Identification of natural compound inhibitors against PfDXR: A hybrid structure-based molecular modeling approach and molecular dynamics simulation studies

In the present contribution, multicomplex-based pharmacophore studies were carried out on the structural proteome of Plasmodium falciparum 1-deoxy-D -xylulose-5-phosphate reductoisomerase. Among the constructed models, a representative model with complementary features, accountable for the inhibition was used as a primary filter for the screening of database molecules. Auxiliary evaluations of the screened molecules were performed via drug-likeness and molecular docking studies. Subsequently, the stability of the docked inhibitors was envisioned by molecular dynamics simulations, principle component analysis, and molecular mechanics-Poisson-Boltzmann surface area-based free binding energy calculations. The stability assessment of the hits was done by comparing with the reference (beta-substituted fosmidomycin analog, LC5) to prioritize more potent candidates. All the complexes showed stable dynamic behavior while three of them displayed higher binding free energy compared with the reference. The work resulted in the identification of the compounds with diverse scaffolds, which could be used as initial leads for the design of novel PfDXR inhibitors.     

Multicomplex-based pharmacophore modeling in conjunction with multi-target docking and molecular dynamics simulations for the identification of PfDHFR inhibitors

Abstract

Plasmodium falciparum dihydrofolate reductase enzyme (PfDHFR) is counted as one of the attractive and validated antimalarial drug targets. However, the point mutations in the active site of wild-type PfDHFR have developed resistance against the well-known antifolates. Therefore, there is a dire need for the development of inhibitors that can inhibit both wild-type and mutant-type DHFR enzyme. In the present contribution, we have constructed the common feature pharmacophore models from the available PfDHFR. A representative hypothesis was prioritized and then employed for the screening of natural product library to search for the molecules with complementary features responsible for the inhibition. The screened candidates were processed via drug-likeness filters and molecular docking studies. The docking was carried out on the wild-type PfDHFR (3QGT); double-mutant PfDHFR (3UM5 and 1J3J) and quadruple-mutant PfDHFR (1J3K) enzymes. A total of eight common hits were obtained from the docking calculations that could be the potential inhibitors for both wild and mutant type DHFR enzymes. Eventually, the stability of these candidates with the selected proteins was evaluated via molecular dynamics simulations. Except for SPECS14, all the prioritized candidates were found to be stable throughout the simulation run. Overall, the strategy employed in the present work resulted in the retrieval of seven candidates that may show inhibitory activity against PfDHFR and could be further exploited as a scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma     

Discover potential inhibitors for PFKFB3 using 3D-QSAR,virtual screening,molecular docking and molecular dynamics simulation

Abstract

The 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 (PFKFB3) is a master regulator of glycolysis in cancer cells by synthesizing fructose-2,6-bisphosphate (F-2,6-BP), a potent allosteric activator of phosphofructokinase-1 (PFK-1), which is a rate-limiting enzyme of glycolysis. PFKFB3 is an attractive target for cancer treatment. It is valuable to discover promising inhibitors by using 3D-QSAR pharmacophore modeling, virtual screening, molecular docking and molecular dynamics simulation. Twenty molecules with known activity were used to build 3D-QSAR pharmacophore models. The best pharmacophore model was ADHR called Hypo1, which had the highest correlation value of 0.98 and the lowest RMSD of 0.82. Then, the Hypo1 was validated by cost value method, test set method and decoy set validation method. Next, the Hypo1 combined with Lipinski's rule of five and ADMET properties were employed to screen databases including Asinex and Specs, total of 1,048,159 molecules. The hits retrieved from screening were docked into protein by different procedures including HTVS, SP and XP. Finally, nine molecules were picked out as potential PFKFB3 inhibitors. The stability of PFKFB3-lead complexes was verified by 40?ns molecular dynamics simulation. The binding free energy and the energy contribution of per residue to the binding energy were calculated by MM-PBSA based on molecular dynamics simulation.     

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     

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.     

In silico screening of anti-inflammatory compounds from Lichen by targeting cyclooxygenase-2

Abstract

Non-steroidal anti-inflammatory drugs (NSAID) targeting cyclooxygenase-2 are clinically effective. However, they lack anti-thrombotic activity resulting in incidences of adverse effects like myocardial infarction, gastrointestinal and abdominal discomfort which necessitate for discovering new drug candidates with improved therapeutic effects and tolerability. Various recent researches have suggested that many lichens offer a vast reservoir for anti-inflammatory drug candidates which are natural as well as safe for human consumption. Drug discovery is a very complex and time-consuming process; however, in silico techniques can make this process simple and economic. Hence to find out natural anti-inflammatory compounds, we have carried out the virtual screening of 412 lichen compounds by molecular docking with human Cox-2 enzyme and validated the docking score by X-Score followed by ADMET and Drug-likeness analysis. The resulting 6 top-scored compounds were subjected to Molecular dynamics simulation (MDS) to analyze the stability of docked protein-ligand complex, to assess the fluctuation and conformational changes during protein-ligand interaction. The values of RMSD, Rg, and interaction energy after 30?ns of MDS revealed the good stability of these Lichen compounds in the active site pocket of Cox-2 in compare to reference, JMS. Additionally, we have done the pharmacophore analysis which found many common pharmacophore features between Lichen compounds and well known anti-inflammatory compounds. Our result shows that these lichen compounds are potential anti-inflammatory candidates and could be further modified and evaluated to develop more effective anti-inflammatory drugs with fewer side effects for the treatment of inflammatory diseases.

Communicated by Ramaswamy H. Sarma     

Identification of novel small molecule non-peptidomimetic inhibitor for prolyl oligopeptidase through in silico and in vitro approaches

Abstract

Prolyl oligopeptidase (POP) enzyme has been studied for various disorders, viz. Schizophrenia, Alzheimer’s, Parkinson’s, Depression, Inflammation, etc., for three decades, but no drug has passed through the clinical trials, possibly because of indigent pharmacokinetics. This might have been a result of similar structures of drug candidates. This study aimed at identifying novel small non-peptidomimetic inhibitors for POP enzyme that could serve as a lead for developing newer drugs. Structure-based virtual screening of molecules of MolMall database was conducted on the POP enzyme (PDB ID 3DDU) to identify potential hits. The hits identified were subjected to computational pharmacokinetic screening followed by molecular mechanics/generalized Born and surface area studies to estimate the binding free energy of the docked complexes. After that, nine hits were selected and tested for POP inhibitory activity, among which one compound MM 4 was found to be most potent with EC₅₀ of 100 µM. Compound MM 4 was further subjected to molecular dynamics simulations to study the overall stability of the ligand–protein complex. The compound interacted strongly with catalytic amino acid Arg643 by forming salt and water bridges; it also interacted well with amino acids Phe173, Arg252 and Met235. This study provides a lead molecule for further development of POP inhibitors.

Communicated by Ramaswamy H. Sarma     

Identification of Pak1 inhibitors using water thermodynamic analysis

Abstract

p21-activated kinases (Paks) play an integral component in various cellular diverse processes. The full activation of Pak is dependent upon several serine residues present in the N-terminal region, a threonine present at the activation loop, and finally the phosphorylation of these residues ensure the complete activation of Pak1. The present study deals with the identification of novel potent candidates of Pak1 using computational methods as anti-cancer compounds. A diverse energy based pharmacophore (e-pharmacophore) was developed using four co-crystal inhibitors of Pak1 having pharmacophore features of 5 (DRDRR), 6 (DRHADR), and 7 (RRARDRP and DRRDADH) hypotheses. These models were used for rigorous screening against e-molecule database. The obtained hits were filtered using ADME/T and molecular docking to identify the high affinity binders. These hits were subjected to hierarchical clustering using dendritic fingerprint inorder to identify structurally diverse molecules. The diverse hits were scored against generated water maps to obtain WM/MM ΔG binding energy. Furthermore, molecular dynamics simulation and density functional theory calculations were performed on the final hits to understand the stability of the complexes. Five structurally diverse novel Pak1 inhibitors (4835785, 32198676, 32407813, 76038049, and 32945545) were obtained from virtual screening, water thermodynamics and WM/MM ΔG binding energy. All hits revealed similar mode of binding pattern with the hinge region residues replacing the unstable water molecules in the binding site. The obtained novel hits could be used as a platform to design potent drugs that could be experimentally tested against cancer patients having increased Pak1 expression.     

Insight into the structural requirements of thiophene-3-carbonitriles-based MurF inhibitors by 3D-QSAR,molecular docking and molecular dynamics study

The discovery of clinically relevant inhibitors against MurF enzyme has proven to be a challenging task. In order to get further insight into the structural features required for the MurF inhibitory activity, we performed pharmacophore and atom-based three-dimensional quantitative structure–activity relationship studies for novel thiophene-3-carbonitriles based MurF inhibitors. The five-feature pharmacophore model was generated using 48 inhibitors having IC₅₀ values ranging from 0.18 to 663?μm. The best-fitted model showed a higher coefficient of determination (R²?=?0.978), cross-validation coefficient (Q²?=?0.8835) and Pearson coefficient (0.9406) at four component partial least-squares factor. The model was validated with external data set and enrichment study. The effectiveness of the docking protocol was validated by docking the co-crystallized ligand into the catalytic pocket of MurF enzyme. Further, binding free energy calculated by the molecular mechanics generalized Born surface area approach showed that van der Waals and non-polar solvation energy terms are the main contributors to ligand binding in the active site of MurF enzyme. A 10-ns molecular dynamic simulation was performed to confirm the stability of the 3ZM6-ligand complex. Four new molecules are also designed as potent MurF inhibitors. These results provide insights regarding the development of novel MurF inhibitors with better binding affinity.     

Origins of the specificity of inhibitor P218 toward wild-type and mutant PfDHFR: a molecular dynamics analysis

Molecular dynamics simulations were performed to evaluate the origin of the antimalarial effect of the lead compound P218. The simulations of the ligand in the cavities of wild-type, mutant Plasmodium falciparum Dihydrofolate Reductase (PfDHFR) and the human DHFR revealed the differences in the atomic-level interactions and also provided explanation for the specificity of this ligand toward PfDHFR. The binding free energy estimation using Molecular Mechanics Poisson-Boltzmann Surface Area method revealed that P218 has higher binding affinity (~ ?30 to ?35 kcal/mol) toward PfDHFR (both in wild-type and mutant forms) than human DHFR (~ ?22 kcal/mol), corroborating the experimental observations. Intermolecular hydrogen bonding analysis of the trajectories showed that P218 formed two stable hydrogen bonds with human DHFR (Ile7 and Glu30), wild-type and double-mutant PfDHFR’s (Asp54 and Arg122), while it formed three stable hydrogen bonds with quadruple-mutant PfDHFR (Asp54, Arg59, and Arg122). Additionally, P218 binding in PfDHFR is stabilized by hydrogen bonds with residues Ile14 and Ile164. It was found that mutant residues do not reduce the binding affinity of P218 to PfDHFR, in contrast, Cys59Arg mutation strongly favors inhibitor binding to quadruple-mutant PfDHFR. The atomistic-level details explored in this work will be highly useful for the design of non-resistant novel PfDHFR inhibitors as antimalarial agents.     

Pharmacoinformatics-based identification of chemically active molecules against Ebola virus

Abstract

Ebola is a dangerous virus transmitted by animals and humans and to date there is no curable agent for such a deadly infectious disease. In this study, pharmacoinformatics-based methods were adopted to find effective novel chemical entities against Ebola virus. A well predictive and statistical robust pharmacophore model was developed from known Ebola virus inhibitors collected from the literature. The model explained the significance of each of hydrogen bond acceptor and donor, and two hydrophobic regions for activity. The National Cancer Institute and Asinex (Antiviral library) databases were screened using the final validated pharmacophore model. Initial hits were further screened with a set of criteria and finally eight molecules from both databases were proposed as promising anti Ebola agents. Further molecular docking and molecular dynamics studies were carried out and it was found that the proposed molecules possessed capability to interact with amino residues of Ebola protein as well as retaining equilibrium of protein-ligand systems. Finally, the binding energies were calculated using molecular mechanics Poisson–Boltzmann surface area approach and all proposed molecules showed strong binding affinity towards the Ebola protein receptor.

Communicated by Ramaswamy H. Sarma     

Designing of benzothiazole derivatives as promising EGFR tyrosine kinase inhibitors: a pharmacoinformatics study

Abstract

Benzothiazole derivatives represent an important class of therapeutic chemical agents and are widely used for interesting biological activities and therapeutic functions including anticancer, antitumor and antimicrobial. In this study, we have performed similarity/substructure-based search of eMolecule database to find out promising benzothiazole derivatives as EGFR tyrosine kinase inhibitors. Several screening criteria that included molecular docking, pharmacokinetics and synthetic accessibility were used on initially derived about 7000 molecules consisting of benzothiazole as major component. Finally, four molecules were found to be promising EGFR tyrosine kinase inhibitors. The best docked pose of each molecule was considered for binding interactions followed by molecular dynamics (MD) and binding energy calculation. Molecular docking clearly showed the final proposed derivatives potential to form a number of binding interactions. MD simulation trajectories undoubtedly indicated that the EGFR protein becomes stable when proposed derivatives bind to the receptor cavity. Strong binding affinity was found for all molecules toward the EGFR which was substantiated by the binding energy calculation using the MM-PBSA approach. Therefore, proposed benzothiazole derivatives may be promising EGFR tyrosine kinase inhibitors for potential application as cancer therapy.

Communicated by Ramaswamy H. Sarma     

Pharmacophore based 3D-QSAR modeling and free energy analysis of VEGFR-2 inhibitors

VEGFR-2, a transmembrane tyrosine kinase receptor is responsible for angiogenesis and has been an attractive target in treating cancers. The inhibition mechanism of structurally diverse urea derivatives, reported as VEGFR-2 inhibitors, was explored by pharmacophore modeling, QSAR, and molecular dynamics based free energy analysis.The pharmacophore hypothesis AADRR, resulted in a highly significant atom based 3D-QSAR model (r² = 0.94 and q² = 0.84). Binding free energy analysis of the docked complexes of highly active and inactive compounds, after 7 ns MD simulation, revealed the importance of van der Waals interaction in VEGFR-2 inhibition. The decomposition of binding free energy on a per residue basis disclosed that the residues in hinge region and hydrophobic pocket play a role in discriminating the active and inactive inhibitors. Thus, the present study proposes a pharmacophore hypothesis representing the identified interactions pattern and its further application as a template in screening databases to identify novel VEGFR-2 inhibitor scaffolds.     

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.     

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.     

Identification of potential inhibitors of Fasciola gigantica thioredoxin1: computational screening,molecular dynamics simulation,and binding free energy studies

Fasciola gigantica is the causative organism of fascioliasis and is responsible for major economic losses in livestock production globally. F. gigantica thioredoxin1 (FgTrx1) is an important redox-active enzyme involved in maintaining the redox homeostasis in the cell. To identify a potential anti-fasciolid compound, we conducted a structure-based virtual screening of natural compounds from the ZINC database (n = 1,67,740) against the FgTrx1 structure. The ligands were docked against FgTrx1 and 309 ligands were found to have better docking score. These compounds were evaluated for Lipinski and ADMET prediction, and 30 compounds were found to fit well for re-docking studies. After refinement by molecular docking and drug-likeness analysis, three potential inhibitors (ZINC15970091, ZINC9312362, and ZINC9312661) were identified. These three ligands were further subjected to molecular dynamics simulation (MDS) to compare the dynamics and stability of the protein structure after binding of the ligands. The binding free energy analyses were calculated to determine the intermolecular interactions. The results suggested that the two compounds had a binding free energy of –82.237, and –109.52 kJ.mol^?1 for compounds with IDs ZINC9312362 and ZINC9312661, respectively. These predicted compounds displayed considerable pharmacological and structural properties to be drug candidates. We concluded that these two compounds could be potential drug candidates to fight against F. gigantica parasites.     

Synthesis,molecular docking,binding free energy calculation and molecular dynamics simulation studies of benzothiazol-2-ylcarbamodithioates as Staphylococcus aureus MurD inhibitors

Abstract

A new series of benzothiazol-2-ylcarbamodithioate functional compounds 5a-f has been designed, synthesized and characterized by spectral data. These compounds were screened for their in vitro antibacterial activity against strains of Staphylococcus aureus (NCIM 5021, NCIM 5022 and methicillin-resistant isolate 43300), Bacillus subtilis (NCIM 2545), Escherichia coli (NCIM 2567), Klebsiella pneumoniae (NCIM 2706) and Psudomonas aeruginosa (NCIM 2036). Compounds 5a and 5d exhibited significant activity against all the tested bacterial strains. Specifically, compounds 5a and 5d showed potent activity against K. pneumoniae (NCIM 2706), while compound 5a also displayed potent activity against S. aureus (NCIM 5021). Compound 5d showed minimum IC₅₀ value of 13.37?μM against S. aureus MurD enzyme. Further, the binding interactions of compounds 5a-f in the catalytic pocket have been investigated using the extra-precision molecular docking and binding free energy calculation by MM-GBSA approach. A 30?ns molecular dynamics simulation of 5d/modeled S. aureus MurD enzyme was performed to determine the stability of the predicted binding conformation.