Fusing Neural and Physical: Augment Protein Conformation Sampling with Tractable Simulations

arXiv:2402.10433v1 Announce Type: cross
Abstract: The protein dynamics are common and important for their biological functions and properties, the study of which usually involves time-consuming molecular dynamics (MD) simulations in silico. Recently, generative models has been leveraged as a surrogate sampler to obtain conformation ensembles with orders of magnitude faster and without requiring any simulation data (a "zero-shot" inference). However, being agnostic of the underlying energy landscape, the accuracy of such generative model may still be limited. In this work, …

abstract arxiv cs.lg dynamics functions generative generative models molecular dynamics orders protein q-bio.bm q-bio.qm sampling simulations study tractable type