Docking and molecular dynamics studies of new potential inhibitors of the human epidermal receptor 2

Compounds similar to lapatinib and gefitinib have been investigated as potential inhibitors of the intracellular receptor tyrosine kinase (RTK) domain of the human epidermal receptor 2 (HER2), which is a promising molecular target to the drug design of new chemotherapies for breast, lung, ovarian and colorectal cancers. In this study, we have searched potential HER2 inhibitors used for treatment of other illnesses such as hepatitis, bacterial infections and sexual impotence screened in the DrugBank. The compounds selected were subjected to virtual screening docking in order to evaluate the main interactions between them and the RTK domain of HER2. The selected compounds were investigated by flexible docking, molecular dynamics studies and ΔG _bind calculations. The results suggest that antrafenine, saprisartan, reserpine, irinotecan and udenafil are potential candidates to inhibit the RTK domain of HER2.     

3D QSAR pharmacophore-based virtual screening for the identification of potential inhibitors of tyrosinase

Abstract

Tyrosinase plays an important role in melanin biosynthesis and protects skin against ultraviolet radiations. Functional deficiency of tyrosinase results in serious dermatological diseases. Tyrosinase also participates in neuromelanin formation in the human brain, which leads to neurodegeneration resulting in Parkinson’s disease. In fruits and vegetables, tyrosinase plays a critical role in senescence, causing undesired browning that results in faster deterioration and shorter shelf lines. The only commercially available tyrosinase is mushroom tyrosinase and it shows the highest homology to the mammalian tyrosinase. Although kojic acid is currently used as a tyrosinase inhibitor, they have serious side effects such as dermatitis, carcinogenesis and hepatotoxicity. Therefore, in order to develop a more active and safer tyrosinase inhibitor, 3D QSAR pharmacophore models were generated based on experimentally known inhibitors. The pharmacophore model, Hypo1, was developed with a large cost difference, high correlation coefficient and low RMS deviation. Hypo1 showed a good spatial arrangement; consisting of five-point features including two hydrogen bond acceptor, one hydrogen bond donor and two hydrophobic features. Hypo1 was further validated by cost analysis, test set and Fisher’s randomisation method. Hypo1 was used as a 3D query for screening the in-house drug-like databases, and the hits were further selected by applying ADMET, Lipinski’s rule of five and fit value criteria. To identify binding conformations, the obtained hits were subjected to molecular docking. Finally, molecular dynamics simulations revealed the appropriate binding modes of hit compounds. To conclude, we propose the final three hit compounds with new structural scaffolds as a virtual candidate as tyrosinase inhibitors.

Communicated by Ramaswamy H. Sarma     

New potential inhibitors of mTOR: a computational investigation integrating molecular docking,virtual screening and molecular dynamics simulation

The mTOR (mammalian or mechanistic Target Of Rapamycin), a complex metabolic pathway that involves multiple steps and regulators, is a major human metabolic pathway responsible for cell growth control in response to multiple factors and that is dysregulated in various types of cancer. The classical inhibition of the mTOR pathway is performed by rapamycin and its analogs (rapalogs). Considering that rapamycin binds to an allosteric site and performs a crucial role in the inhibition of the mTOR complex without causing the deleterious side effects common to ATP-competitive inhibitors, we employ ligand-based drug design strategies, such as virtual screening methodology, computational determination of ADME/Tox properties of selected molecules, and molecular dynamics in order to select molecules with the potential to become non-ATP-competitive inhibitors of the mTOR enzymatic complex. Our findings suggest five novel potential mTOR inhibitors, with similar or better properties than the classic inhibitor complex, rapamycin.     

Homology modeling of human histone deacetylase 10 and design of potential selective inhibitors

Abstract

Histone deacetylases (HDACs) are implicated in the pathology of various cancers, and their pharmacological blockade has proven to be promising in reversing the malignant phenotypes. However, lack of crystal structures of some of the human HDAC isoforms (e.g., HDAC10) hinders the design of the isoform-selective inhibitor. Here, the recently solved X-ray crystal structure of Danio rerio (zebrafish) HDAC10 (Protein Data Bank (PDB) ID; 5TD7, released on 24 May 2017) was retrieved from the PDB and used as a template structure to model the three-dimensional structure of human HDAC10. The overall quality of the best model (M0017) was assessed by computing its z-score—a measure of the deviation of the total energy of the structure with respect to an energy distribution derived from random conformations and by docking of known HDAC10 inhibitors to its catalytic cavity. Furthermore, to identify potential HDAC10-selective inhibitor ligand-based virtual screening was carried out against the ZINC database. The free modeled structure of HDAC10 and its complexes with quisinostat and the highest-ranked compound ZINC19749069 were submitted to molecular dynamics simulation. The comparative analysis of root-mean-squared deviation, root-mean-squared fluctuation, radius of gyration (Rg), and potential energy of these systems showed that HDAC10-ZINC19749069 complex remained the most stable over time. Thus, M0017 could be potentially used for structure-based inhibitor against HDAC10, and ZINC19749069 may provide a scaffold for further optimization.

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.     

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     

Virtual screening,docking, and dynamics of potential new inhibitors of dihydrofolate reductase from Yersinia pestis

In the present work, we propose to design drugs that target the enzyme dihydrofolate redutase (DHFR) as a means of a novel drug therapy against plague. Potential inhibitors of DHFR from Yersinia pestis (YpDHFR) were selected by virtual screening and subjected to docking, molecular dynamics (MD) simulations, and Poisson–Boltzmann surface area method, in order to evaluate their interactions in the active sites of YpDHFR and human DHFR (HssDHFR). The results suggested selectivity for three compounds that were further used to propose the structures of six new potential selective inhibitors for YpDHFR.     

Identification of potential tumour-associated carbonic anhydrase isozyme IX inhibitors: atom-based 3D-QSAR modelling,pharmacophore-based virtual screening and molecular docking studies

Abstract

Tumour hypoxia results in dramatic changes in the gene expression, proliferation and survival of tumour cells. The tumour cells shift towards anaerobic glycolysis which results in change of pH in their microenvironment. In response to this stress, over expression of carbonic anhydrase IX (CA IX) genes is observed in many solid tumours. So, selective inhibition of CA IX can be a promising target for anti-cancer drugs. In this work in silico tools like atom-based 3D-QSAR modelling, pharmacophore-based virtual screening and molecular docking were used to identify potential CA IX inhibitors. Based on the training set used in the QSAR model, twenty pharmacophore models were generated. Out of these, HHHR_1, AHHR_1, DHHHR_1, AHHHR_1 model was used to screen a database of 1,50,000 compounds retrieved from ZINC 15 database. R² and Q² was 0.9864 and 0.8799, respectively, for the developed QSAR model. 163 compounds showed a phase screen score above 2.4 in which ZINC02260669 was the highest ranked (screen score, 2.852058) compound in all the four models. Built QSAR model was used to predict the activity of all these 163 compounds and ZINC72370966 showed the highest predicted activity with pKi value of 7.649. These compounds were docked against CA IX (human) protein (PDB ID 5FL6) and molecular docking results showed favourable binding interactions for the best ten identified hits. This work gives design insights and some potential scaffolds which can be developed as CA IX inhibitors.

Communicated by Ramaswamy H. Sarma     

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, ¹H-NMR, ¹³C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.     

Identification of peptidomimetic compounds as potential inhibitors against MurA enzyme of Mycobacterium tuberculosis

Abstract

Increasing prevalence of resistance to anti-tubercular drugs has become the foremost challenge now. According to WHO, over half a million of multidrug resistance cases (rifampicin, isoniazid, etc.) were reported in 2017, mostly emerging from countries such as China, India, and Russia. Therefore, developing new drugs or repurposing existing ones is need of the hour. The Mycobacterium cell wall biogenesis pathway offers many attractive targets for drug discovery against Tuberculosis (TB). MurA, a transferase enzyme that catalyzes the initial step of peptidoglycan (PG) biosynthesis, is one among them. A peptidoglycan layer resides over the plasma membrane and is an integral component of the bacterial cell wall. Therefore, disruption of their formation through inhibition of MurA enzyme should lead to deficiency in Mycobacterium cell synthesis. Based on this strategy, we have designed this study where two libraries of peptidomimetic compounds (Asinex & ChemDiv) were first screened against our modeled MurA structure and then validated through molecular dynamic simulations. From our virtual screening, top four compounds (ChemDiv: D675-0102, D675-0217; Asinex: BDE25373574, BDE 26717803) were selected based on their docking scores, binding energies, and interactions with catalytic site residues, for further evaluation. Results revealed stable ligand-MurA interactions throughout 50?ns of MD simulation and also druggability acceptable pharmacokinetic profile for all four compounds. Thus, based on our findings, these compounds could be considered as potential inhibitors of Mycobacterium MurA enzyme and hence be further tested for in vitro experimental validation as TB therapeutic drug candidate.

Communicated by Ramaswamy H. Sarma     

In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.     

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM,pharmacophore and docking model

Abstract

Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF) pharmacophore and docking was utilised for screening the CDK2 inhibitors. The evaluation of the validation set indicated that this method can be used to screen large chemical databases because it has a high hit-rate and enrichment factor (80.1% and 332.83 respectively). Six compounds were screened out from NCI, Enamine and Pubchem database. After molecular dynamics and binding free energy calculation, two compounds had great potential as novel CDK2 inhibitors and they also showed selective inhibition against CDK2 in the kinase activity assay.     

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.     

Analysis of non-peptidic compounds as potential malarial inhibitors against Plasmodial cysteine proteases via integrated virtual screening workflow

Falcipain-2 (FP-2) and falcipain-3 (FP-3), haemoglobin-degrading enzymes in Plasmodium falciparum, are validated drug targets for the development of effective inhibitors against malaria. However, no commercial drug-targeting falcipains has been developed despite their central role in the life cycle of the parasites. In this work, in silico approaches are used to identify key structural elements that control the binding and selectivity of a diverse set of non-peptidic compounds onto FP-2, FP-3 and homologues from other Plasmodium species as well as human cathepsins. Hotspot residues and the underlying non-covalent interactions, important for the binding of ligands, are identified by interaction fingerprint analysis between the proteases and 2-cyanopyridine derivatives (best hits). It is observed that the size and chemical type of substituent groups within 2-cyanopyridine derivatives determine the strength of protein–ligand interactions. This research presents novel results that can further be exploited in the structure-based molecular-guided design of more potent antimalarial drugs.     

Virtual screening,molecular dynamics,and binding free energy calculations on human carbonic anhydrase IX catalytic domain for deciphering potential leads

Carbonic anhydrase IX is a tumor-associated membrane-bound metallo-enzyme which catalyzes the reversible hydration of carbon dioxide (CO₂) to bicarbonate (HCO₃^?) and proton (H⁺) ions. It is a hypoxia-inducible enzyme and plays a critical role in tumor pH homeostasis favoring tumor cell invasiveness and drug resistance. Over expression of CAIX is documented in cancers of breast, lung, kidney, colon/rectum, etc. Chemical inhibition of CAIX activity has proven to be an effective therapeutic modality towards targeting cancer. Hence, in this study, we intend to identify potential molecules from NCI (National Cancer Institute) and Maybridge databases implementing high-throughput virtual screening. CAIX co-crystallized with acetazolamide (a known inhibitor of CAIX) (PDB ID: 3IAI) was used for reference-guided docking protocol. The potential inhibitors among the coupled data sets were finalized based on Glide docking score, Prime/MMGBSA scoring, significant intermolecular interactions, ADMET (absorption, distribution, metabolism and excretion, toxicity) prediction and stability of complex formation, molecular dynamics simulation, and comparative analysis. By this study, we propose NSC_93618, NSC_170253, NSC_93618, JFD03677, SEW06488, and BTB09372 to be highly significant, as all these compounds were found to qualify as potential leads surpassing all the stringent filtering process. However, NSC_93618 was found to be the most potential, as it featured with higher complex stability with strong bonded interactions, binding affinity synonymous to acetazolamide. Hence, these proposed compounds shall prove to be effective in targeting CAIX towards modulating carcinogenesis.     

An in silico approach towards the identification of novel inhibitors of the TLR-4 signaling pathway

Precise functioning and fine-tuning of Toll-like receptor 4 (TLR4) signaling is a critical requirement for the smooth functioning of the innate immune system, since aberrant TLR4 activation causes excessive production of pro-inflammatory cytokines and interferons. This can result in life threatening conditions such as septic shock and other inflammatory disorders. The TRIF-related adaptor molecule (TRAM) adaptor protein is unique to the TLR4 signaling pathway and abrogation of TRAM-mediated TLR4 signaling is a promising strategy for developing therapeutics aimed at disrupting TRAM interactions with other components of the TLR4 signaling complex. The VIPER motif from the vaccinia virus-producing protein, A46 has been reported to disrupt TRAM-TLR4 interactions. We have exploited this information, in combination with homology modeling and docking approaches, to identify a potential binding site on TRAM lined by the BB loop and αC helix. Virtual screening of commercially available small molecules targeting the binding site enabled to short-list 12 small molecules to abrogate TRAM-mediated TLR4 signaling. Molecular dynamics and molecular mechanics calculations have been performed for the analysis of these receptor-ligand interactions.     

Design of novel lead molecules against RhoG protein as cancer target – a computational study

Cancer is a class of diseases characterized by uncontrolled cell growth. Every year more than 2 million people are affected by the disease. Rho family proteins are actively involved in cytoskeleton regulation. Over-expression of Rho family proteins show oncogenic activity and promote cancer progression. In the present work RhoG protein is considered as novel target of cancer. It is a member of Rho family and Rac subfamily protein, which plays pivotal role in regulation of microtubule formation, cell migration and contributes in cancer progression. In order to understand the binding interaction between RhoG protein and the DH domain of Ephexin-4 protein, the 3D structure of RhoG was evaluated and Molecular Dynamic Simulations was performed to stabilize the structure. The 3D structure of RhoG protein was validated and active site identified using standard computational protocols. Protein–protein docking of RhoG with Ephexin-4 was done to understand binding interactions and the active site structure. Virtual screening was carried out with ligand databases against the active site of RhoG protein. The efficiency of virtual screening is analysed with enrichment factor and area under curve values. The binding free energy of docked complexes was calculated using prime MM-GBSA module. The SASA, FOSA, FISA, PISA and PSA values of ligands were carried out. New ligands with high docking score, glide energy and acceptable ADME properties were prioritized as potential inhibitors of RhoG protein.     

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r?=?0.96) and Fisher’s randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski’s rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.     

A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors

A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors.