Development of a receptor model for efficient in silico screening of HIV-1 integrase inhibitors

Integrase (IN) is a key viral enzyme for the replication of the type-1 human immunodeficiency virus (HIV-1), and as such constitutes a relevant therapeutic target for the development of anti-HIV agents. However, the lack of crystallographic data of HIV IN complexed with the corresponding viral DNA has historically hindered the application of modern structure-based drug design techniques to the discovery of new potent IN inhibitors (INIs). Consequently, the development and validation of reliable HIV IN structural models that may be useful for the screening of large databases of chemical compounds is of particular interest. In this study, four HIV-1 IN homology models were evaluated respect to their capability to predict the inhibition potency of a training set comprising 36 previously reported INIs with IC₅₀ values in the low nanomolar to the high micromolar range. Also, 9 inactive structurally related compounds were included in this training set. In addition, a crystallographic structure of the IN-DNA complex corresponding to the prototype foamy virus (PFV) was also evaluated as structural model for the screening of inhibitors. The applicability of high throughput screening techniques, such as blind and ligand-guided exhaustive rigid docking was assessed. The receptor models were also refined by molecular dynamics and clustering techniques to assess protein sidechain flexibility and solvent effect on inhibitor binding. Among the studied models, we conclude that the one derived from the X-ray structure of the PFV integrase exhibited the best performance to rank the potencies of the compounds in the training set, with the predictive power being further improved by explicitly modeling five water molecules within the catalytic side of IN. Also, accounting for protein sidechain flexibility enhanced the prediction of inhibition potencies among the studied compounds. Finally, an interaction fingerprint pattern was established for the fast identification of potent IN inhibitors. In conclusion, we report an exhaustively validated receptor model if IN that is useful for the efficient screening of large chemical compounds databases in the search of potent HIV-1 IN inhibitors.     

Binding and discerning interactions of PTP1B allosteric inhibitors: Novel insights from molecular dynamics simulations

The α7 helix is either disordered or missing in the three co-crystal structures of allosteric inhibitors with protein tyrosine phosphatase 1B (PTP1B). It was modeled in each complex using the open form of PTP1B structure and studied using molecular dynamics (MD) simulations for 25 ns. B-factor analysis of the residues sheds light on its disordered nature in the co-crystal structures. Further, the ability of inhibitors to act as allosteric inhibitor was studied and established using novel hydrogen bond criteria. The MD simulations were utilized to determine the relative importance of electrostatic and hydrophobic component in to the binding of inhibitors. It was revealed that the hydrophobic interactions predominantly drive the molecular recognition of these inhibitors. Per residue energy decomposition analysis attributed dissimilar affinities of three inhibitors to the several hydrogen bonds and non-bonded interactions. Among the secondary structure elements that surround the allosteric site, helices α6, α7 and loop α6–α7 were notorious in providing variable affinities to the inhibitors. A novel hydrophobic pocket lined by the α7 helix residues Val287, Asn289 and Trp291 was identified in the allosteric site. This study provides useful insights for the rational design of high affinity PTP1B allosteric inhibitors.     

In silico screening and study of novel ERK2 inhibitors using 3D QSAR,docking and molecular dynamics

ERK2 is a dual specificity protein kinase, part of the Ras/Raf/MEK/ERK signal transduction cascade. It forms an interesting target for inhibition based on its relationship with cell proliferation and oncogenesis. A 3D QSAR pharmacophore model (Hypo1) with high correlation (r = 0.938) was developed for ERK2 ATP site on the basis of experimentally known inhibitors. The model included three hydrogen bonds, and one hydrophobic site. Assessment of Hypo1 through Fisher randomization, cost analysis, leave one out method and decoy test suggested that the model can reliably detect ERK2 inhibitors. Hypo1 has been used for virtual screening of potential inhibitors from ZINC, Drug Bank, NCI, Maybridge and Chembank databases. Using Hypo1 as a query, databases have been interrogated for compounds who meet the pharmacophore features. The resulting hit compounds were subject to docking and analysis. Docking and molecular dynamics analysis showed that in order to achieve a higher potency compounds have to interact with catalytic site, glycine rich loop, Hinge region, Gatekeeper region and ATP site entrance residues. We also identified catalytic site and Glycine rich loop as important regions to bind by molecules for better potency and selectivity.     

Identification of chikungunya virus nsP2 protease inhibitors using structure-base approaches

The nsP2 protease of chikungunya virus (CHIKV) is one of the essential components of viral replication and it plays a crucial role in the cleavage of polyprotein precursors for the viral replication process. Therefore, it is gaining attention as a potential drug design target against CHIKV. Based on the recently determined crystal structure of the nsP2 protease of CHIKV, this study identified potential inhibitors of the virus using structure-based approaches with a combination of molecular docking, virtual screening and molecular dynamics (MD) simulations. The top hit compounds from database searching, using the NCI Diversity Set II, with targeting at five potential binding sites of the nsP2 protease, were identified by blind dockings and focused dockings. These complexes were then subjected to MD simulations to investigate the stability and flexibility of the complexes and to gain a more detailed insight into the interactions between the compounds and the enzyme. The hydrogen bonds and hydrophobic contacts were characterized for the complexes. Through structural alignment, the catalytic residues Cys1013 and His1083 were identified in the N-terminal region of the nsP2 protease. The absolute binding free energies were estimated by the linear interaction energy approach and compared with the binding affinities predicted with docking. The results provide valuable information for the development of inhibitors for CHIKV.     

Nanosecond molecular dynamics simulations of Cdc25B and its complex with a 1,4-naphthoquinone inhibitor: implications for rational inhibitor design

Cdc25 phosphatases have been considered as attractive drug targets for anticancer therapies due to the correlation of their overexpression with a wide variety of cancers. To gain insight into designing new potent inhibitors, we investigate the dynamic properties of Cdc25B and its complex with a 1,4-naphtoquinone inhibitor NSC 95397 by means of molecular dynamics simulations in aqueous solution. It is shown from the calculated dynamic properties that the malleability of the residues 530–532 residing at the start of C-terminal region around the active site should be responsible for the catalytic action of Cdc25B. However, binding of the inhibitor in the active site leads to a substantial decrease in the motional amplitude of the flexible residues, due to the hydrophobic interactions with the side chain of Met531. The simulation results also indicate that at least four hydrogen bonds are involved in the enzyme-inhibitor complex. Among them, the hydrogen bond between the side chain carboxylate group of Glu478 and one of the hydroxyl groups of the inhibitor is found to be the most significant binding force stabilizing the inhibitor in the active site. This result supports the previous experimental implication that the possession of a single hydroxyl group is sufficient for the inhibitory activity of 1,4-naphthoquinone inhibitors.     

Effect of allosteric molecules on structure and drug affinity of HIV-1 protease by molecular dynamics simulations

Recent experiments show that small molecules can bind onto the allosteric sites of HIV-1 protease (PR), which provides a starting point for developing allosteric inhibitors. However, the knowledge of the effect of such binding on the structural dynamics and binding free energy of the active site inhibitor and PR is still lacking. Here, we report 200 ns long molecular dynamics simulation results to gain insight into the influences of two allosteric molecules (1H-indole-6-carboxylic acid, 1F1 and 2-methylcyclohexano, 4D9). The simulations demonstrate that both allosteric molecules change the PR conformation and stabilize the structures of PR and the inhibitor; the residues of the flaps are sensitive to the allosteric molecules and the flexibility of the residues is pronouncedly suppressed; the additions of the small molecules to the allosteric sites strengthen the binding affinities of 3TL-PR by about 12–15 kal/mol in the binding free energy, which mainly arises from electrostatic term. Interestingly, it is found that the action mechanisms of 1F1 and 4D9 are different, the former behaviors like a doorman that keeps the inhibitor from escape and makes the flaps (door) partially open; the latter is like a wedge that expands the allosteric space and meanwhile closes the flaps. Our data provide a theoretical support for designing the allosteric inhibitor.     

Molecular docking and dynamic simulation evaluation of Rohinitib — Cantharidin based novel HSF1 inhibitors for cancer therapy

Recent developments in the target based cancer therapies have identified HSF1 as a novel non oncogenic drug target. The present study delineates the design and molecular docking evaluation of Rohinitib (RHT) — Cantharidin (CLA) based novel HSF1 inhibitors for target-based cancer therapy. Here, we exploited the pharmacophoric features of both the parent ligands for the design of novel hybrid HSF1 inhibitors. The RHT-CLA ligands were designed and characterized for ADME/Tox features, interaction with HSF1 DNA binding domain and their pharmacophoric features essential for interaction. From the results, amino acid residues Ala17, Phe61, His63, Asn65, Ser68, Arg71 and Gln72 were found crucial for HSF1 interaction with the Heat shock elements (HSE). The hybrid ligands had better affinity towards the HSF1 DNA binding domain, in comparison to RHT or CLA and interacted with most of the active site residues. Additionally, the HSF1-ligand complex had a reduced affinity towards HSE in comparison to native HSF1. Based on the results, ligand RC15 and RC17 were non carcinogenic, non mutagenic, completely biodegradable under aerobic conditions, had better affinity for HSF1 (1.132 and 1.129 folds increase respectively) and diminished the interaction of HSF1 with HSE (1.203 and 1.239 folds decrease respectively). The simulation analysis also suggested that the ligands formed a stable complex with HSF1, restraining the movement of active site residues. In conclusion, RHT-CLA hybrid ligands can be used as a potential inhibitor of HSF1 for non-oncogene target based cancer therapy.     

Computational determination of binding structures and free energies of glucose 6-phosphate dehydrogenase with novel steroid inhibitors

Glucose 6-phosphate dehydrogenase (G6PD), the first and the rate-limiting enzyme in the pentose phosphate pathway (PPP), catalyzes the oxidation of G6P to 6-phosphogluconolactone and the reduction of NADP⁺ to NADPH. Its key role in cancer promotes the development of a potent and selective inhibitor that might increase cancer cell death when combined with radiotherapy. In the present study, we investigated the detailed binding modes and binding free energies for G6PD interacting with a promising series of recently developed inhibitors, i.e., the steroid derivatives, by performing molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. The docking indicates that the inhibitors occupy the binding sites of both G6P and NADP⁺. The calculated binding free energies on the basis of the MD-simulated enzyme–inhibitor complexes are in good agreement with the experimental activity data for all of the examined inhibitors. The valuable insights into the detailed enzyme–inhibitor binding including the important intermolecular interactions, e.g., the hydrogen bond interaction and the hydrophobic interaction, have been provided. The computational results provide new insights into future rational design of more potent inhibitors of G6PD as a treatment for cancer.     

A structural insight into the inhibitory mechanism of an orally active PI3K/mTOR dual inhibitor,PKI-179 using computational approaches

The PI3K/AKT/mTOR signaling pathway has been identified as an important target for cancer therapy. Attempts are increasingly made to design the inhibitors against the key proteins of this pathway for anti-cancer therapy. The PI3K/mTOR dual inhibitors have proved more effective than the inhibitors against only single protein targets. Recently discovered PKI-179, an orally effective compound, is one such dual inhibitor targeting both PI3K and mTOR. This anti-cancer compound is efficacious both in vitro and in vivo. However, the binding mechanisms and the molecular interactions of PKI-179 with PI3K and mTOR are not yet available. The current study investigated the exact binding mode and the molecular interactions of PKI-179 with PI3Kγ and mTOR using molecular docking and (un)binding simulation analyses. The study identified PKI-179 interacting residues of both the proteins and their importance in binding was ranked by the loss in accessible surface area, number of molecular interactions of the residue, and consistent appearance of the residue in (un)binding simulation analysis. The key residues involved in binding of PKI-179 were Ala-805 in PI3Kγ and Ile-2163 in mTOR as they have lost maximum accessible surface area due to binding. In addition, the residues which played a role in binding of the drug but were away from the catalytic site were also identified using (un)binding simulation analyses. Finally, comparison of the interacting residues in the respective catalytic sites was done for the difference in the binding of the drug to the two proteins. Thus, the pairs of the residues falling at the similar location with respect to the docked drug were identified. The striking similarity in the interacting residues of the catalytic site explains the concomitant inhibition of both proteins by a number of inhibitors. In conclusion, the docking and (un)binding simulation analyses of dual inhibitor PKI-179 with PI3K and mTOR will provide a suitable multi-target model for studying drug–protein interactions and thus help in designing the novel drugs with higher potency.     

Identification of a high affinity selective inhibitor of Polo-like kinase 1 for cancer chemotherapy by computational approach

Polo-like kinase (Plk)1 is a key regulator of the cell cycle during mitotic phase and is an attractive anti-mitotic drug target for cancer. Plk1 is a member of Ser/Thr kinase family which also includes Plk2-4 in human. Plk1 promotes the cell division whereas Plk2 and Plk3 are reported to act as tumour suppressors. The available inhibitors of Plk1 also suppress Plk2 and Plk3 activity significantly resulting in the cell death of normal cells in addition to the cancer cells. Hence, it is imperative to explore Plk1 specific inhibitors as anti-cancer drugs. In this work, a selective potential inhibitor of Plk1 has been identified by molecular docking based high throughput virtual screening. The identified compound exploits the subtle differences between the binding sites of Plk1 and other Ser/Thr kinases including Plk2-4. The predicted binding affinity of identified inhibitor is higher than available inhibitors with a 100-fold selectivity towards Plk1 over Plk2-4 and several cell cycle kinases. It also satisfies the Lipinski's criteria of drug-like molecules and passes the other ADMET filters. This triazole compound with aryl substituent belongs to a novel class of potential inhibitor for Plk1. The suggested potential lead molecule can thus be tested and developed further as a potent and selective anti-cancer drug.     

流感病毒神经氨酸酶抑制剂的理性筛选

介绍了理性筛选流感病毒神经氨酸酶抑制剂的全过程，共分4个阶段：1)化合物数据库类药性处理；2)建立神经氨酸酶抑制剂三维药效团并对目标数据库进行构象搜索；3)分子对接及对接后分析；4)神经氨酸酶抑制模型的建立及待测化合物的活性检测。活性检测后发现4个活性化合物，其中Ic。为10。M的化合物1个．Ic，。为10^-6M的化合物2个，IC50为10^-7M的化合物1个。应用理性筛选方法，从化合物数据库中挑选出部分化合物进行神经氨酸酶抑制活性的筛选，减少了药物筛选的盲目性，提高了药物发现的机率。     

Identification of potent inhibitors of DNA methyltransferase 1 (DNMT1) through a pharmacophore-based virtual screening approach

DNA methylation is an epigenetic change that results in the addition of a methyl group at the carbon-5 position of cytosine residues. DNA methyltransferase (DNMT) inhibitors can suppress tumour growth and have significant therapeutic value. However, the established inhibitors are limited in their application due to their substantial cytotoxicity. Additionally, the standard drugs for DNMT inhibition are non-selective cytosine analogues with considerable cytotoxic side-effects. In the present study, we have designed a workflow by integrating various ligand-based and structure-based approaches to discover new agents active against DNMT1. We have derived a pharmacophore model with the help of available DNMT1 inhibitors. Utilising this model, we performed the virtual screening of Maybridge chemical library and the identified hits were then subsequently filtered based on the Naïve Bayesian classification model. The molecules that have returned from this classification model were subjected to ensemble based docking. We have selected 10 molecules for the biological assay by inspecting the interactions portrayed by these molecules. Three out of the ten tested compounds have shown DNMT1 inhibitory activity. These compounds were also found to demonstrate potential inhibition of cellular proliferation in human breast cancer MDA-MB-231 cells. In the present study, we have utilized a multi-step virtual screening protocol to identify inhibitors of DNMT1, which offers a starting point to develop more potent DNMT1 inhibitors as anti-cancer agents.     

Drug design: new inhibitors for HIV-1 protease based on Nelfinavir as lead

Nelfinavir (Viracept) is a potent, non-peptidic inhibitor of HIV-1 Protease, which has been marketed for the treatment of HIV infected patients. However, HIV-1 develops drug-resistance which decreases the affinity of Nelfinavir for the binding pocket of Protease. We present here three new variants of Nelfinavir, which we have designed with computational tools, with greater affinity for HIV-1 Protease than Nelfinavir itself. Accordingly, we have introduced rational modifications in Nelfinavir, optimizing its affinity to the most conserved amino acids in Protease, in order to increase the efficiency of the three new inhibitors. Minimization and molecular dynamics simulations have been carried out on four complexes, HIV-1 Protease with Nelfinavir and subsequently with the new inhibitors, respectively, in order to analyze the behavior of the systems. Additionally, we have calculated the binding free energy differences Protease:inhibitor, which gave us a quantitative idea of the new molecules inhibitory efficiency in silico.