Detection and characterization of nonspecific,sparsely populated binding modes in the early stages of complexation |
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Authors: | Antonio Cardone Aaron Bornstein Harish C Pant Mary Brady Ram Sriram Sergio A Hassan |
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Institution: | 1. Software and System Division, National Institute of Standards and Technology, Gaithersburg, Maryland;2. Institute for Advanced Computer Studies, University of Maryland, College Park, Maryland;3. Mathematics and Computer Science, Goucher College, Baltimore, Maryland;4. Laboratory of Neurochemistry, NINDS, National Institutes of Health, Bethesda, Maryland;5. Division of Computational Bioscience, Center for Molecular Modeling, CIT, National Institutes of Health, Bethesda, Maryland |
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Abstract: | A method is proposed to study protein–ligand binding in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific, sparsely populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first‐encounter modes are metastable states from which stable (prerelaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide–protein complex. The peptide adopts several low‐population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. © 2015 Wiley Periodicals, Inc. |
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Keywords: | protein– protein association protein aggregation complex formation configurational‐bias Monte Carlo nonspecific interactions solvent effects implicit solvent model |
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