13 citations · 37 across the 13 of their papers we have counts for
5 papers · 1 filter
Analytical Excited-State Gradients and Derivative Couplings in TDDFT with Minimal Auxiliary Basis Set Approximation and GPU Acceleration
Zhichen Pu, Xiaojie Wu, Yuanheng Wang +5
Calculating excited-state gradients and derivative couplings using time-dependent density functional theory (TDDFT) remains a computationally demanding task. An efficient variant,…
CryoDyna: Multiscale end-to-end modeling of cryo-EM macromolecule dynamics with physics-aware neural network
Chengwei Zhang, Shimian Li, Yihao Niu +4
Single-particle cryo-EM has transformed structural biology but still faces challenges in resolving conformational heterogeneity at atomic resolution. Existing cryo-EM heterogeneity…
TRIDS: AI-native molecular docking framework for accelerating high-throughput virtual screening with physically valid binding poses
Xuhan Liu, Baohua Zhang, Yue Xue +7
Molecular docking is a cornerstone of drug discovery for unveiling the mechanism of ligand-receptor interactions. With the recent advances of deep learning (DL), AI-powered molecul…
Large Language Models as AI Agents for Digital Atoms and Molecules: Catalyzing a New Era in Computational Biophysics
Yijie Xia, Xiaohan Lin, Zicheng Ma +9
In computational biophysics, where molecular data is expanding rapidly and system complexity is increasing exponentially, large language models (LLMs) and agent-based systems are f…
Performing Path Integral Molecular Dynamics Using Artificial Intelligence Enhanced Molecular Simulation Framework
Cheng Fan, Maodong Li, Sihao Yuan +4
This study employed an artificial intelligence-enhanced molecular simulation framework to enable efficient Path Integral Molecular Dynamics (PIMD) simulations. Owing to its modular…