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Zimmerman MI, Hart KM, Sibbald CA, et al. Prediction of New Stabilizing Mutations Based on Mechanistic Insights from Markov State Models. ACS Cent Sci. 2017;3(12):1311-1321doi: 10.1021/acscentsci.7b00465.
Zimmerman, M. I., Hart, K. M., Sibbald, C. A., Frederick, T. E., Jimah, J. R., Knoverek, C. R., Tolia, N. H., & Bowman, G. R. (2017). Prediction of New Stabilizing Mutations Based on Mechanistic Insights from Markov State Models. ACS central science, 3(12), 1311-1321. https://doi.org/10.1021/acscentsci.7b00465
Zimmerman, Maxwell I, et al. "Prediction of New Stabilizing Mutations Based on Mechanistic Insights from Markov State Models." ACS central science vol. 3,12 (2017): 1311-1321. doi: https://doi.org/10.1021/acscentsci.7b00465
Zimmerman MI, Hart KM, Sibbald CA, Frederick TE, Jimah JR, Knoverek CR, Tolia NH, Bowman GR. Prediction of New Stabilizing Mutations Based on Mechanistic Insights from Markov State Models. ACS Cent Sci. 2017 Dec 27;3(12):1311-1321. doi: 10.1021/acscentsci.7b00465. Epub 2017 Nov 21. PMID: 29296672; PMCID: PMC5746865.
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ACS Cent Sci. 2017 Dec 27;3(12):1311-1321. doi: 10.1021/acscentsci.7b00465. Epub 2017 Nov 21.

Prediction of New Stabilizing Mutations Based on Mechanistic Insights from Markov State Models.

ACS central science

Maxwell I Zimmerman, Kathryn M Hart, Carrie A Sibbald, Thomas E Frederick, John R Jimah, Catherine R Knoverek, Niraj H Tolia, Gregory R Bowman

Affiliations

  1. Department of Biochemistry & Molecular Biophysics, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, Missouri 63110, United States.
  2. Department of Molecular Microbiology, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, Missouri 63110, United States.
  3. Department of Biomedical Engineering and Center for Biological Systems Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, Missouri 63130, United States.

PMID: 29296672 PMCID: PMC5746865 DOI: 10.1021/acscentsci.7b00465

Abstract

Protein stabilization is fundamental to enzyme function and evolution, yet understanding the determinants of a protein's stability remains a challenge. This is largely due to a shortage of atomically detailed models for the ensemble of relevant protein conformations and their relative populations. For example, the M182T substitution in TEM β-lactamase, an enzyme that confers antibiotic resistance to bacteria, is stabilizing but the precise mechanism remains unclear. Here, we employ Markov state models (MSMs) to uncover how M182T shifts the distribution of different structures that TEM adopts. We find that M182T stabilizes a helix that is a key component of a domain interface. We then predict the effects of other mutations, including a novel stabilizing mutation, and experimentally test our predictions using a combination of stability measurements, crystallography, NMR, and

Conflict of interest statement

The authors declare no competing financial interest.

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