Reference-Free Identification of Dynamic Structural Domains in Proteins: Comparison of Numeric Predictions with NMR Measurements

Abstract

Understanding proteins’ functionalities, which are intimately related with their structural conformations, require a robust characterization of conformational changes which occur in proteins in response to external impacts, as well as spontaneously. This presentation introduces a novel numeric methodology to identify dynamic structural domains in proteins, which is based on the recent theoretic invention [M. Stepanova, Phys. Rev. E76 (2007) 051918]. The methodology employs a fundamental, reference-free approach including identification of essential collective coordinates by the covariance analysis of molecular dynamics trajectories, construction of the Mori projection operator with these collective coordinates, and analysis of the corresponding generalized Langevin equations (GLE). The dynamic domains are identified as groups of atoms that show a dynamic coupling in the GLE. Since the methodology is based on a rigorous theory, the outcomes are physically transparent: the dynamic domains are associated with regions of relative rigidity, whereas off-domain regions are relatively soft. In the presentation, applications of the new structural analysis are demonstrated for the examples of protein G and prion proteins. Experimental NMR-based model-free S2 profiles, random coil indexes, and amplitude correlation data are compared with the numeric analysis, which includes (i) robust systems of dynamic structural domains and (ii) dynamically consistent local flexibility descriptors. It is shown that these numerical results agree well with the available NMR experiments. It is also demonstrated that the dynamic domains and the corresponding flexibility descriptors represent highly sensitive scores for characterization and comparison of proteins’ conformations. Even very subtle changes in collective behaviors in macromolecules can be easily detected, visualized, and interpreted. The introduced methodology provides the community with a novel powerful tool for interpretation of NMR experiments, as well as for characterization, comparison, and dynamic analysis of proteins’ conformational behaviors.