EvaMol : A python tool for evaluating molecules in hit-to-lead optimization

Abstract

This Python script was developed as a tool in structure-based drug discovery processes, such as fragment-to-lead-optimization, where a large number of variants of an initially identified hit molecule have to be evaluated and ranked in silico. The tool facilitates the identification and selection of follow-up drug candidates with improved predicted pharmacokinetic and binding properties. These candidates can derive from different procedures like similarity search or systematic chemical modifications. The initial hit data are provided either as coordinates of the protein-molecule complex obtained experimentally or by in silico methods such as docking making the script a versatile tool adaptable to variable workflows.