In-silico screening for anti-Zika virus phytochemicals

Zika virus (ZIKV) is an arbovirus that has infected hundreds of thousands of people and is a rapidly expanding epidemic across Central and South America. ZIKV infection has caused serious, albeit rare, complications including Guillain–Barré syndrome and congenital microcephaly. There are currently no vaccines or antiviral agents to treat or prevent ZIKV infection, but there are several ZIKV non-structural proteins that may serve as promising antiviral drug targets. In this work, we have carried out an in-silico search for potential anti-Zika viral agents from natural sources. We have generated ZIKV protease, methyltransferase, and RNA-dependent RNA polymerase using homology modeling techniques and we have carried out molecular docking analyses of our in-house virtual library of phytochemicals with these protein targets as well as with ZIKV helicase. Overall, 2263 plant-derived secondary metabolites have been docked. Of these, 43 compounds that have drug-like properties have exhibited remarkable docking profiles to one or more of the ZIKV protein targets, and several of these are found in relatively common herbal medicines, suggesting promise for natural and inexpensive antiviral therapy for this emerging tropical disease.     

In silico study of subtilisin-like protease 1 (SUB1) from different Plasmodium species in complex with peptidyl-difluorostatones and characterization of potent pan-SUB1 inhibitors

Plasmodium falciparum subtilisin-like protease 1 (SUB1) is a novel target for the development of innovative antimalarials. We recently described the first potent difluorostatone-based inhibitors of the enzyme ((4S)-(N-((N-acetyl-l-lysyl)-l-isoleucyl-l-threonyl-l-alanyl)-2,2-difluoro-3-oxo-4-aminopentanoyl)glycine (1) and (4S)-(N-((N-acetyl-l-isoleucyl)-l-threonyl-l-alanylamino)-2,2-difluoro-3-oxo-4-aminopentanoyl)glycine (2)). As a continuation of our efforts towards the definition of the molecular determinants of enzyme-inhibitor interaction, we herein propose the first comprehensive computational investigation of the SUB1 catalytic core from six different Plasmodium species, using homology modeling and molecular docking approaches. Investigation of the differences in the binding sites as well as the interactions of our inhibitors 1,2 with all SUB1 orthologues, allowed us to highlight the structurally relevant regions of the enzyme that could be targeted for developing pan-SUB1 inhibitors. According to our in silico predictions, compounds 1,2 have been demonstrated to be potent inhibitors of SUB1 from all three major clinically relevant Plasmodium species (P. falciparum, P. vivax, and P. knowlesi). We next derived multiple structure-based pharmacophore models that were combined in an inclusive pan-SUB1 pharmacophore (SUB1-PHA). This latter was validated by applying in silico methods, showing that it may be useful for the future development of potent antimalarial agents.     

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.     

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.     

Three-dimensional models of histamine H3 receptor antagonist complexes and their pharmacophore

Molecular modeling was used to analyze the binding mode and activities of histamine H₃ receptor antagonists. A model of the H₃ receptor was constructed through homology modeling methods based on the crystal structure of bovine rhodopsin. Known H₃ antagonists were interactively docked into the putative antagonist binding pocket and the resultant model was subjected to molecular mechanics energy minimization and molecular dynamics simulations which included a continuum model of the lipid bilayer and intra- and extracellular aqueous environments surrounding the transmembrane helices. The transmemebrane helices stayed well embedded in the dielectric slab representing the lipid bilayer and the intra- and extracellular loops remain situated in the aqueous solvent region of the model during molecular dynamics simulations of up to 200 ps in duration. A pharmacophore model was calculated by mapping the features common to three active compounds three-dimensionally in space. The 3D pharmacophore model complements our atomistic receptor/ligand modeling. The H₃ antagonist pharmacophore consists of two protonation sites (i.e. basic centers) connected by a central aromatic ring or hydrophobic region. These two basic sites can simultaneously interact with Asp 114 (3.32) in helix III and a Glu 206 (5.46) in helix V which are believed to be the key residues that histamine interacts with to stabilize the receptor in the active state. The interaction with Glu 206 is consistent with the enhanced activity resulting from the additional basic site. In addition to these two salt bridging interactions, the central region of these antagonists contains a lipophilic group, usually an aromatic ring, that is found to interact with several nearby hydrophobic side chains. The picture of antagonist binding provided by these models is consistent with earlier pharmacophore models for H₃ antagonists with some exceptions.     

Binding modes of CCR5-targetting HIV entry inhibitors: partial and full antagonists

Since the CC-chemokine receptor 5 (CCR5) was identified as a major co-receptor for human immunodeficiency virus type 1 (HIV-1) entry into a host cell, CCR5-targetting HIV entry inhibitors have been developed and some of them are currently in clinical trials. Most of these inhibitors also inhibit the physiological chemokine reaction function of CCR5, which is so far considered to be safe to patients based on the observation that individuals that naturally lack CCR5 do not show apparent health problems. Nevertheless, to minimize the toxicity and side effects, it would be ideal to preserve the chemokine receptor activity. In this work, we simulated the flexible docking of two small molecule inhibitors to CCR5 in a solvated phospholipid bilayer environment. One of the inhibitors, aplaviroc has a unique feature of preserving two of the natural chemokine ligands binding to CCR5 and subsequent activation whereas the other one, SCH-C fully blocks chemokine-CCR5 interactions. Our results revealed significantly different binding modes of these two inhibitors although both established extensive interaction networks with CCR5. Comparison of the different binding modes suggests that avoiding the deep insertion of inhibitors into the transmembrane helix bundle may be able to preserve chemokine-CCR5 interactions. These results could help design HIV co-receptor activity-specific inhibitors.