Latent Chemical Space Searching for Plug-in Multi-objective Molecule Generation

arXiv:2404.06691v1 Announce Type: cross
Abstract: Molecular generation, an essential method for identifying new drug structures, has been supported by advancements in machine learning and computational technology. However, challenges remain in multi-objective generation, model adaptability, and practical application in drug discovery. In this study, we developed a versatile 'plug-in' molecular generation model that incorporates multiple objectives related to target affinity, drug-likeness, and synthesizability, facilitating its application in various drug development contexts. We improved the Particle Swarm Optimization (PSO) in the context …

abstract adaptability application arxiv challenges computational cs.lg cs.ne discovery drug discovery however machine machine learning multi-objective practical q-bio.bm searching space study technology type