(672d) Quantifying Signal Propagation and Conformational Changes in Allosteric Proteins

Authors: 
Ortiz, V., Columbia University
Ribeiro, A. A. S. T., Columbia University

Allostery connects subtle changes in a protein's potential energy surface to significant changes in its function. Understanding this phenomenon and predicting its occurrence are major goals of current research in biophysics and molecular biology. At the microscopic level, protein energetics is characterized by a balance between different inter-atomic interactions, with small perturbations at specific sites potentially leading to major changes in conformational distributions. Therefore, a thorough characterization of allostery requires understanding of two aspects: (1) how energy propagates through the protein structure, and (2) which regions of the protein are likely to suffer structural deformations as a response to the applied perturbation.

On the first aspect, we have developed a new energy-based network analysis method, which allows characterization of signaling pathways in proteins. The method assumes that signals travel more efficiently through residues that have strong inter-atomic interactions, and is able to correctly identify important residues for allosteric signal propagation in the allosteric enzyme imidazole glycerol phosphate synthase. In addition, we introduce a quantity named energetic coupling, which is able to discriminate allosterically active mutants of a known allosterically regulated protein, the lactose repressor (LacI). Commonly used protein structure networks based on correlation coefficients or number of inter-residue contacts, are not able to reproduce our results.

On the second aspect, we show that the calculation and analysis of atomic elastic constants of LacI, highlights regions that are particularly prone to suffer structural deformation, and are experimentally linked to allosteric function. The calculations are based on a high resolution, all-atom description of the protein, but are computationally inexpensive when compared to methods employing the same resolution. Lower resolution models are shown to yield qualitatively different results, indicating the importance of adequately describing the local environment surrounding the different parts of the protein.