CSearch: chemical space search via virtual synthesis and global optimization.

ABSTRACT: The two key components of computational molecular design are virtually generating molecules and predicting the properties of these generated molecules. This study focuses on an effective method for molecular generation through virtual synthesis and global optimization of a given objective function. Using a pre-trained graph neural network (GNN) objective function to approximate the docking energies of compounds for four target receptors, we generated highly optimized compounds with 300-400 times less computational effort compared to virtual compound library screening. These optimized compounds exhibit similar synthesizability and diversity to known binders with high potency and are notably novel compared to library chemicals or known ligands. This method, called CSearch, can be effectively

SUBMITTER: Kim H 

PROVIDER: S-EPMC11622599 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature