Gradual Optimization Learning for Conformational Energy Minimization

arXiv:2311.06295v2 Announce Type: replace-cross
Abstract: Molecular conformation optimization is crucial to computer-aided drug discovery and materials design. Traditional energy minimization techniques rely on iterative optimization methods that use molecular forces calculated by a physical simulator (oracle) as anti-gradients. However, this is a computationally expensive approach that requires many interactions with a physical simulator. One way to accelerate this procedure is to replace the physical simulator with a neural network. Despite recent progress in neural networks for molecular conformation energy prediction, …

abstract arxiv computer cs.lg design discovery drug discovery energy however interactions iterative materials optimization oracle physics.chem-ph type