Analysis of Inducer and Operator Binding for Cyclic-AMP Receptor Protein Mutants

TL;DR

This study compares two allosteric models, MWC and KNF, to understand CRP mutants' behavior, showing MWC slightly better fits and more consistent with structural data, with implications for predicting mutant interactions and gene regulation.

Contribution

The paper demonstrates that both models can explain CRP mutant data, with MWC providing more accurate and structurally consistent parameters, advancing understanding of allosteric regulation.

Findings

Both models fit mutant data well

MWC model aligns better with structural knowledge

Framework predicts mutant interactions and gene regulation

Abstract

Allosteric transcription factors undergo binding events both at their inducer binding sites as well as at distinct DNA binding domains, and it is often difficult to disentangle the structural and functional consequences of these two classes of interactions. In this work, we compare the ability of two statistical mechanical models - the Monod-Wyman-Changeux (MWC) and the Koshland-N\'emethy-Filmer (KNF) models of protein conformational change - to characterize the multi-step activation mechanism of the broadly acting cyclic-AMP receptor protein (CRP). We first consider the allosteric transition resulting from cyclic-AMP binding to CRP, then analyze how CRP binds to its operator, and finally investigate the ability of CRP to activate gene expression. In light of these models, we examine data from a beautiful recent experiment that created a single-chain version of the CRP homodimer, thereby enabling each subunit to be mutated separately. Using this construct, six mutants were created using all possible combinations of the wild type subunit, a D53H mutant subunit, and an S62F mutant subunit. We demonstrate that both the MWC and KNF models can explain the behavior of all six mutants using a small, self-consistent set of parameters. In comparing the results, we find that the MWC model slightly outperforms the KNF model in the quality of its fits, but more importantly the parameters inferred by the MWC model are more in line with structural knowledge of CRP. In addition, we discuss how the conceptual framework developed here for CRP enables us to not merely analyze data retrospectively, but has the predictive power to determine how combinations of mutations will interact, how double mutants will behave, and how each construct would regulate gene expression.