COVID-19) was firstly reported in Wuhan, China, towards the end of 2019, and emerged as a pandemic. The spread and lethality rates of the COVID-19 have ignited studies that focus on the development of therapeutics for either treatment or prophylaxis purposes. In parallel, drug repurposing studies have also come into prominence. Herein, we aimed at having a holistic understanding of conformational and dynamical changes induced by an experimentally characterized inhibitor on main protease (Mpro) which would enable the discovery of novel inhibitors. To this end, we performed molecular dynamics simulations using crystal structures of apo and α-ketoamide 13b-bound Mpro homodimer. Analysis of trajectories pertaining to apo Mpro revealed a new target site, which is located at the homodimer interface, next to the catalytic dyad. Thereafter, we performed ensemble-based virtual screening by exploiting the ZINC and DrugBank databases and identified three candidate molecules, namely eluxadoline, diosmin, and ZINC02948810 that could invoke local and global conformational rearrangements which were also elicited by α-ketoamide 13b on the catalytic dyad of Mpro. Furthermore, ZINC23881687 stably interacted with catalytically important residues Glu166 and Ser1 and the target site throughout the simulation. However, it gave positive binding energy, presumably, due to displaying higher flexibility that might dominate the entropic term, which is not included in the MM-PBSA method. Finally, ZINC20425029, whose mode of action was different, modulated dynamical properties of catalytically important residue, Ala285. As such, this study presents valuable findings that might be used in the development of novel therapeutics against Mpro. Communicated by Ramaswamy H. Sarma

Ensemble-based high-throughput virtual screening of natural ligands using the Super Natural-II database against cell-wall protein dTDP-4-dehydrorhamnose reductase (RmlD) in Mycobacterium tuberculosis

The disease Tuberculosis (TB) is caused by a bacterium called Mycobacterium tuberculosis (Mtb). The bacterial cell-wall consists of peptidoglycan layer maintains the cellular integrity and cell viability. The main problem resides in the cell cycle of Mycobacterium tuberculosis in its quiescent form which is not targeted by any drugs hence there is an immediate need for new antibiotics to target the cell wall. The current study deals with the dTDP-4-dehydrorahmnose reductase (RmlD) which is the final enzyme in the series of cell-wall proteins of Mtb. The RmlD is a part of Carbohydrate biosynthesis has been considered as a good drug target for the novel class of antibiotics. Our study begins with the protein structure prediction, Homology studies were conducted using the Phyre2 web server. The structure is then refined and subjected to molecular dynamics simulations for 50 ns using GROMACS. The clustering analysis has been carried out and generated 41 clusters with 2 Å as the cut-off. Blind docking virtual screening was performed against RmlD protein using the Super Natural-II database with AutoDock4.0. its results helped to screen top ligands based on best binding energies. In both dockings, there are some common residues in which the ligands are interacting and forming the Hydrogen bonds such as Asp-105, Val-158, Thr-160, Gly-161, Arg-224, Arg-256. The ligand-567 giving the best results by being in the top-3 of all the clusters in both blind docking as well as the active-site docking. Hence ligand-567 can be a potential inhibitor of RmlD which can further inhibit the cell-wall synthesis of Mycobacterium tuberculosis. Communicated by Ramaswamy H. Sarma

Ensemble-based virtual screening in discovering potent inhibitors targeting Von Hippel-Lindau (VHL) E3 ubiquitin ligase

BackgroundThe Von Hippel-Lindau (VHL) E3 ubiquitin ligase, which mediates its substrate hypoxia-inducible factor 1α (HIF-1α) for ubiquitination and subsequent degradation, is an attractive drug target in various diseases, such as anemia, inflammation, neurodegeneration and cancer. Proteolysis targeting chimeras (PROTACs) containing a VHL ligand that can hijack the E3 ligase activity to degrade the target protein has also been studied in academic and in industry areas recently. MethodsHerein, by developing and optimizing the Bayesian Model, we report ensemble-based virtual screening as an effective strategy to discover potential VHL inhibitors from Specs database. ResultsThe virtual screening protocol was developed, ten representative molecules were obtained and five compounds were selected for subsequent binding mode analysis to be potent VHL inhibitors.

Multi-target, ensemble-based virtual screening yields novel allosteric KRAS inhibitors at high success rate.

RAS mutations account for >15% of all human tumors, and of these ~85% are due to mutations in a particular RAS gene: KRAS. Recent studies revealed that KRAS harbors four druggable allosteric sites. Here, we have (a) used molecular simulations to generate ensembles of wild type and four major oncogenic KRAS mutants (G12V, G12D, G13D, and Q61H); (b) characterized the druggability of each allosteric pocket in each protein; (c) conducted extensive ensemble-based virtual screening using pocket-tailored ligand libraries; (d) prioritized hits through hierarchical postdocking analysis; and (e) validated predicted hits with NMR. Of the 785 diverse potential hits identified by our in silico analysis, we tested 90 for their ability to bind KRAS using NMR and found that nine cause backbone amide chemical shift perturbations of residues near the functionally responsive switch loops, suggesting potential binding. We conducted detailed biophysical analyses on a novel indole-based compound to demonstrate the potential of our workflow to yield lead compounds. We believe the detailed information documented in this work regarding the druggability profile of each allosteric site and the chemical fingerprints of compounds that target them will serve as vital resources for future structure-based drug design efforts against KRAS, a high-value target for cancer therapy.

Ensemble-based virtual screening: identification of a potential allosteric inhibitor of Bcr-Abl

Ensemble-based virtual screening using different conformations of a target protein is gaining popularity, as it can leverage information from target flexibility for effective lead identification. In this paper, molecular dynamics simulation followed by RMSD-based clustering was employed to generate and choose distinct conformations of Bcr-Abl. Three representative structures from the most-populated clusters along with the crystal structure conformation (PDBID: 3K5V) were used to perform docking-based virtual screening of 14,400 compounds (in the Maybridge database) in order to identify potential allosteric site binders. Seven compounds found as hits in at least three of the four virtual screenings had higher Glide docking scores than the co-crystallized allosteric inhibitor GNF-2. Detailed computational analyses of the seven hits identified SEW02675 (ΔG bind=-164.92kJ/mol with the wild-type (wt) Bcr-Abl and -167.37kJ/mol with the T334I Bcr-Abl mutant) as a better allosteric site binder with both the wt and the mutant Bcr-Abl protein than the reference allosteric inhibitor GNF-2 (ΔG bind=-103.12 with wt and -142.96kJ/mol with T334I). Moreover, the presence of SEW02675 in the allosteric site enhanced the binding of imatinib (ΔG bind=-367.58 with wt and -294.56kJ/mol with T334I) to the ATP sites of the wt and the mutant Bcr-Abl. However, when GNF-2 was present in the allosteric site, the binding of imatinib (ΔG bind=-351.76 with wt and -273.94kJ/mol with T334I) to the ATP site was weaker. The in silico findings suggest that SEW02675 could be used in combination with imatinib to treat chronic myeloid leukemia, and that it could help to overcome resistance due to T334I Bcr-Abl mutation. Graphical abstract Virtual screening strategy to identify allosteric inhbitors of Bcr-Abl for the treatment of Chronic myeloid leukemia.

Ensemble-Based Virtual Screening Led to the Discovery of New Classes of Potent Tyrosinase Inhibitors.

In this study, we report new classes of potent tyrosinase inhibitors identified by enhanced structure-based virtual screening prediction; the enzyme and melanin content assays were also confirmed. Tyrosinase, a type-3 copper protein, participates in two distinct reactions, hydroxylation of tyrosine to DOPA and conversion of DOPA to dopaquinone, in melanin biosynthesis. Although numerous inhibitors of this reaction have been reported, there is a lag in the discovery of the new functional moieties. In order to improve the performance of virtual screening, we first produced an ensemble of 10,000 structures using molecular dynamics simulation. Quantum mechanical calculation was used to determine the partial charges of catalytic copper ions based on the met and deoxy states. Second, we selected a structure showing an optimal receiver operating characteristic (ROC) curve with known direct binders and their physicochemically matched decoys. The structure revealed more than 10-fold higher enrichment at 1% of the ROC curve than those observed in X-ray structures. Third, high-throughput virtual screening with DOCK 3.6 was performed using a library consisting of approximately 400,000 small molecules derived from the ZINC database. Fourth, we obtained the top 60 molecules and tested their inhibition of mushroom tyrosinase. The extended assays included 21 analogs of the 21 initial hits to test their inhibition properties. Here, the moieties of tetrazole and triazole were identified as new binding cores interacting with the dicopper catalytic center. All 42 inhibitors showed inhibitory constant, Ki, values ranging from 11.1 nM and 33.4 μM, with a tetrazole compound exhibiting the strongest activity. Among the 42 molecules, five displayed more than 30% reduction in melanin production when treated in B16F10 melanoma cells; cell viability was >90% at 20 μM. Particularly, a thiosemicarbazone-containing compound reduced melanin content by 55%.