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Kinetic Rate Constant Prediction Supports the Conformational Selection Mechanism of Protein Binding

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  • Iain H Moal
  • Paul A Bates

Abstract

The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies. Author Summary: Almost all biological processes involve proteins interacting with each other. Knowledge about how quickly proteins associate and disassociate is fundamental for understanding how proteins work together to perform biological functions. Here we look at a large set of interacting protein pairs, which are extensively characterized by many numerical values that describe the properties of their interactions. An algorithm was used to automatically construct linear equations for the association and dissociation rates by selecting and weighting important features. Upon inspecting the selected features, we conclude that the most significant factor determining the rate of association is how often the unbound proteins can adopt the shape with which their surfaces complement each other. This suggests that proteins must adopt this configuration before they bind. Secondly, the rate at which proteins dissociate is determined by how strong the interaction is once this shape has been adopted, suggesting that proteins must dissociate before they adopt a more relaxed state. This work contradicts the view that proteins bind first and then adjust their shape, and instead supports the hypothesis that proteins adopt many shapes, and only those which are in the correct configuration are selected by their binding partner.

Suggested Citation

  • Iain H Moal & Paul A Bates, 2012. "Kinetic Rate Constant Prediction Supports the Conformational Selection Mechanism of Protein Binding," PLOS Computational Biology, Public Library of Science, vol. 8(1), pages 1-13, January.
  • Handle: RePEc:plo:pcbi00:1002351
    DOI: 10.1371/journal.pcbi.1002351
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    1. Sander Woutersen & Huib J. Bakker, 1999. "Resonant intermolecular transfer of vibrational energy in liquid water," Nature, Nature, vol. 402(6761), pages 507-509, December.
    2. Mazen Ahmad & Wei Gu & Tihamér Geyer & Volkhard Helms, 2011. "Adhesive water networks facilitate binding of protein interfaces," Nature Communications, Nature, vol. 2(1), pages 1-7, September.
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    Cited by:

    1. Jan H Peters & Bert L de Groot, 2012. "Ubiquitin Dynamics in Complexes Reveal Molecular Recognition Mechanisms Beyond Induced Fit and Conformational Selection," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-10, October.
    2. Rudi Agius & Mieczyslaw Torchala & Iain H Moal & Juan Fernández-Recio & Paul A Bates, 2013. "Characterizing Changes in the Rate of Protein-Protein Dissociation upon Interface Mutation Using Hotspot Energy and Organization," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-27, September.

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