Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state
Characterization of binding hot spots of protein interfaces is a fundamental study in molecular biology. Many computational methods have been proposed to identify binding hot spots. However, there are few studies to assess the biological significance of binding hot spots. We introduce the notion of...
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sg-ntu-dr.10356-987652020-05-28T07:41:43Z Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state Liu, Qian Wong, Limsoon Li, Jinyan School of Computer Engineering DRNTU::Engineering::Computer science and engineering Characterization of binding hot spots of protein interfaces is a fundamental study in molecular biology. Many computational methods have been proposed to identify binding hot spots. However, there are few studies to assess the biological significance of binding hot spots. We introduce the notion of biological significance of a contact residue for capturing the probability of the residue occurring in or contributing to protein binding interfaces. We take a statistical Z-score approach to the assessment of the biological significance. The method has three main steps. First, the potential score of a residue is defined by using a knowledge-based potential function with relative accessible surface area calculations. A null distribution of this potential score is then generated from artifact crystal packing contacts. Finally, the Z-score significance of a contact residue with a specific potential score is determined according to this null distribution. We hypothesize that residues at binding hot spots have big absolute values of Z-score as they contribute greatly to binding free energy. Thus, we propose to use Z-score to predict whether a contact residue is a hot spot residue. Comparison with previously reported methods on two benchmark datasets shows that this Z-score method is mostly superior to earlier methods. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction. 2013-08-01T02:49:51Z 2019-12-06T19:59:27Z 2013-08-01T02:49:51Z 2019-12-06T19:59:27Z 2012 2012 Journal Article Liu, Q., Wong, L.,& Li, J. (2012). Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, 1824(12), 1457-1467. 1570-9639 https://hdl.handle.net/10356/98765 http://hdl.handle.net/10220/12723 10.1016/j.bbapap.2012.05.014 en Biochimica et Biophysica Acta (BBA) - proteins and proteomics |
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DRNTU::Engineering::Computer science and engineering Liu, Qian Wong, Limsoon Li, Jinyan Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
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Characterization of binding hot spots of protein interfaces is a fundamental study in molecular biology. Many computational methods have been proposed to identify binding hot spots. However, there are few studies to assess the biological significance of binding hot spots. We introduce the notion of biological significance of a contact residue for capturing the probability of the residue occurring in or contributing to protein binding interfaces. We take a statistical Z-score approach to the assessment of the biological significance. The method has three main steps. First, the potential score of a residue is defined by using a knowledge-based potential function with relative accessible surface area calculations. A null distribution of this potential score is then generated from artifact crystal packing contacts. Finally, the Z-score significance of a contact residue with a specific potential score is determined according to this null distribution. We hypothesize that residues at binding hot spots have big absolute values of Z-score as they contribute greatly to binding free energy. Thus, we propose to use Z-score to predict whether a contact residue is a hot spot residue. Comparison with previously reported methods on two benchmark datasets shows that this Z-score method is mostly superior to earlier methods. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction. |
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School of Computer Engineering |
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School of Computer Engineering Liu, Qian Wong, Limsoon Li, Jinyan |
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Article |
author |
Liu, Qian Wong, Limsoon Li, Jinyan |
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Liu, Qian |
title |
Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
title_short |
Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
title_full |
Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
title_fullStr |
Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
title_full_unstemmed |
Z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
title_sort |
z-score biological significance of binding hot spots of protein interfaces by using crystal packing as the reference state |
publishDate |
2013 |
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https://hdl.handle.net/10356/98765 http://hdl.handle.net/10220/12723 |
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1681059379441303552 |