title: Stoichiometries and affinities of interacting proteins from concentration series of solution scattering data: decomposition by least squares and quadratic optimization.
abstract: In studying interacting proteins, complementary insights are provided by analyzing both the association model (the stoichiometry and affinity constants of the intermediate and final complexes) and the quaternary structure of the resulting complexes. Many current methods for analyzing protein interactions either give a binary answer to the question of association and no information about quaternary structure or at best provide only part of the complete picture. Presented here is a method to extract both types of information from X-ray or neutron scattering data for a series of equilibrium mixtures containing the initial components at different concentrations. The method determines the association pathway and constants, along with the scattering curves of the individual members of the mixture, so as to best explain the scattering data for the mixtures. The derived curves then enable reconstruction of the intermediate and final complexes. Using simulated solution scattering data for four hetero-oligomeric complexes with different structures, molecular weights and association models, it is demonstrated that this method accurately determines the simulated association model and scattering profiles for the initial components and complexes. Recognizing that experimental mixtures contain static contaminants and nonspecific complexes with the lowest affinities (inter-particle interference) as well as the desired specific complex(es), a new analytical method is also employed to extend this approach to evaluating the association models and scattering curves in the presence of static contaminants, testing both a nonparticipating monomer and a large homo-oligomeric aggregate. It is demonstrated that the method is robust to both random noise and systematic noise from such contaminants, and the treatment of nonspecific complexes is discussed. Finally, it is shown that this method is applicable over a large range of weak association constants typical of specific but transient protein-protein complexes.
authors.affiliation: Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Himanshu
authors.initials: H
authors.lastname: Chandola
authors.affiliation: Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.
authors.forename: Tim E
authors.initials: TE
authors.lastname: Williamson
authors.affiliation: Department of Statistics, Purdue University, West Lafayette, IN 47907, USA.
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Craig
authors.affiliation: Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA ; Markey Center for Structural Biology, Purdue Cancer Center and Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA.
authors.forename: Alan M
authors.initials: AM
authors.lastname: Friedman
authors.affiliation: Department of Computer Science, Dartmouth College, Hanover, NH 03755, USA.
authors.forename: Chris
authors.initials: C
authors.lastname: Bailey-Kellogg
keywords: interacting proteins; solution scattering; solution series; stoichiometry