Agents targeting multiple proteins are known to circumvent efficacy and drug resistance-related limitations in comparison to highly selective drugs. On the other hand, these therapeutics often have unintended off-target interactions giving rise to adverse drug effects. Rational design of agents with targeted polypharmacology requires a detailed understanding of both the chemical space of the targets under investigation and the landscape of the anti-targets. Though there exists a plethora of computer-aided drug design (CADD) tools geared towards creating selective inhibitors, the rational design of multi-targeting agents calls for a novel suite of tools that best accommodates the polypharmacological rationale.<br/><br/>To address this unmet need, we present CSViz, a computational tool that interactively analyzes the chemogenomic landscape of targets and anti-targets to 1) identify scaffolds shared across targets and 2) exclude scaffolds implicated in anti-target binding. CSViz thereby provides a knowledge-driven compound moiety for designing multi-target inhibitors. Given a set of targets and their inhibitors, CSViz estimates pairwise compound similarity and finds the maximum common substructure (MCS). These MCSs are first filtered based on connectivity and ring-based criteria, and later subjected to topological-based clustering. Representative MCSs are identified for each cluster and their enrichment scores are estimated. The resulting MCSs, along with their enrichment scores, enable the identification of initial scaffolds for the design of ligands with multi-targeting activity.<br/><br/>The present case study focuses on identifying polypharmacological agents for kinase targets p38α and EGFR. Representative MCSs shared between inhibitors of p38α and EGFR were identified (Fig. 1). These MCSs were used as seed molecules to virtually screen various vendor libraries. The compounds were found to show favorable docking poses amongst the selected targets. We anticipate that this tool will accelerate the discovery of kinase inhibitors with targeted polypharmacology.

Common Scaffold Visualizer (CSViz): A computational framework to enable interactive analysis and design of multi-targeted kinase inhibitors

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