Artur Meller

发表

DiffNets: deep learning the structural determinants of proteins biochemical properties by comparing different structural ensembles

Maxwell I. Zimmerman, Michael D. Ward, G. Bowman, 2020 .

Conformational distributions of isolated myosin motor domains encode their mechanochemical properties

Maxwell I. Zimmerman, G. Bowman, J. Porter, 2019, bioRxiv.

Predicting the locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

Jonathan H. Borowsky, Michael D. Ward, G. Bowman, 2022, bioRxiv.

Drug specificity and affinity are encoded in the probability of cryptic pocket opening in myosin motor domains

L. Leinwand, G. Bowman, Lindsey A. Lee, 2022, bioRxiv.

Accelerating Cryptic Pocket Discovery Using AlphaFold

G. Bowman, S. Bhakat, Artur Meller, 2022, bioRxiv.

Functional divergence of the sarcomeric myosin, MYH7b, supports species-specific biological roles

Samantha K. Barrick, L. Leinwand, G. Bowman, 2022, The Journal of biological chemistry.

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

Vincent A. Voelz, Matthew F. D. Hurley, Rafal P. Wiewiora, 2021, Nature Chemistry.

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

Maxwell I. Zimmerman, Michael D. Ward, G. Bowman, 2021, Nature Communications.

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

Vincent A. Voelz, Matthew F. D. Hurley, Rafal P. Wiewiora, 2020, Biophysical Journal.

SARS-CoV-2 Simulations Go Exascale to Capture Spike Opening and Reveal Cryptic Pockets Across the Proteome

John D. Chodera, Vincent A. Voelz, Gregory R. Bowman, 2020, bioRxiv.

Homologous mutations in β, embryonic, and perinatal muscle myosins have divergent effects on molecular power generation

L. Leinwand, J. Spudich, K. Ruppel, 2023, bioRxiv.

Conformational distributions of isolated myosin motor domains encode their mechanochemical properties

Michael J. Greenberg, Gregory R. Bowman, Maxwell I. Zimmerman, 2019, bioRxiv.

Discovery of a cryptic pocket in the AI-predicted structure of PPM1D phosphatase explains the binding site and potency of its allosteric inhibitors

Saulo H. P. de Oliveira, A. Davtyan, G. Bowman, 2023, bioRxiv.

Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network

Jonathan H. Borowsky, Michael D. Ward, G. Bowman, 2023, Nature Communications.

Divergent Molecular Phenotypes in Point Mutations at the Same Residue in Beta-Myosin Heavy Chain Lead to Distinct Cardiomyopathies

L. Leinwand, G. Bowman, S. Langer, 2023, bioRxiv.

Homologous mutations in human β, embryonic, and perinatal muscle myosins have divergent effects on molecular power generation

L. Leinwand, J. Spudich, K. Ruppel, 2024, Proceedings of the National Academy of Sciences of the United States of America.

DiffNets: Self-supervised deep learning to identify the mechanistic basis for biochemical differences between protein variants

Maxwell I. Zimmerman, Michael D. Ward, G. Bowman, 2020, bioRxiv.

Toward physics‐based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants

Artur Meller, Devin Kelly, Louis G Smith, 2024, Protein science : a publication of the Protein Society.

Discovery of a cryptic pocket in the AI-predicted structure of PPM1D phosphatase explains the binding site and potency of its allosteric inhibitors

Saulo H. P. de Oliveira, A. Davtyan, G. Bowman, 2023, Frontiers in Molecular Biosciences.