DrugGen: a database of de novo-generated molecular binders for specified target proteins

Abstract

Abstract De novo molecular generation is a promising approach to drug discovery, building novel molecules from the scratch that can bind the target proteins specifically. With the increasing availability of machine learning algorithms and computational power, artificial intelligence (AI) has emerged as a valuable tool for this purpose. Here, we have developed a database of 3D ligands that collects six AI models for de novo molecular generation based on target proteins, including 20 disease-associated targets. Our database currently includes 1767 protein targets and up to 164 107 de novo-designed molecules. The primary goal is to provide an easily accessible and user-friendly molecular database for professionals in the fields of bioinformatics, pharmacology and related areas, enabling them to efficiently screen for potential lead compounds with biological activity. Additionally, our database provides a comprehensive resource for computational scientists to explore and compare different AI models in terms of their performance in generating novel molecules with desirable properties. All the resources and services are publicly accessible at https://cmach.sjtu.edu.cn/drug/. Database URL: https://cmach.sjtu.edu.cn/drug/.