A Pareto Algorithm for Efficient De Novo Design of Multi-Functional Molecule

TL;DR

This paper presents a Pareto sorting algorithm integrated into a de novo molecule design program, enabling simultaneous optimization of multiple properties and improving the generation of synthesizable, multi-functional molecules.

Contribution

Introduction of a Pareto sorting algorithm into de novo design to optimize multiple properties and constraints simultaneously.

Findings

Enhanced ability to generate molecules meeting complex constraints

Improved performance in designing dual and selective inhibitors

Successful design of structure-directing agents for zeolites

Abstract

We have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor.