ArticlePLoS computational biology2011
Binding free energy landscape of domain-peptide interactions.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Molecular Modelling in Bioactive Peptide Discovery and Characterisation.Biomolecules · 2025Review
- Rapid prediction of crucial hotspot interactions for icosahedral viral capsid self-assembly by energy landscape atlasing validated by mutagenesis.PLoS computational biology · 2020Article
- Computer-aided design of amino acid-based therapeutics: a review.Drug design, development and therapy · 2018Review
- Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell.Chemical reviews · 2016Review
- Computational design of selective peptides to discriminate between similar PDZ domains in an oncogenic pathway.Journal of molecular biology · 2015Article
- Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening.PLoS computational biology · 2013Article
- Coupled folding-binding in a hydrophobic/polar protein model: impact of synergistic folding and disordered flanks.Biophysical journal · 2012Article
- The role of flexibility and conformational selection in the binding promiscuity of PDZ domains.PLoS computational biology · 2012Article
- Binding of two intrinsically disordered peptides to a multi-specific protein: a combined Monte Carlo and molecular dynamics study.PLoS computational biology · 2012Article
- The impact of small molecule binding on the energy landscape of the intrinsically disordered protein C-myc.PloS one · 2012Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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