A litmus test for classifying recognition mechanisms of transiently binding proteins
Artikel i vetenskaplig tidskrift, 2022
Partner recognition in protein binding is critical for all biological functions, and yet, delineating its mechanism is challenging, especially when recognition happens within microseconds. We present a theoretical and experimental framework based on straight-forward nuclear magnetic resonance relaxation dispersion measurements to investigate protein binding mechanisms on sub-millisecond timescales, which are beyond the reach of standard rapid-mixing experiments. This framework predicts that conformational selection prevails on ubiquitin’s paradigmatic interaction with an SH3 (Src-homology 3) domain. By contrast, the SH3 domain recognizes ubiquitin in a two-state binding process. Subsequent molecular dynamics simulations and Markov state modeling reveal that the ubiquitin conformation selected for binding exhibits a characteristically extended C-terminus. Our framework is robust and expandable for implementation in other binding scenarios with the potential to show that conformational selection might be the design principle of the hubs in protein interaction networks.
Författare
Kalyan S. Chakrabarti
Max-Planck-Gesellschaft
Krea University
Simon Olsson
Chalmers, Data- och informationsteknik, Data Science och AI
Freie Universität Berlin
Supriya Pratihar
Max-Planck-Gesellschaft
Karin Giller
Max-Planck-Gesellschaft
Kerstin Overkamp
Max-Planck-Gesellschaft
Ko On Lee
Korea Basic Science Institute
Vytautas Gapsys
Max-Planck-Gesellschaft
Kyoung Seok Ryu
Korea Basic Science Institute
Bert L. de Groot
Max-Planck-Gesellschaft
Frank Noé
Freie Universität Berlin
Rice University
Stefan Becker
Max-Planck-Gesellschaft
Donghan Lee
University of Louisville
Thomas R. Weikl
Max-Planck-Gesellschaft
Christian Griesinger
Max-Planck-Gesellschaft
Nature Communications
2041-1723 (ISSN) 20411723 (eISSN)
Vol. 13 1 3792Ämneskategorier (SSIF 2011)
Biofysik
Strukturbiologi
Bioinformatik och systembiologi
DOI
10.1038/s41467-022-31374-5
PubMed
35778416