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Title: Fast Calculation of Protein–Protein Binding Free Energies Using Umbrella Sampling with a Coarse-Grained Model

Journal Article · · Journal of Chemical Theory and Computation
ORCiD logo [1];  [2]
  1. Center for Modeling Complex Interactions, University of Idaho, Moscow, Idaho 83844, United States
  2. Department of Physics, University of Idaho, Moscow, Idaho 83844, United States

Determination of protein-protein binding affinity values is key to understanding various underlying biological phenomena, such as how missense variations change protein-protein binding. Most existing nonrigorous (fast) and rigorous (slow) methods that rely on all-atom representation of the proteins force the user to choose between speed and accuracy. In an attempt to achieve balance between speed and accuracy, we have combined rigorous umbrella sampling molecular dynamics simulation with a coarse-grained protein model. We predicted the effect of missense variations on binding affinity by selecting three protein-protein systems and comparing results to empirical relative binding affinity values and to nonrigorous modeling approaches. We obtained significant improvement both in our ability to discern stabilizing from destabilizing missense variations and in the correlation between predicted and experimental values compared to nonrigorous approaches. Overall our results suggest that using a rigorous affinity calculation method with coarse-grained protein models could offer fast and reliable predictions of protein-protein binding free energies.

Research Organization:
Univ. of Idaho, Moscow, ID (United States)
Sponsoring Organization:
USDOE Office of Nuclear Energy (NE)
Grant/Contract Number:
AC07-05ID14517
OSTI ID:
1417063
Alternate ID(s):
OSTI ID: 1508328
Journal Information:
Journal of Chemical Theory and Computation, Journal Name: Journal of Chemical Theory and Computation Vol. 14 Journal Issue: 2; ISSN 1549-9618
Publisher:
American Chemical SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 23 works
Citation information provided by
Web of Science

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