The small molecule libraries will be obtained from the ZINC and Mcule purchasable databases and further common filters will be applied to remove the duplicates. Additionally, an in-house Evolutionary chemical binding similarity (ECBS) method (PMID: 31504818) will be using for primary virtual screening of the curated database. The ECBS method is designed to encode molecular features enriched in evolutionarily conserved chemical-target binding relationships, and formulated by the likelihood of chemical compounds binding to identical targets. The collected chemical pair, target, and evolutionary data were used to build ECBS model through classification similarity learning. In particular, an ECBS model was developed to classify ERCPs (Evolutionarily Related Chemical Pairs) from ‘unrelated chemical pairs’ and the output values of the ECBS model represented chemical similarity score prioritizing the selection of ERCPs.
TS-ensECBS model (Target-Specific ensemble model) is specifically trained to recognize chemical pairs that bind to a given virtual screening (VS) target and are therefore used for VS between different ECBS model. The TS-ensECBS model defines only the ERCP of target that are evolutionarily linked to the VS targets and integrates multiple ECBS models based on definitions of evolutionary information about the VS targets to reflect different evolutionary information. The TS-ensECBS model assigns each chemical a similarity score between 0 and 1. The higher the similarity, the more likely it is to bind to the VS target. Our preliminary work includes the ECBS model (PMID:31504818).
The TS-ensECBS top scoring compounds will be using for virtual screening with AutoDock-Vina and AutoDock4.2. The crystal structures of PDBIDs 6Z5T, 6W02, and 7BF5 will be used for docking procedure. Subsequently, the docked complexes will be used for molecular dynamics simulations using AMBER software. Using BAT tool the absolute binding free energy (ABFE) calculations will be carried. Later these candidates are ranked based on ABFE. After molecules being chosen based on consensus scores from both docking and ABFE, they will be subjected to clustering to find the most common substructures among them. To select the binding pose for the calculation of the final state binding free energy, the docking poses of the compounds shortlisted by both methods are scored using a scoring function to determine the protein-ligand interaction. For choosing the final chemicals for experimental validation, pairwise chemical similarity score, visual inspection and binding free energy scores will be considered. To ensure that the top hits satisfy the ADME properties along with QED scores, and synthesizable quality, we will carry the filters using SwissADME tool.