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A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors

The Journal of chemical physics, 2020-09, Vol.153 (12), p.124105-124105

2020

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Kinetic and thermodynamic insights into sodium ion translocation through the μ-opioid receptor from molecular dynamics and machine learning analysis

PLoS computational biology, 2019-01, Vol.15 (1), p.e1006689-e1006689

2019

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Assessing the relative stability of dimer interfaces in g protein-coupled receptors

PLoS computational biology, 2012-08, Vol.8 (8), p.e1002649-e1002649

2012

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Differences in interactions between transmembrane domains tune the activation of metabotropic glutamate receptors

eLife, 2021-04, Vol.10

2021

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The Dynamic Process of Drug-GPCR Binding at Either Orthosteric or Allosteric Sites Evaluated by Metadynamics

Methods in molecular biology (Clifton, N.J.), 2015, Vol.1335, p.277

2015

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Ligand-Binding Calculations with Metadynamics

Methods in molecular biology (Clifton, N.J.), 2019, Vol.2022, p.233

Provasi, Davide

2019

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Molecular Determinants and Thermodynamics of the Amyloid Precursor Protein Transmembrane Domain Implicated in Alzheimer's Disease

Journal of molecular biology, 2011-05, Vol.408 (5), p.879-895

2011

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Computational structural biology of opioid receptors

Methods in molecular biology (Clifton, N.J.), 2015, Vol.1230, p.13

Provasi, Davide

2015

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Putative Active States of a Prototypic G-Protein-Coupled Receptor from Biased Molecular Dynamics

Biophysical journal, 2010-05, Vol.98 (10), p.2347-2355

2010

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PLUMED: A portable plugin for free-energy calculations with molecular dynamics

Computer physics communications, 2009-10, Vol.180 (10), p.1961-1972

2009

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Promoting transparency and reproducibility in enhanced molecular simulations

Nature methods, 2019-08, Vol.16 (8), p.670-673

The PLUMED consortium

2019

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An efficient strategy to estimate thermodynamics and kinetics of Gprotein-coupled receptor activation using metadynamics and maximum caliber

The Journal of chemical physics, 2018-12, Vol.149 (22)

2018

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GPCRmd uncovers the dynamics of the 3D-GPCRome

Nature methods, 2020-08, Vol.17 (8), p.777-787

2020

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Kinetic and thermodynamic insights into sodium ion translocation through the [mu]-opioid receptor from molecular dynamics and machine learning analysis

PLoS computational biology, 2019-01, Vol.15 (1)

2019

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Bioactive conformations of two seminal delta opioid receptor penta-peptides inferred from free-energy profiles

Biopolymers, 2014-01, Vol.101 (1), p.21-27

2014

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A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors

Kinetic and thermodynamic insights into sodium ion translocation through the μ-opioid receptor from molecular dynamics and machine learning analysis

Assessing the relative stability of dimer interfaces in g protein-coupled receptors

Differences in interactions between transmembrane domains tune the activation of metabotropic glutamate receptors

The Dynamic Process of Drug-GPCR Binding at Either Orthosteric or Allosteric Sites Evaluated by Metadynamics

Ligand-Binding Calculations with Metadynamics

Molecular Determinants and Thermodynamics of the Amyloid Precursor Protein Transmembrane Domain Implicated in Alzheimer's Disease

Computational structural biology of opioid receptors

Putative Active States of a Prototypic G-Protein-Coupled Receptor from Biased Molecular Dynamics

PLUMED: A portable plugin for free-energy calculations with molecular dynamics

Promoting transparency and reproducibility in enhanced molecular simulations

An efficient strategy to estimate thermodynamics and kinetics of Gprotein-coupled receptor activation using metadynamics and maximum caliber

GPCRmd uncovers the dynamics of the 3D-GPCRome

Kinetic and thermodynamic insights into sodium ion translocation through the [mu]-opioid receptor from molecular dynamics and machine learning analysis

Bioactive conformations of two seminal delta opioid receptor penta-peptides inferred from free-energy profiles

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