Out of one, many: Exploiting intrinsic motions to explore protein structure spaces

Nearly all cellular processes involve proteins structurally rearranging to accommodate molecular partners. The energy landscape underscores the inherent nature of proteins as dynamic molecules interconverting between structures with varying energies. Reconstructing a protein’s energy landscape holds the key to characterizing the structural dynamics and its regulation of protein function. In practice, the disparate spatio-temporal scales spanned by the slow dynamics challenge wet and dry laboratories. The growing number of deposited structures for proteins central to human biology presents an opportunity to infer the relevant dynamics. Recent computational efforts using extrinsic modes of motion as variables have successfully reconstructed detailed energy landscapes of several medium-size proteins. Here we investigate the extent to which one can reconstruct the energy landscape of a protein in the absence of sufficient, wet-laboratory structural data. We do so by integrating intrinsic modes of motion extracted off a single structure in a stochastic optimization framework that supports the plug-and-play of different variable selection strategies. We demonstrate that, while knowledge of more wetlaboratory structures yields better-reconstructed landscapes, precious information can be obtained even when one structural model is available. The presented work opens up interesting venues of research on structure-based inference of dynamics.