8 citations · 14 across the 9 of their papers we have counts for
9 papers
THEMol dataset: Torsion, Hessian, and Energy of Molecules
Jiashu Liang, Tianze Zheng, Yu Xia +13
We present THEMol (Torsion, Hessian, Energy of Molecules), a massive open-source collection of quantum mechanical properties tailored for closed-shell organic molecules, with up to…
Development and large-scale benchmarks of a protein--ligand absolute binding free energy toolkit
Yu Liu, Ailun Wang, Yu Xia +2
Absolute binding free energy (ABFE) calculations offer a theoretically rigorous approach for predicting protein--ligand binding affinities without the scaffold constraints of relat…
Accelerated Machine Learning Force Field for Predicting Thermal Conductivity of Organic Liquids
Wei Feng, Siyuan Liu, Hongyi Wang +11
The thermal conductivity of organic liquids is a vital parameter influencing various industrial and environmental applications, including energy conversion, electronics cooling, an…
Bridging Quantum Mechanics to Liquid Properties via a Universal Organic Force Field
Tianze Zheng, Xingyuan Xu, Zhi Wang +10
Molecular dynamics simulations are essential tools for unraveling atomic-level insights into the structure and behavior of condensed-phase systems. However, the universal and accur…
Generative molecule evolution using 3D pharmacophore for efficient Structure-Based Drug Design
Yi He, Ailun Wang, Zhi Wang +3
Recent breakthroughs in generative models have shown great promise for drug discovery, yet Structure-Based Drug Design (SBDD) faces two critical challenges: the scarcity of high-qu…
A Unified Predictive and Generative Solution for Liquid Electrolyte Formulation
Zhenze Yang, Yifan Wu, Xu Han +10
Liquid electrolytes are critical components of next-generation energy storage systems, enabling fast ion transport, minimizing interfacial resistance, and ensuring electrochemical…
OpenMM-Python-Force: Deploying Accelerated Python Modules in Molecular Dynamics Simulation
Zhi Wang, Wen Yan
We present OpenMM-Python-Force, a plugin designed to extend OpenMM's functionality by enabling integration of energy and force calculations from external Python programs via a call…
Data-Driven Parametrization of Molecular Mechanics Force Fields for Expansive Chemical Space Coverage
Tianze Zheng, Ailun Wang, Xu Han +9
A force field is a critical component in molecular dynamics simulations for computational drug discovery. It must achieve high accuracy within the constraints of molecular mechanic…
A predictive machine learning force field framework for liquid electrolyte development
Sheng Gong, Yumin Zhang, Zhenliang Mu +13
Despite the widespread applications of machine learning force fields (MLFF) in solids and small molecules, there is a notable gap in applying MLFF to simulate liquid electrolyte, a…