Using Energy Landscape Theory to Uncover the Organization of Conformational Space of Proteins in Their Native States.
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The functional motions of proteins navigate on rugged energy landscapes. Hence, mapping of these multidimensional landscapes into lower dimensional manifolds is imperative for gaining deeper insights into the functional dynamics. In the present work we implement novel computational schemes and means of analysis to characterize the topography of conformational space of selected proteins and also to elucidate their functional implications. The present thesis is divided into two parts, where we focus on the case studies of the intrinsically disordered histone tails and the representative allosteric protein Adenlyate Kinase. In particular, analyzing the energy landscapes of histone tails, we find preferential clustering of transient secondary structural elements in the conformational ensembles, which have a dramatic impact on the chain statistics, conformational dynamics and the binding pathways. In the study of Adenylate Kinase we use a novel nonlinear order parameter to rigorously estimate the free energy difference between allosteric states and map out the plausible pathway of transition, which reveals important structural and thermodynamic insights about the mechanism of allostery in Adenylate Kinase. Taken together our findings indicate that the organization of conformational space of functional proteins is delicately crafted to ensure efficient functional regulation and robust response to external signals.