Molecular dynamics is based on solving Newton's equations for many-particle systems that evolve along complex, highly fluctuating trajectories. The orbital instability and short-time complexity of Newtonian orbits is in sharp contrast to the more coherent behavior of collective modes such as density profiles. The notion of virtual molecular dynamics is introduced here based on temporal coarse-graining via Pade approximants and the Ito formula for stochastic processes. It is demonstrated that this framework leads to significant efficiency over traditional molecular dynamics and avoids the need to introduce coarse-grained variables and phenomenological equations for their evolution. In this framework, an all-atom trajectory is represented by a Markov chain of virtual atomic states at a discrete sequence of timesteps, transitions between which are determined by an integration of conventional molecular dynamics with Pade approximants and a microstate energy annealing methodology. The latter is achieved by a conventional and an MD NVE energy minimization schemes. This multiscale framework is demonstrated for a pertussis toxin subunit undergoing a structural transition, a T=1 capsid-like structure of HPV16 L1 protein, and two coalescing argon droplets.
Correlation-Converged Virtual Orbitals for Accurate and Efficient Quantum Molecular Simulations
City University of Hong Kong（香港城市大学）；Hon Hai Research Institute（鸿海研究院）；National Taiwan University（台湾大学）；National Center for Theoretical Sciences, National Taiwan University（台湾大学理论科学中心）；Department of Material Science and Engineering, City University of Hong Kong（香港城市大学材料科学与工程系）
TRIDS: AI-native molecular docking framework for accelerating high-throughput virtual screening with physically valid binding poses
Shenzhen Bay Laboratory（深圳湾实验室）；Shenzhen medical academy of research and translation（深圳市医学科学院）；Peking University（北京大学）；Changping Laboratory（昌平实验室）；Westlake University（西湖大学）；Chromatin (Beijing) Technology Co., Ltd.（华因泰（北京）科技有限公司）；XtalPi Technologies Co., Ltd.（晶泰科技有限公司）；ICE Bioscience Inc.（冰鉴生物科技有限公司）
Sensing the properties of virtual objects without physical feedback
Intangible Realities Laboratory (IRL), Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIus), University of Santiago de Compostela, Santiago de Compostela, Spain（圣地亚哥-德孔波斯特拉大学）
