M
Michael Feig
Researcher at Michigan State University
Publications - 193
Citations - 28987
Michael Feig is an academic researcher from Michigan State University. The author has contributed to research in topics: Molecular dynamics & Solvation. The author has an hindex of 54, co-authored 181 publications receiving 24201 citations. Previous affiliations of Michael Feig include Scripps Research Institute & RIKEN Quantitative Biology Center.
Papers
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Journal ArticleDOI
RNA polymerase II with open and closed trigger loops: active site dynamics and nucleic acid translocation.
Michael Feig,Zachary F. Burton +1 more
TL;DR: A modified Brownian ratchet mechanism is proposed whereby thermally driven translocation is only possible with an open TL, and fidelity control and catalysis require TL closing.
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Reaching new levels of realism in modeling biological macromolecules in cellular environments
Michael Feig,Yuji Sugita +1 more
TL;DR: In this review, recent studies with models of biomolecules in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses.
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Protein structure refinement via molecular-dynamics simulations: What works and what does not?
Michael Feig,Vahid Mirjalili +1 more
TL;DR: Analysis of the CASP submission from the Feig group focused on refinement success versus amount of sampling, refinement of different secondary structure elements and whether refinement varied as a function of which group provided initial models.
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Experimental accuracy in protein structure refinement via molecular dynamics simulations.
Lim Heo,Michael Feig +1 more
TL;DR: The results presented here demonstrate that structure refinement to experimental accuracy via simulation is indeed possible, but significant challenges are revealed that have to be overcome in practical refinement protocols.
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Extending the horizon: towards the efficient modeling of large biomolecular complexes in atomic detail
TL;DR: The work described herein will lead to new, efficient modeling tools that will allow the simulation of longer timescales and larger system sizes in order to meet current and future challenges by the experimental community.