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Find my institution Log In Journal of Chemical Information and Modeling ACS Publications …
Find my institution Log In Journal of Chemical Information and Modeling ACS Publications …
Quantum chemistry in the age of machine learning
PO Dral - The journal of physical chemistry letters, 2020 - ACS Publications
As the quantum chemistry (QC) community embraces machine learning (ML), the number of
new methods and applications based on the combination of QC and ML is surging. In this …
new methods and applications based on the combination of QC and ML is surging. In this …
Alchemical binding free energy calculations in AMBER20: Advances and best practices for drug discovery
Predicting protein–ligand binding affinities and the associated thermodynamics of
biomolecular recognition is a primary objective of structure-based drug design. Alchemical …
biomolecular recognition is a primary objective of structure-based drug design. Alchemical …
Advances in the calculation of binding free energies
A de Ruiter, C Oostenbrink - Current opinion in structural biology, 2020 - Elsevier
Highlights•Binding free energy calculations are increasing used in drug design and
biotechnology.•We distinguish end-state methods, alchemical methods and pathway …
biotechnology.•We distinguish end-state methods, alchemical methods and pathway …
Machine-learning-assisted free energy simulation of solution-phase and enzyme reactions
Despite recent advances in the development of machine learning potentials (MLPs) for
biomolecular simulations, there has been limited effort on develo** stable and accurate …
biomolecular simulations, there has been limited effort on develo** stable and accurate …
Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development
Understanding enzyme mechanisms is essential for unraveling the complex molecular
machinery of life. In this review, we survey the field of computational enzymology …
machinery of life. In this review, we survey the field of computational enzymology …
Hierarchical machine learning of potential energy surfaces
We present hierarchical machine learning (hML) of highly accurate potential energy
surfaces (PESs). Our scheme is based on adding predictions of multiple Δ-machine learning …
surfaces (PESs). Our scheme is based on adding predictions of multiple Δ-machine learning …
Predicting density functional theory-quality nuclear magnetic resonance chemical shifts via δ-machine learning
PA Unzueta, CS Greenwell… - Journal of Chemical …, 2021 - ACS Publications
First-principles prediction of nuclear magnetic resonance chemical shifts plays an
increasingly important role in the interpretation of experimental spectra, but the required …
increasingly important role in the interpretation of experimental spectra, but the required …
Combined QM/MM, machine learning path integral approach to compute free energy profiles and kinetic isotope effects in RNA cleavage reactions
We present a fast, accurate, and robust approach for determination of free energy profiles
and kinetic isotope effects for RNA 2′-O-transphosphorylation reactions with inclusion of …
and kinetic isotope effects for RNA 2′-O-transphosphorylation reactions with inclusion of …
Development of a robust indirect approach for MM→ QM free energy calculations that combines force-matched reference potential and Bennett's acceptance ratio …
TJ Giese, DM York - Journal of chemical theory and computation, 2019 - ACS Publications
We use the PBE0/6-31G* density functional method to perform ab initio quantum
mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations under …
mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations under …