Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods

From systems to structure — using genetic data to model protein structures

(2022) Hannes Braberg et al.   NATURE REVIEWS GENETICS

Generating 3D molecules conditional on receptor binding sites with deep generative models

(2022) Matthew Ragoza et al.   Chemical Science

Conformational transitions in BTG1 antiproliferative protein and their modulation by disease mutants

(2022) Ekaterina Kots et al.   BIOPHYSICAL JOURNAL

Circuit topology predicts pathogenicity of missense mutations

(2022) Jaie Woodard et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations

(2022) Jingxuan Zhu et al.   Nature Communications

Dynamic coupling of residues within proteins as a mechanistic foundation of many enigmatic pathogenic missense variants

(2022) Nicholas J. Ose et al.   PLoS Computational Biology

MVP predicts the pathogenicity of missense variants by deep learning

(2021) Hongjian Qi et al.   Nature Communications

NMR spectroscopy captures the essential role of dynamics in regulating biomolecular function

(2021) T. Reid Alderson et al.   CELL

Unsupervised Learning Methods for Molecular Simulation Data

(2021) Aldo Glielmo et al.   CHEMICAL REVIEWS

CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction

(2021) Fusong Ju et al.   Nature Communications

Assessing the performance of computational predictors for estimating protein stability changes upon missense mutations

(2021) Shahid Iqbal et al.   BRIEFINGS IN BIOINFORMATICS

Deep learning techniques have significantly impacted protein structure prediction and protein design

(2021) Robin Pearce et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets

(2021) Michael D. Ward et al.   Nature Communications

Machine learning in protein structure prediction

(2021) Mohammed AlQuraishi   CURRENT OPINION IN CHEMICAL BIOLOGY

Interpretable artificial intelligence and exascale molecular dynamics simulations to reveal kinetics: Applications to Alzheimer's disease

(2021) William Martin et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Disease variant prediction with deep generative models of evolutionary data

(2021) Jonathan Frazer et al.   NATURE

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

(2021) Mihaly Varadi et al.   NUCLEIC ACIDS RESEARCH

Machine Learning for Molecular Simulation

(2020) Frank Noé et al.   Annual Review of Physical Chemistry

Rhapsody: Predicting the pathogenicity of human missense variants

(2020) Luca Ponzoni et al.   BIOINFORMATICS

Computationally predicting binding affinity in protein–ligand complexes: free energy-based simulations and machine learning-based scoring functions

(2020) Debby D Wang et al.   BRIEFINGS IN BIOINFORMATICS

Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods

(2020) James M Krieger et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

DynaMut2 : Assessing changes in stability and flexibility upon single and multiple point missense mutations

(2020) Carlos H.M. Rodrigues et al.   PROTEIN SCIENCE

Prediction of rifampicin resistance beyond the RRDR using structure-based machine learning approaches

(2020) Stephanie Portelli et al.   Scientific Reports

Predicting Genetic Variation Severity Using Machine Learning to Interpret Molecular Simulations

(2020) Matthew D. McCoy et al.   BIOPHYSICAL JOURNAL

Estimating Change in Foldability Due to Multipoint Deletions in Protein Structures

(2020) Anupam Banerjee et al.   Journal of Chemical Information and Modeling

Adaptability and specificity: how do proteins balance opposing needs to achieve function?

(2020) Bentley Wingert et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Generative deep learning for macromolecular structure and dynamics

(2020) Pourya Hoseini et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Modulating Hinge Flexibility in the APP Transmembrane Domain Alters γ-Secretase Cleavage

(2019) Alexander Götz et al.   BIOPHYSICAL JOURNAL

Coupling Molecular Dynamics and Deep Learning to Mine Protein Conformational Space

(2019) Matteo T. Degiacomi   STRUCTURE

Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer’s Disease

(2019) Salma Jamal et al.   Frontiers in Pharmacology

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

(2019) Alex Zhavoronkov et al.   NATURE BIOTECHNOLOGY

Machine learning for protein folding and dynamics

(2019) Frank Noé et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Intrinsic dynamics is evolutionarily optimized to enable allosteric behavior

(2019) Yan Zhang et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

OUP accepted manuscript

(2018)   BRIEFINGS IN BIOINFORMATICS

ColDock: Concentrated Ligand Docking with All-Atom Molecular Dynamics Simulation

(2018) Kazuhiro Takemura et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Markov State Models: From an Art to a Science

(2018) Brooke E. Husic et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Structural dynamics is a determinant of the functional significance of missense variants

(2018) Luca Ponzoni et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

VAMPnets for deep learning of molecular kinetics

(2018) Andreas Mardt et al.   Nature Communications

The EVcouplings Python framework for coevolutionary sequence analysis

(2018) Thomas A Hopf et al.   BIOINFORMATICS

Mutation effects predicted from sequence co-variation

(2017) Thomas A Hopf et al.   NATURE BIOTECHNOLOGY

OUP accepted manuscript

(2017)   NUCLEIC ACIDS RESEARCH

‘Latent drivers’ expand the cancer mutational landscape

(2015) Ruth Nussinov et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability

(2015) Vincent Frappier et al.   NUCLEIC ACIDS RESEARCH

Molecular Binding Sites Are Located Near the Interface of Intrinsic Dynamics Domains (IDDs)

(2014) Hongchun Li et al.   Journal of Chemical Information and Modeling

Platinum: a database of experimentally measured effects of mutations on structurally defined protein–ligand complexes

(2014) Douglas E.V. Pires et al.   NUCLEIC ACIDS RESEARCH

A Coarse-Grained Elastic Network Atom Contact Model and Its Use in the Simulation of Protein Dynamics and the Prediction of the Effect of Mutations

(2014) Vincent Frappier et al.   PLoS Computational Biology

ATPase Subdomain IA Is a Mediator of Interdomain Allostery in Hsp70 Molecular Chaperones

(2014) Ignacio J. General et al.   PLoS Computational Biology

Models with Energy Penalty on Interresidue Rotation Address Insufficiencies of Conventional Elastic Network Models

(2011) Lee-Wei Yang   BIOPHYSICAL JOURNAL

A method and server for predicting damaging missense mutations

(2010) Ivan A Adzhubei et al.   NATURE METHODS

Crystal Structure of the p53 Core Domain Bound to a Full Consensus Site as a Self-Assembled Tetramer

(2010) Yongheng Chen et al.   STRUCTURE

Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0

(2009) Yves Dehouck et al.   BIOINFORMATICS

Principal component analysis of native ensembles of biomolecular structures (PCA_NEST): insights into functional dynamics

(2009) Lee-Wei Yang et al.   BIOINFORMATICS

The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding

(2009) A. Bakan et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Perturbation-Response Scanning Reveals Ligand Entry-Exit Mechanisms of Ferric Binding Protein

(2009) Canan Atilgan et al.   PLoS Computational Biology