Ensemble-based characterization of unbound and bound states on protein energy landscape
Anatoly M. Ruvinsky, Tatsiana Kirys, Alexander V. Tuzikov, and Ilya A., Vakser

TL;DR
This study uses ensemble-based analysis to compare bound and unbound protein states, revealing insights into their energy landscapes, conformational selection mechanisms, and the role of entropy and vibrations in protein binding.
Contribution
It provides a detailed characterization of protein energy landscapes and conformational ensembles, highlighting the overlap between bound and unbound states and supporting conformational selection as a binding mechanism.
Findings
Bound and unbound spectra often significantly overlap.
Conformational selection is the likely binding mechanism for most proteins studied.
Unbound states generally have higher energy and entropy than bound states.
Abstract
Characterization of protein energy landscape and conformational ensembles is important for understanding mechanisms of protein folding and function. We studied ensembles of bound and unbound conformations of six proteins to explore their binding mechanisms and characterize the energy landscapes in implicit solvent. First, results show that bound and unbound spectra often significantly overlap. Moreover, the larger the overlap the smaller the RMSD between bound and unbound conformational ensembles. Second, the analysis of the unbound-to-bound changes points to conformational selection as the binding mechanism for four of the proteins. Third, the center of the unbound spectrum has a higher energy than the center of the corresponding bound spectrum of the dimeric and multimeric states for most of the proteins. This suggests that the unbound states often have larger entropy than the bound…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsProtein Structure and Dynamics · Spectroscopy and Quantum Chemical Studies · Molecular spectroscopy and chirality
