Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery
Computational methods constitute efficient strategies for screening and optimizing potential
drug molecules. A critical factor in this process is the binding affinity between candidate …
drug molecules. A critical factor in this process is the binding affinity between candidate …
Scalable hybrid deep neural networks/polarizable potentials biomolecular simulations including long-range effects
Deep-HP is a scalable extension of the Tinker-HP multi-GPU molecular dynamics (MD)
package enabling the use of Pytorch/TensorFlow Deep Neural Network (DNN) models …
package enabling the use of Pytorch/TensorFlow Deep Neural Network (DNN) models …
β-Lactamases evolve against antibiotics by acquiring large active-site electric fields
A compound bound covalently to an enzyme active site can act either as a substrate if the
covalent linkage is readily broken up by the enzyme or as an inhibitor if the bond dissociates …
covalent linkage is readily broken up by the enzyme or as an inhibitor if the bond dissociates …
Routine molecular dynamics simulations including nuclear quantum effects: From force fields to machine learning potentials
We report the implementation of a multi-CPU and multi-GPU massively parallel platform
dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP …
dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP …
A Polarizable QM/MM Model That Combines the State-Averaged CASSCF and AMOEBA Force Field for Photoreactions in Proteins
This study presents the polarizable quantum mechanics/molecular mechanics (QM/MM)
embedding of the state-averaged complete active space self-consistent field (SA-CASSCF) …
embedding of the state-averaged complete active space self-consistent field (SA-CASSCF) …
Streamlining and Optimizing Strategies of Electrostatic Parameterization
Accurate characterization of electrostatic interactions is crucial in molecular simulation.
Various methods and programs have been developed to obtain electrostatic parameters for …
Various methods and programs have been developed to obtain electrostatic parameters for …
Accurate host–guest binding free energies using the AMOEBA polarizable force field
A grand challenge of computational biophysics is accurate prediction of interactions
between molecules. Molecular dynamics (MD) simulations have recently gained much …
between molecules. Molecular dynamics (MD) simulations have recently gained much …
Incorporating Neural Networks into the AMOEBA Polarizable Force Field
Neural network potentials (NNPs) offer significant promise to bridge the gap between the
accuracy of quantum mechanics and the efficiency of molecular mechanics in molecular …
accuracy of quantum mechanics and the efficiency of molecular mechanics in molecular …
Synergistic integration of physical embedding and machine learning enabling precise and reliable force field
L Xu, J Jiang - Journal of Chemical Theory and Computation, 2024 - ACS Publications
Machine-learning force fields have achieved significant strides in accurately reproducing the
potential energy surface with quantum chemical accuracy. However, this approach still faces …
potential energy surface with quantum chemical accuracy. However, this approach still faces …
Advancing Force Fields Parameterization: A Directed Graph Attention Networks Approach
Force fields (FFs) are an established tool for simulating large and complex molecular
systems. However, parametrizing FFs is a challenging and time-consuming task that relies …
systems. However, parametrizing FFs is a challenging and time-consuming task that relies …