D. E. Kleiman

Active Learning of the Conformational Ensemble of Proteins using Maximum Entropy VAMPNets

This paper introduces MaxEnt VAMPNet, an active learning method that accelerates conformational landscape exploration in biomolecules by maximizing entropy in VAMPNet-trained microstates.

Multi-Agent Reinforcement Learning-based Adaptive Sampling for Conformational Sampling of Proteins

This paper introduces two multi-agent reinforcement learning algorithms to improve conformational sampling in protein simulations by coordinating agents to share information and prioritize relevant collective variables.

Intriguing Role of Water in Plant Hormone Perception

This study uses molecular dynamics simulations to show that water displacement at plant hormone receptor binding sites affects binding free energy and provides insights for agrochemical design.