57 citations · 182 across the 11 of their papers we have counts for
12 papers
Multi-objective fluorescent molecule design with a data-physics dual-driven generative framework
Yanheng Li, Zhichen Pu, Lijiang Yang +2
Designing fluorescent small molecules with tailored optical and physicochemical properties requires navigating vast, underexplored chemical space while satisfying multiple objectiv…
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…
A Generalized Nucleation Theory for Ice Crystallization
Maodong Li, Yupeng Huang, Yijie Xia +5
Despite the simplicity of the water molecule, the kinetics of ice nucleation under natural conditions can be complex. We investigated spontaneously grown ice nuclei using all-atom…
Enhanced sampling reveals the main pathway of an organic cascade reaction
Yi Sun, Xu Han, Lijiang Yang
Normal molecular dynamics simulations are usually unable to simulate chemical reactions due to the low probability of forming the transition state. Therefore, enhanced sampling met…
Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure Prediction
Jun Zhang, Sirui Liu, Mengyun Chen +12
Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and…
PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction
Sirui Liu, Jun Zhang, Haotian Chu +16
Proteins are essential component of human life and their structures are important for function and mechanism analysis. Recent work has shown the potential of AI-driven methods for…
Atomistic View of Homogeneous Nucleation of Water into Polymorphic Ices
Maodong Li, Jun Zhang, Niu Haiyang +6
Water is one of the most abundant substances on Earth, and ice, i.e., solid water, has more than 18 known phases. Normally ice in nature exists only as Ice Ih, Ice Ic, or a stackin…
Deep Reinforcement Learning of Transition States
Jun Zhang, Yao-Kun Lei, Zhen Zhang +5
Combining reinforcement learning (RL) and molecular dynamics (MD) simulations, we propose a machine-learning approach (RL) to automatically unravel chemical reaction mechanisms…
A Perspective on Deep Learning for Molecular Modeling and Simulations
Jun Zhang, Yao-Kun Lei, Zhen Zhang +6
Deep learning is transforming many areas in science, and it has great potential in modeling molecular systems. However, unlike the mature deployment of deep learning in computer vi…
Combine Umbrella Sampling with Integrated Tempering Method for Efficient and Accurate Calculation of Free Energy Changes of Complex Energy Surface
Mingjun Yang, Lijiang Yang, Yiqin Gao +1
Umbrella sampling is an efficient method for the calculation of free energy changes of a system along well-defined reaction coordinates. However, when multiple parallel channels al…
Facile implementation of integrated tempering sampling method to enhance the sampling over a broad range of temperatures
Peng Zhao, Li Jiang Yang, Yi Qin Gao +1
Integrated tempering sampling (ITS) method is an approach to enhance the sampling over a broad range of energies and temperatures in computer simulations. In this paper, a new vers…