Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots

Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However,...

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Main Authors: Liu, Qian, Hoi, Steven Chu Hong, Kwoh, Chee Keong, Wong, Limsoon, Li, Jinyan
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2014
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Online Access:https://hdl.handle.net/10356/102334
http://hdl.handle.net/10220/18903
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1023342022-02-16T16:27:01Z Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots Liu, Qian Hoi, Steven Chu Hong Kwoh, Chee Keong Wong, Limsoon Li, Jinyan School of Computer Engineering DRNTU::Engineering::Computer science and engineering Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results This work proposes a new method, βACVASA, to predict the change of binding free energy after alanine mutations. βACVASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector (ACV). A β contact between two atoms is a direct contact without being interrupted by any other atom between them. A β contact’s potential contribution to protein binding is also supposed to be inversely proportional to its ASA to follow the water exclusion hypothesis of binding hot spots. Tested on a dataset of 396 alanine mutations, our method is found to be superior in classification performance to many other methods, including Robetta, FoldX, HotPOINT, an ACV method of β contacts without ASA integration, and ACVASA methods (similar to βACVASA but based on distance-cutoff contacts). Based on our data analysis and results, we can draw conclusions that: (i) our method is powerful in the prediction of binding free energy change after alanine mutation; (ii) β contacts are better than distance-cutoff contacts for modeling the well-organized protein-binding interfaces; (iii) β contacts usually are only a small fraction number of the distance-based contacts; and (iv) water exclusion is a necessary condition for a residue to become a binding hot spot. Conclusions βACVASA is designed using the advantages of both β contacts and water exclusion. It is an excellent tool to predict binding free energy changes and binding hot spots after alanine mutation. Published version 2014-03-14T04:45:59Z 2019-12-06T20:53:36Z 2014-03-14T04:45:59Z 2019-12-06T20:53:36Z 2014 2014 Journal Article Liu, Q., Hoi, S. C. H., Kwoh, C. K., Wong, L., & Li, J. (2014). Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots. BMC Bioinformatics, 15(1), 57-. 1471-2105 https://hdl.handle.net/10356/102334 http://hdl.handle.net/10220/18903 10.1186/1471-2105-15-57 24568581 en BMC bioinformatics This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Liu, Qian
Hoi, Steven Chu Hong
Kwoh, Chee Keong
Wong, Limsoon
Li, Jinyan
Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
description Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results This work proposes a new method, βACVASA, to predict the change of binding free energy after alanine mutations. βACVASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector (ACV). A β contact between two atoms is a direct contact without being interrupted by any other atom between them. A β contact’s potential contribution to protein binding is also supposed to be inversely proportional to its ASA to follow the water exclusion hypothesis of binding hot spots. Tested on a dataset of 396 alanine mutations, our method is found to be superior in classification performance to many other methods, including Robetta, FoldX, HotPOINT, an ACV method of β contacts without ASA integration, and ACVASA methods (similar to βACVASA but based on distance-cutoff contacts). Based on our data analysis and results, we can draw conclusions that: (i) our method is powerful in the prediction of binding free energy change after alanine mutation; (ii) β contacts are better than distance-cutoff contacts for modeling the well-organized protein-binding interfaces; (iii) β contacts usually are only a small fraction number of the distance-based contacts; and (iv) water exclusion is a necessary condition for a residue to become a binding hot spot. Conclusions βACVASA is designed using the advantages of both β contacts and water exclusion. It is an excellent tool to predict binding free energy changes and binding hot spots after alanine mutation.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Liu, Qian
Hoi, Steven Chu Hong
Kwoh, Chee Keong
Wong, Limsoon
Li, Jinyan
format Article
author Liu, Qian
Hoi, Steven Chu Hong
Kwoh, Chee Keong
Wong, Limsoon
Li, Jinyan
author_sort Liu, Qian
title Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
title_short Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
title_full Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
title_fullStr Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
title_full_unstemmed Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
title_sort integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots
publishDate 2014
url https://hdl.handle.net/10356/102334
http://hdl.handle.net/10220/18903
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