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Author Correction: Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations
- Source :
- Nature Communications, Vol 9, Iss 1, Pp 1-1 (2018), Nature Communications
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- Understanding and control of structures and rates involved in protein ligand binding are essential for drug design. Unfortunately, atomistic molecular dynamics (MD) simulations cannot directly sample the excessively long residence and rearrangement times of tightly binding complexes. Here we exploit the recently developed multi-ensemble Markov model framework to compute full protein-peptide kinetics of the oncoprotein fragment 25–109Mdm2 and the nano-molar inhibitor peptide PMI. Using this system, we report, for the first time, direct estimates of kinetics beyond the seconds timescale using simulations of an all-atom MD model, with high accuracy and precision. These results only require explicit simulations on the sub-milliseconds timescale and are tested against existing mutagenesis data and our own experimental measurements of the dissociation and association rates. The full kinetic model reveals an overall downhill but rugged binding funnel with multiple pathways. The overall strong binding arises from a variety of conformations with different hydrophobic contact surfaces that interconvert on the milliseconds timescale.<br />Binding and unbinding kinetics are important determinants of protein-protein or small molecule protein functional interactions that can guide drug development. Here the authors exploit the multi-ensemble Markov model framework to develop a computational approach that allows the estimation of binding kinetics reaching into the seconds timescale.
- Subjects :
- Physics
0303 health sciences
Multidisciplinary
010304 chemical physics
Science
Association (object-oriented programming)
General Physics and Astronomy
General Chemistry
01 natural sciences
Article
General Biochemistry, Genetics and Molecular Biology
03 medical and health sciences
Section (archaeology)
0103 physical sciences
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING
lcsh:Q
Statistical physics
lcsh:Science
030304 developmental biology
Subjects
Details
- ISSN :
- 20411723
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Nature Communications
- Accession number :
- edsair.doi.dedup.....633879189dfd6804a6cab79c7afd22af
- Full Text :
- https://doi.org/10.1038/s41467-018-03452-0