Detection and characterization of nonspecific, sparsely populated binding modes in the early stages of complexation. Issue 13 (18th March 2015) - Cardone, Antonio; Bornstein, Aaron; Pant, Harish C.; Brady, Mary; Sriram, Ram; Hassan, Sergio A.
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. Abstract : A method is developed to study protein complexation in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific sparsely populated binding modes. 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 in concentrated multispecies, multiprotein systems.