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Molecules 2018, 23(1), 216; https://doi.org/10.3390/molecules23010216

From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction

1,†,‡
and
1,2,3,†,‡,*
1
Department of Computer Science, George Mason University, Fairfax, VA 22030, USA
2
Department of Bioengineering, George Mason University, Fairfax, VA 22030, USA
3
School of Systems Biology, George Mason University, Mansassas, VA 20110, USA
Current address: 4400 University Dr., MS 4A5, Fairfax, VA 22030, USA.
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 8 December 2017 / Revised: 6 January 2018 / Accepted: 11 January 2018 / Published: 19 January 2018
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Abstract

Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins. View Full-Text
Keywords: template-free protein structure prediction; decoy selection; conformational space; energy landscape; basins; Pareto optimality template-free protein structure prediction; decoy selection; conformational space; energy landscape; basins; Pareto optimality
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Akhter, N.; Shehu, A. From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction. Molecules 2018, 23, 216.

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