Adaptive CVgen: Leveraging reinforcement learning for advanced sampling in protein folding and chemical reactions.

ABSTRACT: Enhanced sampling techniques have traditionally encountered two significant challenges: identifying suitable reaction coordinates and addressing the exploration-exploitation dilemma, particularly the difficulty of escaping local energy minima. Here, we introduce Adaptive CVgen, a universal adaptive sampling framework designed to tackle these issues. Our approach utilizes a set of collective variables (CVs) to comprehensively cover the system's potential evolutionary phase space, generating diverse reaction coordinates to address the first challenge. Moreover, we integrate reinforcement learning strategies to dynamically adjust the generated reaction coordinates, thereby effectively balancing the exploration-exploitation dilemma. We apply this framework to sample the conformational space of

SUBMITTER: Shen W 

PROVIDER: S-EPMC11551409 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature