Feig, Michael

Multi-State Modeling of G-protein Coupled Receptors at Experimental Accuracy

Heo, L., & Feig, M. (2021) · Proteins Structure Function and Bioinformatics

Receptor Mechanisms and SignalingProtein Structure and Dynamics

Cited by 215

Multi‐state modeling of G‐protein coupled receptors at experimental accuracy

Heo, L., & Feig, M. (2022) · Proteins: Structure, Function, and Bioinformatics

Receptor Mechanisms and SignalingProtein Structure and Dynamics

Cited by 215

Direct generation of protein conformational ensembles via machine learning

Janson, G., Valdes-Garcia, G., Heo, L., & Feig, M. (2023) · Nature Communications

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 192

Direct Generation of Protein Conformational Ensembles via Machine Learning

Janson, G., Valdes-Garcia, G., Heo, L., & Feig, M. (2022) · Nature Communications

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 192

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

Hwang, W., Austin, S. L., Blondel, A., Boittier, E. D., Boresch, S., Buck, M., Buckner, J., Caflisch, A., Chang, H.-T., Cheng, X., et al. (2024) · The Journal of Physical Chemistry B

Protein Structure and DynamicsAdvanced Physical and Chemical Molecular Interactions

Cited by 136

Transferable deep generative modeling of intrinsically disordered protein conformations

Janson, G., & Feig, M. (2024) · PLoS Computational Biology

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 62

Transferable deep generative modeling of intrinsically disordered protein conformations

Janson, G., & Feig, M. (2024) · PLOS Computational Biology

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 62

Accurate Predictions of Molecular Properties of Proteins via Graph Neural Networks and Transfer Learning

Wozniak, S., Janson, G., & Feig, M. (2025) · Journal of Chemical Theory and Computation

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 14

Characterization of RNA polymerase II trigger loop mutations using molecular dynamics simulations and machine learning

Dutagaci, B., Duan, B., Qiu, C., Kaplan, C. D., & Feig, M. (2023) · PLOS Computational Biology

Protein Structure and DynamicsRNA and protein synthesis mechanisms

Cited by 7

Characterization of RNA Polymerase II Trigger Loop Mutations using Molecular Dynamics Simulations and Machine Learning

Dutagaci, B., Duan, B., Qiu, C., Kaplan, C. D., & Feig, M. (2022) · PLoS Computational Biology

Protein Structure and DynamicsRNA and protein synthesis mechanisms

Cited by 7

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Raza, S., Yadav, N. S., Jussupow, A., Kerfeld, C. A., Feig, M., & Vermaas, J. V. (2025) · The Journal of Physical Chemistry B

Protein Structure and DynamicsAdvanced Physical and Chemical Molecular Interactions

Cited by 4

Structure Characterization of Bacterial Microcompartment Shells via X-ray Scattering and Coordinate Modeling: Evidence for adventitious capture of cytoplasmic proteins

Zuo, X., Jussupow, A., Ponomarenko, N. S., Tefft, N. M., Yadav, N. S., Range, K. L., Ralston, C. Y., TerAvest, M. A., Sutter, M., Kerfeld, C. A., et al. (2024) · ACS Applied Bio Materials

Enzyme Structure and FunctionProtein Structure and Dynamics

Cited by 3