Author

R. P. Wiewiora

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Biophysics· 4

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 2 Research Focus:protein folding & dynamics· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Assay:protein structure· 1 Approach:simulation· 1

Frequent Co-Authors

J. D. Chodera· 4 shared K. A. Beauchamp· 2 shared A. C. Simmonett· 1 shared A. M. Harbison· 1 shared A. Ma· 1 shared A. Meller· 1 shared B. R. Brooks· 1 shared C. A. Fogarty· 1 shared

Activity by Year

2017-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

4 shared papersBiophysics

J. D. Chodera

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

What Markov state models can and cannot do: Correlation versus path-based observables in protein folding models

E. Suarez, R. P. Wiewiora, C. Wehmeyer, F. Noe, J. D. Chodera, D. M. Zuckerman

This study evaluates the ability of Markov state models (MSMs) to reproduce path-based observables in protein folding, finding they are reliable only when state lifetimes exceed the lag time, and history-augmented MSMs improve reliability.

bioRxiv · Nov 9, 2020Biophysics

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

M. I. Zimmerman, J. R. Porter, M. D. Ward, S. Singh, N. Vithani, A. Meller, U. L. Mallimadugula, C. E. Kuhn, J. H. Borowsky, R. P. Wiewiora, M. F. D. Hurley, A. M. Harbison, C. A. Fogarty, J. E. Coffland, E. Fadda, , G. R. Bowman

The paper uses exascale simulations to study SARS-CoV-2 protein dynamics, revealing cryptic epitopes and conformational changes that inform antiviral target design.

bioRxiv · Jun 27, 2020 · PreprintBiophysics

The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8

S. Chen, R. P. Wiewiora, F. Meng, N. Babault, A. Ma, W. Yu, K. Qian, H. Hu, H. Zou, J. Wang, S. Fan, G. Blum, F. Pittella-Silva, K. A. Beauchamp, W. Tempel, , M. Luo

This study reveals dynamic conformational landscapes of SETD8 using X-ray structures and molecular simulations, showing how protein dynamics influence catalysis and cancer-associated mutations.

bioRxiv · Oct 12, 2018Biophysics

OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics

P. Eastman, J. Swails, J. D. Chodera, R. T. McGibbon, Y. Zhao, K. A. Beauchamp, L.-P. Wang, A. C. Simmonett, M. P. Harrigan, C. D. Stern, R. P. Wiewiora, B. R. Brooks, V. S. Pande

OpenMM 7 enables rapid development of high-performance molecular dynamics algorithms with extensible features that work across hardware types without modifying the core toolkit.

bioRxiv · Jun 28, 2017Biophysics