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Binding Free Energy Landscape of Domain-Peptide Interactions

Författare

  • Iskra Staneva
  • Stefan Wallin

Summary, in English

Peptide recognition domains (PRDs) are ubiquitous protein domains which mediate large numbers of protein interactions in the cell. How these PRDs are able to recognize peptide sequences in a rapid and specific manner is incompletely understood. We explore the peptide binding process of PDZ domains, a large PRD family, from an equilibrium perspective using an all-atom Monte Carlo (MC) approach. Our focus is two different PDZ domains representing two major PDZ classes, I and II. For both domains, a binding free energy surface with a strong bias toward the native bound state is found. Moreover, both domains exhibit a binding process in which the peptides are mostly either bound at the PDZ binding pocket or else interact little with the domain surface. Consistent with this, various binding observables show a temperature dependence well described by a simple two-state model. We also find important differences in the details between the two domains. While both domains exhibit well-defined binding free energy barriers, the class I barrier is significantly weaker than the one for class II. To probe this issue further, we apply our method to a PDZ domain with dual specificity for class I and II peptides, and find an analogous difference in their binding free energy barriers. Lastly, we perform a large number of fixed-temperature MC kinetics trajectories under binding conditions. These trajectories reveal significantly slower binding dynamics for the class II domain relative to class I. Our combined results are consistent with a binding mechanism in which the peptide C terminal residue binds in an initial, rate-limiting step.

Publiceringsår

2011

Språk

Engelska

Publikation/Tidskrift/Serie

PLoS Computational Biology

Volym

7

Issue

8

Dokumenttyp

Artikel i tidskrift

Förlag

Public Library of Science (PLoS)

Ämne

  • Bioinformatics and Systems Biology

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1553-7358