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.     

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.     

Discovery of Potent ALK Inhibitors Using Pharmacophore-Informatics Strategy

Anaplastic lymphoma kinase is a tyrosine kinase receptor protein belonging to insulin receptor superfamily. Gene fusions in anaplastic lymphoma kinase are associated with non-small cell lung cancer development. Hence, they are of immense importance in targeted therapies. Thus, for the treatment of non-small cell lung cancer, effective anaplastic lymphoma kinase inhibitors are of great significance. Therefore, our objective is to find hit compounds that could have better inhibitory activity than the existing anaplastic lymphoma kinase inhibitors. Keeping this in mind, in the present study pharmacophore based virtual screening was performed to identify possible anaplastic lymphoma kinase inhibitors. Initially, a five-point common pharmacophore hypothesis was generated based on twelve anaplastic lymphoma kinase inhibitors using PHASE module of Schrödinger. Subsequently, common pharmacophore hypothesis-based screening was conducted against in-trials subset of ZINC database and a total of 1000 hits were identified. The molecules obtained were further screened by three stages of docking using GLIDE software. The docking results reveal that six hit molecules showed higher glide score in comparison with the reference molecules. Finally, pharmacokinetic properties of the hit molecules were also analysed using QikProp programme. The results indicate that molecules namely videx, dexecadotril, chloramphenicol, naficillin were found to have good pharmacokinetic properties and human oral absorption. Moreover, videx, naficillin and chloramphenicol were found to have significant inhibitory activity for mutant (F1174L) anaplastic lymphoma kinase. It was also found that videx exhibited crucial interactions with the Met1199 residue of the native and mutant anaplastic lymphoma kinase protein. Furthermore, PASS algorithm predicted anti-neoplastic activity for all the four molecules. Thus these hits are found to be promising leads for anaplastic lymphoma kinase inhibitors. We believe that this study will be useful for the discovery and designing of more potent anaplastic lymphoma kinase inhibitors in the near future.     

DFT study of the Lewis acid mediated synthesis of 3-acyltetramic acids

The recent emergence and re-emergence of alphaviruses, in particular the chikungunya virus (CHIKV), in numerous countries has invoked a worldwide threat to human health, while simultaneously generating an economic burden on affected countries. There are currently no vaccines or effective drugs available for the treatment of the CHIKV, and with few lead compounds reported, the vital medicinal chemistry is significantly more challenging. This study reports on the discovery of potential inhibitors for the nsP3 macro domain of CHIKV using molecular docking, virtual screening, and molecular dynamics simulations, as well as work done to evaluate and confirm the active site of nsP3. Virtual screening was carried out based on blind docking as well as focused docking, using the database of 1541 compounds from NCI Diversity Set II, to identify hit compounds for nsP3. The top hit compounds were further subjected to molecular dynamic simulations, yielding a greater understanding of the dynamic behavior of nsP3 and its complexes with various ligands, concurrently confirming the outcomes of docking, and establishing in silico lead compounds which target the CHIKV nsP3 enzyme.

c-Met inhibitors with novel binding mode show activity against several hereditary papillary renal cell carcinoma-related mutations

c-Met is a receptor tyrosine kinase often deregulated in human cancers, thus making it an attractive drug target. One mechanism by which c-Met deregulation leads to cancer is through gain-of-function mutations. Therefore, small molecules capable of targeting these mutations could offer therapeutic benefits for affected patients. SU11274 was recently described and reported to inhibit the activity of the wild-type and some mutant forms of c-Met, whereas other mutants are resistant to inhibition. We identified a novel series of c-Met small molecule inhibitors that are active against multiple mutants previously identified in hereditary papillary renal cell carcinoma patients. AM7 is active against wild-type c-Met as well as several mutants, inhibits c-Met-mediated signaling in MKN-45 and U-87 MG cells, and inhibits tumor growth in these two models grown as xenografts. The crystal structures of AM7 and SU11274 bound to unphosphorylated c-Met have been determined. The AM7 structure reveals a novel binding mode compared with other published c-Met inhibitors and SU11274. The molecule binds the kinase linker and then extends into a new hydrophobic binding site. This binding site is created by a significant movement of the C-helix and so represents an inactive conformation of the c-Met kinase. Thus, our results demonstrate that it is possible to identify and design inhibitors that will likely be active against mutants found in different cancers.     

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 potent Yes1 kinase inhibitors using a library screening approach

Yes1 kinase has been implicated as a potential therapeutic target in a number of cancers including melanomas, breast cancers, and rhabdomyosarcomas. Described here is the development of a robust and miniaturized biochemical assay for Yes1 kinase that was applied in a high throughput screen (HTS) of kinase-focused small molecule libraries. The HTS provided 144 (17% hit rate) small molecule compounds with IC₅₀ values in the sub-micromolar range. Three of the most potent Yes1 inhibitors were then examined in a cell-based assay for inhibition of cell survival in rhabdomyosarcoma cell lines. Homology models of Yes1 were generated in active and inactive conformations, and docking of inhibitors supports binding to the active conformation (DFG-in) of Yes1. This is the first report of a large high throughput enzymatic activity screen for identification of Yes1 kinase inhibitors, thereby elucidating the polypharmacology of a variety of small molecules and clinical candidates.     

In silico hit optimization toward AKT inhibition: fragment-based approach,molecular docking and molecular dynamics study

Abstract

Protein kinase B also known as AKT is a cardinal node in different signaling pathways that regulates diverse cell processes. AKT has three isoforms that share high homology. Hyperactivation of each isoform is related with different types of cancer. This work describes the computational search for new inhibitors using a hit optimization process of the previously reported AKT pan inhibitor, a 2,4,6-trisubstituted pyridine. A database of new molecules was proposed using a variant of fragment-based docking methodology and previous reported considerations. Molecular docking followed by molecular dynamics studies were performed to select the best compounds and analyze their behavior. Protein–ligand complexes energy was calculated using molecular mechanics Poisson–Boltzmann surface area protocol. Further, proposed molecules were compared with the ChEMBL database of compounds assayed against AKT. Data analysis leads to determine the structural requirements necessary for a favorable interaction of the proposed ligands with the AKT pocket. Molecular dynamics data suggested that the pK_a of the ligands is important for the stability in the AKT pocket. Molecular similarity analysis shows that proposed ligands have not been previously reported. Thus, ligands with high docking scores and favorable behavior on molecular dynamics simulations are proposed as potential AKT inhibitors.     

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.     

Discovery of promising FtsZ inhibitors by E-pharmacophore, 3D-QSAR,molecular docking study,and molecular dynamics simulation

Filamentous temperature-sensitive protein Z (FtsZ), playing a key role in bacterial cell division, is regarded as a promising target for the design of antimicrobial agent. This study is looking for potential high-efficiency FtsZ inhibitors. Ligand-based pharmacophore and E-pharmacophore, virtual screening and molecular docking were used to detect promising FtsZ inhibitors, and molecular dynamics simulation was used to study the stability of protein-ligand complexes in this paper. Sixty-three inhibitors from published literatures with pIC₅₀ ranging from 2.483 to 5.678 were collected to develop ligand-based pharmacophore model. 4DXD bound with 9PC was selected to develop the E-pharmacophore model. The pharmacophore models validated by test set method and decoy set were employed for virtual screening to exclude inactive compounds against ZINC database. After molecular docking, ADME analysis, IFD docking and MM-GBSA, 8 hits were identified as potent FtsZ inhibitors. A 50?ns molecular dynamics simulation was implemented on the compounds to assess the stability between potent inhibitors and FtsZ. The results indicated that the candidate compounds had a high docking score and were strongly combined with FtsZ by forming hydrogen bonding interactions with key amino acid residues, and van der Waals forces and hydrophobic interactions had significant contribution to the stability of the binding. Molecular dynamics simulation results showed that the protein-ligand compounds performed well in both the stability and flexibility of the simulation process.     

Exploration of Virtual Candidates for Human HMG-CoA Reductase Inhibitors Using Pharmacophore Modeling and Molecular Dynamics Simulations

3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.     

Discovery of furan carboxylate derivatives as novel inhibitors of ATP-citrate lyase via virtual high-throughput screening

The enzyme ATP citrate lyase (ACL) catalyzes the formation of cytosolic acetyl CoA, the starting material for de novo lipid and cholesterol biosynthesis. The dysfunction and upregulation of ACL in numerous cancers makes it an attractive target for developing anticancer therapies. ACL inhibition by shRNA knockdown limits cancer cell proliferation and reduces cancer stemness. We designed and implemented a dual docking protocol to select virtual ACL inhibitors that were scored among the top 10 percentiles by both the Autodock Vina and the Glamdock algorithms. Via this in silico screens of a focused furoic acid library, we discovered four subtypes of furans and benzofurans as novel ACL inhibitors. The hit rate of our in silico protocol was 45.8% with 11 of 24 virtual hits confirmed as active in an in vitro ACL enzymatic assay. The IC₅₀ of the most potent ACL inhibitor A1 is 4.1 μM. Our results demonstrated remarkable hit rate by the dual docking approach and provided novel chemical scaffolds for the development of ACL inhibitors for the treatment of cancer.     

In-silico identification of inhibitors against mutated BCR-ABL protein of chronic myeloid leukemia: a virtual screening and molecular dynamics simulation study

Aberrant and proliferative expression of the oncogene BCR-ABL in the bone marrow cells had been proven as the prime cause of chronic myeloid leukemia (CML). It has been established that tyrosine kinase domain of BCR-ABL protein is a potential therapeutic target for the treatment of CML. Imatinib is considered as a first-generation drug that can inhibit the enzymatic action by inhibiting the ATP binding with BCR-ABL protein. Later on, insensitivity of CML cells towards Imatinib has been observed may be due to mutation in tyrosine kinase domain of the ABL receptor. Subsequently, some other second-generation drugs have also been reported viz. Baustinib, Nilotinib, Dasatinib, Ponatinib, Bafetinib, etc., which can able to combat against mutated domain of ABL tyrosine kinase protein. By taking into account of bioavailability and resistance developed, there is an utmost need to find some more inhibitors for the mutated ABL tyrosine kinase protein. For virtual screening, a data-set has been generated by collecting the all available drug like natural compounds from ZINC and Drug Bank databases. Comparative docking analysis was also carried out on the active site of ABL tyrosine kinase receptor with reported reference inhibitors. Molecular dynamics simulation of the best screened interacting complex was done for 50 ns to validate the stability of the system. These selected inhibitors were further validated and analyzed through pharmacokinetics properties and series of ADMET parameters by in silico methods. Considering the above said parameters proposed molecules are concluded as potential leads for drug designing pipeline against CML.     

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.     

Structural insight into Mycobacterium tuberculosis maltosyl transferase inhibitors: pharmacophore-based virtual screening,docking, and molecular dynamics simulations

Pharmacophore-based virtual screening, subsequent docking, and molecular dynamics (MD) simulations have been done to identify potential inhibitors of maltosyl transferase of Mycobacterium tuberculosis (mtb GlgE). Ligand and structure-based pharmacophore models representing its primary binding site (pbs) and unique secondary binding site 2 (sbs2), respectively, were constructed based on the three dimensional structure of mtb GlgE. These pharmacophore models were further used for screening of ZINC and antituberculosis compounds database (ATD). Virtually screened molecules satisfying Lipinski’s rule of five were then analyzed using docking studies and have identified 23 molecules with better binding affinity than its natural substrate, maltose. Four top scoring ligands from ZINC and ATD that either binds to pbs or sbs2 have been subjected to 10 ns each MD simulations and binding free energy calculations. Results of these studies have confirmed stable protein ligand binding. Results reported in the article are likely to be helpful in antitubercular therapeutic development research.     

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.     

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.     

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.     

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