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Abstract:
Intrinsically disordered regions are predicted to exist in a
significant fraction of proteins encoded in eukaryotic genomes. The
high levels of conformational plasticity of this class of proteins endows
them with unique capacities to act in functional modes not achievable
by folded proteins, but also places their molecular characterization
beyond the reach of classical structural biology. New techniques are
therefore required to understand the relationship between primary
sequence and biological function in this class of proteins. Although
dependences of some NMR parameters such as chemical shifts (CSs) or residual dipolar couplings (RDCs) on structural
propensity are known, so that sampling regimes are often inferred from experimental observation, there is currently no
framework that allows for a statistical mapping of the available Ramachandran space of each amino acid in terms of
conformational propensity. In this study we develop such an approach, combining highly efficient conformational sampling with
ensemble selection to map the backbone conformational sampling of IDPs on a residue specific level. By systematically analyzing
the ability of NMR data to map the conformational landscape of disordered proteins, we identify combinations of RDCs and CSs
that can be used to raise conformational degeneracies inherent to different data types, and apply these approaches to characterize
the conformational behavior of two intrinsically disordered proteins, the K18 domain from Tau protein and NTAIL from measles
virus nucleoprotein. In both cases, we identify the enhanced populations of turn and helical regions in key regions of the proteins,
as well as contiguous strands that show clear and enhanced polyproline II sampling.
