Modeling of a new tubercular maltosyl transferase,GlgE, study of its binding sites and virtual screening

Recently maltosyl transferase of Mycobacterium tuberculosis (mtb GlgE) belonging to α-amylase family has been identified as a potential drug target. Despite its importance, its three dimensional (3D) structure is unavailable. In this study we have modeled its 3D homo-dimeric structure using its homologue in Streptomyces ceolicolor (stp GlgE) as the template. Its monomer consists of five domains and four inserts, out of which two inserts are unique to mtb GlgE. It also has three binding cavities. One primary (pbs) and two secondary (sbs1 and sbs2), with one unique insert appearing within sbs2. Investigation of its homo-dimeric model revealed the presence of a disulphide bridge between Cys-29 of both the chains which is absent in stp GlgE. Virtual screening with known substrates and substrate analogues of α-amylase family proteins indicated better binding of maltose to sbs1 than pbs. Among all computationally screened substrates 3-O-Alpha-d-Glucopyranosyl-d-Fructose (OTU) docked with best binding affinity to pbs. Interaction of known inhibitors of α-amylase family proteins from CHEMBL is also studied. This reveals for the first time the unique 3D structure of mtb GlgE and provides insights into its active sites and substrate binding affinities. This may help in developing new anti-tubercular drugs and its analogues.     

Pharmacoinformatics analysis to identify inhibitors of Mtb-ASADH

Aspartate-semialdehyde dehydrogenase (ASADH; EC 1.2.1.11) is a key enzyme in the biosynthesis of essential amino acids in prokaryotes and fungi, inhibition of ASADH leads to the development of novel antitubercular agents. In the present work, a combined structure and ligand-based pharmacophore modeling, molecular docking, and molecular dynamics (MD) approaches were employed to identify potent inhibitors of mycobacterium tuberculosis (Mtb)-ASADH. The structure-based pharmacophore hypothesis consists of three hydrogen bond acceptor (HBA), two negatively ionizable, and one positively ionizable center, while ligand-based pharmacophore consists of additional one HBA and one hydrogen bond donor features. The validated pharmacophore models were used to screen the chemical databases (ZINC and NCI). The screened hits were subjected to ADME and toxicity filters, and subsequently to the molecular docking analysis. Best-docked 25 compounds carry the characteristics of highly electronegative functional groups (–COOH and –NO₂) on both sides and exhibited the H-bonding interactions with highly conserved residues Arg99, Arg249, and His256. For further validation of docking results, MD simulation studies were carried out on two representative compounds NSC51108 and ZINC04203124. Both the compounds remain bound to the key active residues of Mtb-ASADH during the MD simulations. These identified hits can be further used for lead optimization and in the design more potent inhibitors against Mtb-ASADH.     

Targeting the NTPase site of Zika virus NS3 helicase for inhibitor discovery

Abstract

The major threats linked to Zika virus (ZIKV) are microcephaly, Guillain-Barre syndrome, and the ability to transfer through sexual transmission. Despite these threats, Zika specific FDA approved drugs or vaccines are not available as of yet. Additionally, the involvement of pregnant women makes the drug screening process lengthy and complicated in terms of safety and minimum toxicity of the molecules. Since NS3 helicase of ZIKV performs the critical function of unwinding double-stranded RNA during replication, it is considered as a promising drug target to block ZIKV replication. In the present study, we have exploited the NTPase site of ZIKV NS3 helicase for screening potential inhibitor compounds by molecular docking, and molecular dynamics (MD) simulation approaches. NS3 helicase hydrolyzes the ATP to use its energy for unwinding RNA. We have chosen twenty natural compounds from ZINC library with known antiviral properties and a helicase focused library (HFL) of small molecules from Life Chemicals compounds. After going through docking, the top hit molecules from ZINC and HFL library were further analysed by MD simulations to find out stable binding poses. Finally, we have reported the molecules with potential of binding at NTPase pocket of ZIKV NS3 helicase, which could be further tested on virus through in vitro experiments to check their efficacy.

Communicated by Ramaswamy H. Sarma     

Virtual screening to identify <Emphasis Type="Italic">Leishmania braziliensis N</Emphasis>-myristoyltransferase inhibitors: pharmacophore models,docking, and molecular dynamics

Leishmaniasis is caused by several protozoa species belonging to genus Leishmania that are hosted by humans and other mammals. Millions of new cases are recorded every year and the drugs available on the market do not show satisfactory efficacy and safety. A hierarchical virtual screening approach based on the pharmacophore model, molecular docking, and molecular dynamics was conducted to identify possible Leishmania braziliensis N-misristoyltransferase (LbNMT) inhibitors. The adopted pharmacophore model had three main features: four hydrophobic centers, four hydrogen-bond acceptor atoms, and one positive nitrogen center. The molecules (n=15,000) were submitted to alignment with the pharmacophore model and only 27 molecules aligned to model. Six molecules were submitted to molecular docking, using receptor PDB ID 5A27. After docking, the ZINC35426134 was a top-ranked molecule (? 64.61 kcal/mol). The molecule ZINC35426134 shows hydrophobic interactions with Phe82, Tyr209, Val370, and Leu391 and hydrogen bonds with Asn159, Tyr318, and Val370. Molecular dynamics simulations were performed with the protein in its APO and HOLO forms for 37 ns in order to assess the stability of the protein–ligand complex. Results showed that the HOLO form was more stable than the APO one, and it suggests that the ZINC35426134 binding stabilizes the enzyme. Therefore, the selected molecule has the potential to meet the herein proposed target.     

Identification of novel inhibitor of protein tyrosine phosphatases delta: structure-based pharmacophore modeling,virtual screening,flexible docking,molecular dynamics simulation,and post-molecular dynamics analysis

Abstract

Owing to their unique functions in regulating the synapse activity of protein tyrosine phosphatases delta (PTPδ) that has drawn special attention for developing drugs to autism spectrum disorders (ASDs). In this study, the PTPδ pharmacophore was first established by the structure-based pharmacophore method. Subsequently, 10 compounds contented Lipinski’s rule of five was acquired by the virtual screening of the PTPδ pharmacophore against ZINC and PubChem databases. Then, the 10 identified molecules were discovered that had better binding affinity than a known PTPδ inhibitors compound SCHEMBL16375396. Two compounds SCHEMBL16375408 and ZINC19796658 with high binding score, low toxicity were gained. They were observed by docking analysis and molecular dynamics simulations that the novel potential inhibitors not only possessed the same function as SCHEMBL16375396 did in inhibiting PTPδ, but also had more favorable conformation to bind with the catalytic active regions. This study provides a new method for identify PTPδ inhibitor for the treatment of ASDs disease.

Communicated by Ramaswamy H. Sarma     

Identification of potential leukocyte antigen-related protein (PTP-LAR) inhibitors through 3D QSAR pharmacophore-based virtual screening and molecular dynamics simulation

Abstract

Owing to its negative regulatory role in insulin signaling, protein tyrosine phosphatase of leukocyte antigen-related protein (PTP-LAR) was widely thought as a potential drug target for diabetes. Now, it was urgent to search for potential LAR inhibitors targeting diabetes. Initially, the pharmacophore models of LAR inhibitors were established with the application of the HypoGen module. The cost analysis, test set validation, as well as Fischer’s test was used to verify the efficiency of pharmacophore model. Then, the best pharmacophore model (Hypo-1-LAR) was applied for the virtual screening of the ZINC database. And 30 compounds met the Lipinski’s rule of five. Among them, 10 compounds with better binding affinity than the known LAR inhibitor (BDBM50296375) were discovered by docking studies. Finally, molecular dynamics simulations and post-analysis experiments (RMSD, RMSF, PCA, DCCM and RIN) were conducted to explore the effect of ligands (ZINC97018474 and Compound 1) on LAR and preliminary understand why ZINC97018474 had better inhibitory activity than Compound 1 (BDBM50296375).

Communicated by Ramaswamy H. Sarma     

Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Binding mode exploration of LuxR-thiazolidinedione analogues,e-pharmacophore-based virtual screening in the designing of LuxR inhibitors and its biological evaluation

Master quorum sensing (QS) regulator LuxR of Vibrio harveyi is a unique member of the TetR protein superfamily. Recent studies have demonstrated the contribution of thiazolidinedione analogues in blocking QS by decreasing the DNA-binding ability of LuxR. However, the precise mechanism of thiazolidinedione analogues binding to LuxR is still unclear. In the present study, molecular docking combined with molecular dynamics (MD) simulations was performed to understand the mechanism of ligand binding to the protein. The binding pattern of thiazolidinedione analogues showed strong hydrogen bonding interactions with the amine group (NH) of polar amino acid residue Asn133 and carbonyl (C=O) interaction with negatively charged amino acid residue Gln137 in the binding site of LuxR. The stability of the protein–ligand complexes was confirmed by running 50 ns of MD simulations. Further, the four-featured pharmacophore hypothesis (AHHD) consists of one acceptor (A), two hydrophobic regions (HH) and one donor (D) group was used to screen compounds from ChemBridge database. The identified hit molecules were shown to have excellent pharmacokinetic properties under the acceptable range. Based on the computational studies, ChemBridge_5343641 was selected for in vitro assays. The 1-(4-chlorophenoxy)-3-[(4,6-dimethyl-2-pyrimidinyl)thio]-2-propanol (ChemBridge_5343641) showed significant reduction in bioluminescence in a dose-dependent manner. In addition, ChemBridge_5343641 inhibits biofilm formation and motility in V. harveyi. The result from the study suggests that ChemBridge_5343641 could serve as an anti-QS molecule.     

E-pharmacophore-based virtual screening to identify GSK-3β inhibitors

Glycogen synthase kinase-3β (GSK-3β) is a serine/threonine kinase which has attracted significant attention during recent years in drug design studies. The deregulation of GSK-3β increased the loss of hippocampal neurons by triggering apoptosis-mediating production of neurofibrillary tangles and alleviates memory deficits in Alzheimer’s disease (AD). Given its role in the formation of neurofibrillary tangles leading to AD, it has been a major therapeutic target for intervention in AD, hence was targeted in the present study. Twenty crystal structures were refined to generate pharmacophore models based on energy involvement in binding co-crystal ligands. Four common e-pharmacophore models were optimized from the 20 pharmacophore models. Shape-based screening of four e-pharmacophore models against nine established small molecule databases using Phase v3.9 had resulted in 1800 compounds having similar pharmacophore features. Rigid receptor docking (RRD) was performed for 1800 compounds and 20 co-crystal ligands with GSK-3β to generate dock complexes. Interactions of the best scoring lead obtained through RRD were further studied with quantum polarized ligand docking (QPLD), induced fit docking (IFD) and molecular mechanics/generalized Born surface area. Comparing the obtained leads to 20 co-crystal ligands resulted in 18 leads among them, lead1 had the lowest docking score, lower binding free energy and better binding orientation toward GSK-3β. The 50?ns MD simulations run confirmed the stable nature of GSK-3β-lead1 docking complex. The results from RRD, QPLD, IFD and MD simulations confirmed that lead1 might be used as a potent antagonist for GSK-3β.     

Homology modeling,docking and structure-based virtual screening for new inhibitor identification of Klebsiella pneumoniae heptosyltransferase-III

Abstract

Klebsiella pneumoniae (K. pneumoniae) is a Gram-negative opportunistic pathogen commonly associated with hospital-acquired infections that are often resistant even to antibiotics. Heptosyltransferase (HEP) belongs to the family of glycosyltransferase-B (GT-B) and plays an important in the synthesis of lipopolysaccharides (LPS) essential for the formation of bacterial cell membrane. HEP-III participates in the transfer of heptose sugar to the outer surface of bacteria to synthesize LPS. LPS truncation increases the bacterial sensitivity to hydrophobic antibiotics and detergents, making the HEP as a novel drug target. In the present study, we report the 3D homology model of K. pneumoniae HEP-III and its structure validation. Active site was identified based on similarities with known structures using Dali server, and structure-based pharmacophore model was developed for the active site substrate ADP. The generated pharmacophore model was used as a 3D search query for virtual screening of the ASINEX database. The hit compounds were further filtered based on fit value, molecular docking, docking scores, molecular dynamics (MD) simulations of HEP-III complexed with hit molecules, followed by binding free energy calculations using Molecular Mechanics-Poisson–Boltzmann Surface Area (MM-PBSA). The insights obtained in this work provide the rationale for design of novel inhibitors targeting K. pneumoniae HEP-III and the mechanistic aspects of their binding.

Communicated by Ramaswamy H. Sarma     

In silico docking and molecular dynamics simulation of 3-dehydroquinate synthase (DHQS) from <Emphasis Type="Italic">Mycobacterium tuberculosis</Emphasis>

The shikimate pathway is as an attractive target because it is present in bacteria, algae, fungi, and plants but does not occur in mammals. In Mycobacterium tuberculosis (MTB), the shikimate pathway is integral to the biosynthesis of naphthoquinones, menaquinones, and mycobactin. In these study, novel inhibitors of 3-dehydroquinate synthase (DHQS), an enzyme that catalyzes the second step of the shikimate pathway in MTB, were determined. 12,165 compounds were selected from two public databases through virtual screening and molecular docking analysis using PyRx 8.0 and Autodock 4.2, respectively. A total of 18 compounds with the best binding energies (?13.23 to ?8.22 kcal/mol) were then selected and screened for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis, and nine of those compounds were found to satisfy all of the ADME and toxicity criteria. Among those nine, the three compounds—ZINC633887?(binding energy =??10.29 kcal/mol), ZINC08983432?(?9.34 kcal/mol), and PubChem73393?(?8.61 kcal/mol)—with the best binding energies were further selected for molecular dynamics (MD) simulation analysis. The results of the 50-ns MD simulations showed that the two compounds ZINC633887 and PubChem73393 formed stable complexes with DHQS and that the structures of those two ligands remained largely unchanged at the ligand-binding site during the simulations. These two compounds identified through docking and MD simulation are potential candidates for the treatment of TB, and should undergo validation in vivo and in vitro.     

A combination of pharmacophore modeling,atom-based 3D-QSAR,molecular docking and molecular dynamics simulation studies on PDE4 enzyme inhibitors

Phosphodiesterases 4 enzyme is an attractive target for the design of anti-inflammatory and bronchodilator agents. In the present study, pharmacophore and atom-based 3D-QSAR studies were carried out for pyrazolopyridine and quinoline derivatives using Schrödinger suite 2014-3. A four-point pharmacophore model was developed using 74 molecules having pIC₅₀ ranging from 10.1 to 4.5. The best four feature model consists of one hydrogen bond acceptor, two aromatic rings, and one hydrophobic group. The pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a high correlation coefficient (R^2?=?.9949), cross validation coefficient (Q^2?=?.7291), and Pearson-r (.9107) at six component partial least square factor. The external validation indicated that our QSAR model possessed high predictive power with R² value of .88. The generated model was further validated by enrichment studies using the decoy test. Molecular docking, free energy calculation, and molecular dynamics (MD) simulation studies have been performed to explore the putative binding modes of these ligands. A 10-ns MD simulation confirmed the docking results of both stability of the 1XMU–ligand complex and the presumed active conformation. Outcomes of the present study provide insight in designing novel molecules with better PDE4 inhibitory activity.     

Computational screening of dipeptidyl peptidase IV inhibitors from micoroalgal metabolites by pharmacophore modeling and molecular docking

Dipeptidyl peptidase IV (DPP‐IV) catalyzes conversion of GLP‐1 (glucagon like peptide 1) to inert structure, which results in insufficient secretion of insulin and increase in postprandial blood glucose level. The present study attempts to identify novel inhibitors from bioactive metabolites present in microalgae against DPP‐IV through virtual screening, molecular docking, and pharmacophore modeling for the active target. Possible binding modes of all 60 ligands against DPP‐IV receptor were constructed using MTiOpenScreen virtual screening server. Pharmacophore model was built based on identified 38 DPP‐IV test ligands by using the web‐based PharmaGist program which encompasses hydrogen‐bond acceptors, hydrophobic groups, spatial features, and aromatic rings. The pharmacophore model having highest scores was selected to screen active DPP‐IV ligands. Highest scoring model was used as a query in ZincPharmer screening. All identified ligands were filtered, based on the Lipinski's rule‐of‐five and were subjected to docking studies. In the process of docking analyses, we considered different bonding modes of one ligand with multiple active cavities of DPP‐IV with the help of AutoDock 4.0. The docking analyses indicate that the bioactive constituents, namely, β‐stigmasterol, barbamide, docosahexaenoic acid, arachidonic acid, and harman showed the best binding energies on DPP‐IV receptor and hydrogen bonding with ASP545, GLY741, TYR754, TYR666, ARG125, TYR547, SER630, and LYS554 residues. This study concludes that docosahexaenoic acid, arachidonic acid, β‐stigmasterol, barbamide, harman, ZINC58564986, ZINC56907325, ZINC69432950, ZINC69431828, ZINC73533041, ZINC84287073, ZINC69849395, and ZINC10508406 act as possible DPP‐IV inhibitors.     

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling,structure based pharmacophore,molecular docking,and molecular dynamics simulations

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.     

Combined pharmacophore modeling, 3D-QSAR and docking studies to identify novel HDAC inhibitors using drug repurposing

Abstract

Histone deacetylases (HDACs), a critical family of epigenetic enzymes, has emerged as a promising target for antitumor drugs. Here, we describe our protocol of virtual screening in identification of novel potential HDAC inhibitors through pharmacophore modeling, 3D-QSAR, molecular docking and molecular dynamics (MD) simulation. Considering the limitation of current virtual screening works, drug repurposing strategy was applied to discover druggable HDAC inhibitor. The ligand-based pharmacophore and 3D-QSAR models were established, and their reliability was validated by different methods. Then, the DrugBank database was screened, followed by molecular docking. MD simulation (100?ns) was performed to further study the stability of ligand binding modes. Finally, results indicated the hit DB03889 with high in silico inhibitory potency was suitable for further experimental analysis.

Communicated by Ramaswamy H. Sarma     

Virtual screening of small molecules databases for discovery of novel PARP-1 inhibitors: combination of in silico and in vitro studies

Poly(ADP-ribose) polymerase-1 (PARP-1) enzyme has critical roles in DNA replication repair and recombination. Thus, PARP-1 inhibitors play an important role in the cancer therapy. In the current study, we have performed combination of in silico and in vitro studies in order to discover novel inhibitors against PARP-1 target. Structure-based virtual screening was carried out for an available small molecules database. A total of 257,951 ligands from Otava database were screened at the binding pocket of PARP-1 using high-throughput virtual screening techniques. Filtered structures based on predicted binding energy results were then used in more sophisticated molecular docking simulations (i.e. Glide/standard precision, Glide/XP, induced fit docking – IFD, and quantum mechanics polarized ligand docking – QPLD). Potential high binding affinity compounds that are predicted by molecular simulations were then tested by in vitro methods. Computationally proposed compounds as PARP-1 inhibitors (Otava Compound Codes: 7111620047 and 7119980926) were confirmed by in vitro studies. In vitro results showed that compounds 7111620047 and 7119980926 have IC₅₀ values of 0.56 and 63 μM against PARP-1 target, respectively. The molecular mechanism analysis, free energy perturbation calculations using long multiple molecular dynamics simulations for the discovered compounds which showed high binding affinity against PARP-1 enzyme, as well as structure-based pharmacophore development (E-pharmacophore) studies were also studied.     

Identification of Phytochemicals Targeting c-Met Kinase Domain using Consensus Docking and Molecular Dynamics Simulation Studies

c-Met receptor tyrosine kinase is a proto-oncogene whose aberrant activation is attributed to a lower rate of survival in most cancers. Natural product-derived inhibitors known as “fourth generation inhibitors” constitute more than 60% of anticancer drugs. Furthermore, consensus docking approach has recently been introduced to augment docking accuracy and reduce false positives during a virtual screening. In order to obtain novel small-molecule Met inhibitors, consensus docking approach was performed using Autodock Vina and Autodock 4.2 to virtual screen Naturally Occurring Plant-based Anti-cancer Compound–Activity–Target database against active and inactive conformation of c-Met kinase domain structure. Two hit molecules that were in line with drug-likeness criteria, desired docking score, and binding pose were subjected to molecular dynamics simulations to elucidate intermolecular contacts in protein–ligand complexes. Analysis of molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area studies showed that ZINC08234189 is a plausible inhibitor for the active state of c-Met, whereas ZINC03871891 may be more effective toward active c-Met kinase domain compared to the inactive form due to higher binding energy. Our analysis showed that both the hit molecules formed hydrogen bonds with key residues of the hinge region (P1158, M1160) in the active form, which is a hallmark of kinase domain inhibitors. Considering the pivotal role of HGF/c-Met signaling in carcinogenesis, our results propose ZINC08234189 and ZINC03871891 as the therapeutic options to surmount Met-dependent cancers.     

Shape-based virtual screening,docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors

Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand–enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6?Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.     

Identification of InhA inhibitors: A combination of virtual screening,molecular dynamics simulations and quantum chemical studies

In the present work, multiple pharmacophore-based virtual screening of the SPECS natural product database was carried out to identify novel inhibitors of the validated biological target, InhA. The pharmacophore models were built from the five different groups of the co-crystallized ligands present within the active site. The generated models with the same features from each group were pooled and subjected to the test set validation, receiver–operator characteristic analysis and Güner–Henry studies. A set of five hypotheses with sensitivity > 0.5, specificity > 0.5, area under curve (AUC) > 0.7, and goodness of hit score > 0.7 were retrieved and exploited for the virtual screening. The common hits (87 molecules) obtained from these hypotheses were processed via drug-likeness filters. The filtered molecules (27 molecules) were compared for the binding modes and the top scored molecules (12 molecules) along with the reference (triclosan (TCL), docking score = ?11.65 kcal/mol) were rescored and reprioritized via molecular mechanics-generalized Born surface area approach. Eventually, the stability of reprioritized (10 molecules) docked complexes was scrutinized via molecular dynamics simulations. Moreover, the quantum chemical studies of the dynamically stable compounds (9 molecules) were performed to understand structural features essential for the activity. Overall, the protocol resulted in the recognition of nine lead compounds that can be targeted against InhA.