How the "Folding Funnel" Depends on Size and Structure of Proteins? A View from the Scoring Function Perspective

Sheng-You Huang; Gordon K. Springer

doi:10.1109/TST.2013.6616520

Tsinghua Science and Technology 2013, 18(5): 462-468 https://doi.org/10.1109/TST.2013.6616520

Open Access | Issue | Published: 03 October 2013

How the "Folding Funnel" Depends on Size and Structure of Proteins? A View from the Scoring Function Perspective

Show Author's Information Hide Author's Information Sheng-You Huang(

), Gordon K. Springer

Research Support Computing, University of Missouri Bioinformatics Consortium and Department of Computer Science, University of Missouri, Columbia, MO 65211, USA

Keywords:

energy landscape, folding funnel, protein structure prediction, scoring function, protein folding

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Huang S-Y, Springer GK. How the "Folding Funnel" Depends on Size and Structure of Proteins? A View from the Scoring Function Perspective. Tsinghua Science and Technology, 2013, 18(5): 462-468. https://doi.org/10.1109/TST.2013.6616520

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Abstract

It has been well accepted that the folding energy landscape may resemble a funnel according to the theory of protein folding. This theory of "folding funnel" has been extensively studied and thought to play an important role in guiding the sampling process of the protein folding and refinement in protein structure prediction. Here, we have investigated the relationship between the "funnel likeness" of protein folding and the size/structure of the proteins based on a set of non-homologous proteins we have recently evaluated using a statistical mechanics-based scoring function ITScorePro. It was found that larger proteins that consist of more helix/sheet structures tend to have a higher score-Root Mean Square Deviation (RMSD) correlation (or a more funnel like energy landscape). Another measurement in protein folding, Z-score, has also shown some correlation with the size of the proteins. As expected, proteins with a better "olding funnel likeness" (or score-RMSD correlation) tend to have a better-predicted conformation with a lower RMSD from their native structures. These findings can be extremely valuable for the development and improvement of sampling and scoring algorithms for protein structure prediction.

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About this article

How the "Folding Funnel" Depends on Size and Structure of Proteins? A View from the Scoring Function Perspective

Show Author's information Hide Author's Information Sheng-You Huang(

), Gordon K. Springer

Research Support Computing, University of Missouri Bioinformatics Consortium and Department of Computer Science, University of Missouri, Columbia, MO 65211, USA

Abstract

Keywords: energy landscape, folding funnel, protein structure prediction, scoring function, protein folding

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Received: 09 August 2013

Revised: 01 September 2013

Accepted: 02 September 2013

Published: 03 October 2013

Issue date: October 2013

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Acknowledgements

Computations for the scoring evaluations were performed on the HPC resources at the University of Missouri Bioinformatics Consortium (UMBC). The support of the UMBC is greatly appreciated.