Reconstructing and Decomposing Protein Energy Landscapes to Organize Structure Spaces and Reveal Biologically-active States

The concept of energy landscape has become a useful construction in protein modeling due to its ability to relate structures and structural dynamics to function. While great progress is being made in probing energy landscapes, it remains unclear how to reconstruct the landscape from computed structures. Recently, our laboratories have made headway in this direction via concepts from topological and statistical analysis of spatial data. In this paper, we propose a novel approach to reconstruct the underlying energy landscape populated by computed/sampled energy-evaluated structures of a molecule and decompose it into basins of attraction. We demonstrate that such a construction not only allows deep analysis of the efficacy of a structure computation algorithm and the energy function it employs in the first place, but, more importantly, makes important steps toward addressing the open decoy selection problem in template-free protein structure prediction.

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