Abstract
Significant efforts in wet and dry laboratories are devoted to resolving molecular structures. In particular, computational methods can now compute thousands of tertiary structures that populate the structure space of a protein molecule of interest. These advances are now allowing us to turn our attention to analysis methodologies that are able to organize the computed structures in order to highlight functionally relevant structural states. In this paper, we propose a methodology that leverages community detection methods, designed originally to detect communities in social networks, to organize computationally probed protein structure spaces. We report a principled comparison of such methods along several metrics on proteins of diverse folds and lengths. We present a rigorous evaluation in the context of decoy selection in template-free protein structure prediction. The results make the case that network-based community detection methods warrant further investigation to advance analysis of protein structure spaces for automated selection of functionally relevant structures.
Highlights
The structure which the peptide-bonded amino acids pack in three-dimensional (3d) space in a protein molecule is recognized to be central to the biological activities of a protein in the living cell [1]
Proof-of-concept presentation of this approach in [10], we show how one can leverage a graph-based organization of tertiary structures to identify with community detection methods
In addition to providing a principled evaluation of state-of-the-art, representative community detection methods for their ability to identify communities, we evaluate the utility of identifying communities for decoy selection
Summary
The (tertiary) structure which the peptide-bonded amino acids pack in three-dimensional (3d) space in a protein molecule is recognized to be central to the biological activities of a protein in the living cell [1]. Provided a protein amino-acid sequence, these methods seek tertiary structures that are local minima of some selected energy/cost function, using this function as an indicator of biological activity. These functions are known to be inherently inaccurate; that is, structures
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