Protein Conformation Generation via Force-Guided SE(3) Diffusion Models

arXiv:2403.14088v1 Announce Type: cross
Abstract: The conformational landscape of proteins is crucial to understanding their functionality in complex biological processes. Traditional physics-based computational methods, such as molecular dynamics (MD) simulations, suffer from rare event sampling and long equilibration time problems, hindering their applications in general protein systems. Recently, deep generative modeling techniques, especially diffusion models, have been employed to generate novel protein conformations. However, existing score-based diffusion methods cannot properly incorporate important physical prior knowledge to guide the generation process, …

abstract applications arxiv computational cs.lg diffusion diffusion models dynamics event general generative generative modeling landscape modeling molecular dynamics physics processes protein proteins q-bio.bm sampling simulations systems type understanding via