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.     

Docking based virtual screening and molecular dynamics study to identify potential monoacylglycerol lipase inhibitors

Monoacylglycerol lipase (MAGL) is one of the key enzymes of the endocannabinoid system (ECS). It hydrolyzes one of the major endocannabinoid, 2-arachidonoylglycerol (2-AG), an endogenous full agonist at G protein coupled cannabinoid receptors CB1 and CB2. Numerous studies showed that MGL inhibitors are potentially useful for the treatment of pain, inflammation, cancer and CNS disorders. These provocative findings suggested that pharmacological inhibition of MAGL function may confer significant therapeutic benefits. In this study, we presented hybrid ligand and structure-based approaches to obtain a novel set of virtual leads as MAGL inhibitors. The constraints used in this study, were Glide score, binding free energy estimates and ADME properties to screen the ZINC database, containing approximately 21 million compounds. A total of seven virtual hits were obtained, which showed significant binding affinity towards MAGL protein. Ligand, ZINC24092691 was employed in complex form with the protein MAGL, for molecular dynamics simulation study, because of its excellent glide score, binding free energy and ADME properties. The RMSD of ZINC24092691 was observed to stay at 0.1 nm (1 Å) in most of the trajectories, which further confirmed its ability to inhibit the protein MAGL. The hits were then evaluated for their ability to inhibit human MAGL. The compound ZINC24092691 displayed the noteworthy inhibitory activity reducing MAGL activity to 21.15% at 100 nM concentration, with an IC₅₀ value of 10 nM.     

High throughput screening,docking, and molecular dynamics studies to identify potential inhibitors of human calcium/calmodulin-dependent protein kinase IV

Calcium/calmodulin-dependent protein kinase IV (CAMKIV) is associated with many diseases including cancer and neurodegenerative disorders and thus being considered as a potential drug target. Here, we have employed the knowledge of three-dimensional structure of CAMKIV to identify new inhibitors for possible therapeutic intervention. We have employed virtual high throughput screening of 12,500 natural compounds of Zinc database to screen the best possible inhibitors of CAMKIV. Subsequently, 40 compounds which showed significant docking scores (?11.6 to ?10.0?kcal/mol) were selected and further filtered through Lipinski rule and drug likeness parameter to get best inhibitors of CAMKIV. Docking results are indicating that ligands are binding to the hydrophobic cavity of the kinase domain of CAMKIV and forming a significant number of non-covalent interactions. Four compounds, ZINC02098378, ZINC12866674, ZINC04293413, and ZINC13403020, showing excellent binding affinity and drug likeness were subjected to molecular dynamics simulation to evaluate their mechanism of interaction and stability of protein-ligand complex. Our observations clearly suggesting that these selected ligands may be further employed for therapeutic intervention to address CAMKIV associated diseases.

Communicated by Ramaswamy H. Sarma     

Screening from TCM Database@Taiwan and QSAR model for identifying HER2 inhibitors

Human epidermal growth factor receptor type 2 (HER2) overexpression, which has been reported to increase the malignancy of human ovarian cancer cells and the metastatic potential of human breast cancer cells, is an important factor in tumour formation and tumour growth. However, currently available HER2 inhibitors, such as Lapatinib, for cancer therapy cause adverse side effects including diarrhoea, rash and possible liver toxicity. We hoped to find novel agents that cause less adverse side effects by performing virtual screening process on the world's largest traditional Chinese medicine compound database. The results thus obtained were then validated using 3D quantitative structure–activity relationship model. Top three candidates were selected from the docking results. The top three candidates and the control both formed a hydrogen bond with the key residue, Lys724. This showed that the candidates and the control have similar binding effects to HER2. These candidates were investigated using comparative molecular field analysis and comparative molecular similarity indices analysis models. The results from these models showed high correlation coefficients (r ²) of 0.9547 and 0.9226, respectively. All top three candidates had high docking scores, favourable pharmacophores and functional groups forming stable hydrogen bonds with HER2. These properties suggested stable binding affinities and favourable interaction with HER2. We concluded that these candidates may be further investigated as potential HER2 inhibitors.     

Focused screening to identify new adenosine kinase inhibitors

Adenosine kinase (AdK) is a key player in controlling intra- and extracellular concentrations of the signaling molecule adenosine. Extensive evidence points to an important role of AdK in several diseases, and suggests that AdK inhibition might be a promising therapeutic strategy.The development of a new AdK assay and subsequent screening of part of our focused compound library led to the identification of 12 hit compounds (hit rate of 6%) representing six new classes of non-nucleoside human AdK inhibitors. The most potent inhibitor 1 displayed a K_i value of 184 nM. Compound screening with a newly developed assay was useful and efficient for discovering novel AdK inhibitors which may serve as lead structures for developing drugs for adenosine augmentation therapy.     

Pharmacophore based virtual screening,molecular docking and biological evaluation to identify novel PDE5 inhibitors with vasodilatory activity

Prompted by the role of PDE5 and its closely associated cAMP and cGMP in hypertension, we have attempted to discover novel PDE5 inhibitors through ligand based virtual screening. Rigorously validated model comprising of one HBA, one HY and one RA was used as a query to search the NCI database leading to retrieval of many compounds which were screened on the basis of estimated activity, fit value and Lipinski’s violation. Selected compounds were subjected to docking studies which resulted into visualization of potential interaction capabilities of NCI compounds in line to pharmacophoric features. Finally three compounds were subjected to in vitro evaluation using the isolated rat aortic model. The results showed that all three compounds are potent and novel PDE5 inhibitors with vasodilatory activity range from 10⁻² to 10⁻⁵ M.     

Pharmacophore modeling and molecular dynamics approach to identify putative DNA Gyrase B inhibitors for resistant tuberculosis

One of the major mechanisms followed by the therapeutic agents to target the causative organism of TB, mycobacterium tuberculosis (Mtb), involves disruption of the replication cycle of the pathogen DNA. The process involves two steps that occur simultaneously, ie, breakage and reunion of DNA at gyrase A (GyrA) domain and ATP hydrolysis at gyrase B (GyrB) domain. Current therapy for multi-drug resistant TB involves FDA approved, Fluoroquinolone-based antibiotics, which act by targeting the replication process at GyrA domain. However, resistance against fluoroquinolones due to mutations in the GyrA domain has limited the use of this therapy and shifted the focus of the research community on the GyrB domain. Thus, this study involves in silico designing of chemotherapeutic agents for resistant TB by targeting GyrB domain. In the current study, a pharmacophore model for GyrB domain was generated using reported inhibitors. It was utilized as a query search against three commercial databases to identify GyrB domain inhibitors. Additionally, a qualitative Hip-Hop pharmacophore model for GyrA was also developed on the basis of some marketed fluoroquinolone-based GyrA inhibitors, to remove non-selective gyrase inhibitors obtained in virtual screening. Further, molecular dynamic simulations were carried out to determine the stability of the obtained molecules in complex with both the domains. Finally, Molecular mechanics with generalized Born and surface area solvation score was calculated to determine the binding affinity of obtained molecule with both domains to determine the selectivity of the obtained molecules that resulted in seven putative specific inhibitors of GyrB domain.     

Drug discovery for DNA break repair system by screening from TCM database and molecular dynamics approach

In search for novel anti-tumour agents targeting non-homologous end joining pathway, we conducted a virtual screening using traditional Chinese medicine (TCM) on Ku heterodimer which plays an important role on DNA break repair system. Docking results gave glycyrrhizic acid and macedonoside C as potential TCM candidates. Both glycyrrhizic acid and macedonoside C were docked onto the Ku heterodimer with high-predicted binding affinities as evidenced in their Dock Score. These two ligands also interact with key residues which have been previously shown to influence Ku DNA-binding affinity. Both compounds show consistent hydrogen bonding interactions with key residues throughout the 10- ns dynamics simulation run. Furthermore, glycyrrhizic acid and macedonoside C are able to form additional hydrogen bond interactions with positively charged Ku heterodimer surface. Such interactions strengthen the binding interaction of the top two TCM compounds with Ku heterodimer. Glycyrrhizic acid and macedonoside C are products of licorice (Glycyrrhiza glabra), which is a commonly used herb in TCM formulations. Overall, we report glycyrrhizic acid and macedonoside C as potential anti-tumour agents.     

Potent inhibitor design against H1N1 swine influenza: structure-based and molecular dynamics analysis for M2 inhibitors from traditional Chinese medicine database

The rapid spread of influenza virus subtype H1N1 poses a great threat to million lives worldwide. To search for new anti-influenza compounds, we performed molecular docking and molecular dynamics simulation to identify potential traditional Chinese medicine (TCM) constituents that could block influenza M2 channel activity. Quinic acid, genipin, syringic acid, cucurbitine, fagarine, and methyl isoferulate all have extremely well docking results as compared to control amantadine. Further de novo drug design suggests that derivatives of genipin and methyl isoferulate could have enhanced binding affinity towards M2 channel. Selected molecular dynamics simulations of M2-derivative complexes show stable hydrogen bond interactions between the derivatives and M2 residues, Ser10 and Ala9. To our best knowledge, this is the first study on the anti-viral activity of the above listed TCM compounds.     

In silico identification and screening of CYP24A1 inhibitors: 3D QSAR pharmacophore mapping and molecular dynamics analysis

Vitamin D is a key signalling molecule that plays a vital role in the regulation of calcium phosphate homeostasis and bone remodelling. The circulating biologically active form of vitamin D is regulated by the catabolic mechanism of cytochrome P450 24-hydroxylase (CYP24A1) enzyme. The over-expression of CYP24A1 negatively regulates the vitamin D level, which is the causative agent of chronic kidney disease, osteoporosis and several types of cancers. In this study, we found three potential lead molecules adverse to CYP24A1 through structure-based, atom-based pharmacophore and e-pharmacophore-based screening methods. Analysis was done by bioinformatics methods and tools like binding affinity (binding free energy), chemical reactivity (DFT studies) and molecular dynamics simulation (protein–ligand stability). Combined computational investigation showed that the compounds NCI_95001, NCI_382818 and UNPD_141613 may have inhibitory effects against the CYP24A1 protein.     

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.     

Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors

Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC(50) values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer's randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.     

Pharmacophore modeling and virtual screening to identify potential RET kinase inhibitors

Chemical features based 3D pharmacophore model for REarranged during Transfection (RET) tyrosine kinase were developed by using a training set of 26 structurally diverse known RET inhibitors. The best pharmacophore hypothesis, which identified inhibitors with an associated correlation coefficient of 0.90 between their experimental and estimated anti-RET values, contained one hydrogen-bond acceptor, one hydrogen-bond donor, one hydrophobic, and one ring aromatic features. The model was further validated by a testing set, Fischer’s randomization test, and goodness of hit (GH) test. We applied this pharmacophore model to screen NCI database for potential RET inhibitors. The hits were docked to RET with GOLD and CDOCKER after filtering by Lipinski’s rules. Ultimately, 24 molecules were selected as potential RET inhibitors for further investigation.     

Ligand-based and structure-based virtual screening to identify carbonic anhydrase IX inhibitors

A three-dimensional pharmacophore model of CA IX inhibitors was generated and used to screen the ZINC database of commercially available compounds. The hits were docked in a CA IX homology model. By visualizing the binding mode and score of these compounds, six derivatives were selected and evaluated for their inhibitory potency against CA IX. A highly active CA IX inhibitor was identified which may be used as a lead to design novel such derivatives.     

Combined structure- and ligand-based pharmacophore modeling and molecular dynamics simulation studies to identify selective inhibitors of MMP-8

Matrix metalloproteinase-8 (MMP-8) is the key mediator in initiating type I collagen degradation and is associated with rheumatoid arthritis. In the present study, a pharmacophore hypothesis was developed based on selective non zinc binding inhibitors of MMP-8. The pharmacophore hypothesis was refined manually and validated by observing structures and the interactions of MMP-8 inhibitors. The refined pharmacophore model was able to discriminate the non-zinc binding inhibitors of MMP-8 with respect to other inhibitors. Hence this study proposes a combined structure- and ligand-based pharmacophore model that is suitable for retrieving the novel inhibitors of MMP-8. The pharmacophore hypothesis AADRH was used as query for retrieving potential compounds from the Zinc database and hits were selected based on the catalytic selective amino acid residues of Arg 222, and Tyr 227. We identified six compounds as potent inhibitors and their selectivity profile were checked against different subtypes of MMPs using the cross-docking method. Molecular dynamics results indicated that ZINC 00673680 forms a stable interaction with the key amino acid residues and avoids the zinc atom with a distance of 5.49?Å. Our computational study might be useful for further development of selective MMP-8 inhibitors.     

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.     

Structure based virtual screening, 3D-QSAR,molecular dynamics and ADMET studies for selection of natural inhibitors against structural and non-structural targets of Chikungunya

The transmission of mosquito-borne Chikungunya virus (CHIKV) has large epidemics worldwide. Till date, there are neither anti-viral drugs nor vaccines available for the treatment of Chikungunya. Accumulated evidences suggest that some natural compounds i.e., Epigallocatechin gallate, Harringtonine, Apigenin, Chrysin, Silybin, etc. have the capability to inhibit CHIKV replication in vitro. Natural compounds are known to possess less or no side effects. Therefore, natural compound in its purified or crude extracts form could be the preeminent and safe mode of therapies for Chikungunya. Wet lab screening and identification of natural compounds against Chikungunya targets is a time consuming and expensive exercise. In the present study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), Three Dimensional Quantitative Structure Activity Relation (3D-QSAR) and ADME properties to screen out potential compounds. Aim of the study is to identify potential lead/s from natural sources using in silico techniques that can be developed as a drug like molecule against Chikungunya infection and replication. Three softwares were used for molecular docking studies. Potential ligands selected by docking studies were subsequently subjected 3D-QSAR studies to predict biological activity. Based on docking scores and pIC₅₀ value, potential anti-Chikungunya compounds were identified. Best docked receptor-ligands were also subjected to MD for more accurate estimation. Lipinski’s rule and ADME studies of the identified compounds were also studied to assess their drug likeness properties. Results of in silico findings, led to identification of few best fit compounds of natural origin against targets of Chikungunya virus which may lead to discovery of new drugs for Chikungunya.

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.     

A molecular dynamics analysis of protein structural elements

The relation between protein secondary structure and internal motions was examined by using molecular dynamics to calculate positional fluctuations of individual helix, beta-sheet, and loop structural elements in free and substrate-bound hen egg-white lysozyme. The time development of the fluctuations revealed a general correspondence between structure and dynamics; the fluctuations of the helices and beta-sheets converged within the 101 psec period of the simulation and were lower than average in magnitude, while the fluctuations of the loop regions were not converged and were mostly larger than average in magnitude. Notable exceptions to this pattern occurred in the substrate-bound simulation. A loop region (residues 101-107) of the active site cleft had significantly reduced motion due to interactions with the substrate. Moreover, part of a loop and a 3(10) helix (residues of 67-88) not in contact with the substrate showed a marked increase in fluctuations. That these differences in dynamics of free and substrate-bound lysozyme did not result simply from sampling errors was established by an analysis of the variations in the fluctuations of the two halves of the 101 psec simulation of free lysozyme. Concerted transitions of four to five mainchain phi and psi angles between dihedral wells were shown to be responsible for large coordinate shifts in the loops. These transitions displaced six or fewer residues and took place either abruptly, in 1 psec or less, or with a diffusive character over 5-10 psec. Displacements of rigid secondary structures involved longer timescale motions in bound lysozyme; a 0.5 A rms change in the position of a helix occurred over the 55 psec simulation period. This helix reorientation within the protein appears to be a response to substrate binding. There was little correlation between the solvent accessible surface area and the dynamics of the different structural elements.