10.1186/1471-2105-15-57BMC Bioinformatics151-BBMI

A Benedix

AA Bogan

BC Barber

C Pallara

Chee Keong Kwoh

DG Kirkpatrick

E Guney

G Schreiber

IH Moal

J Li

J Mintseris

J Schymkowitz

J Wells

JF Xia

Jinyan Li

JM Martins

KI Cho

KS Thorn

L Deng

L Wang

Limsoon Wong

MDS Kumar

N Tuncbag

P Chen

Q Liu

Qian Liu

R Guerois

R Moretti

S Grosdidier

SA Assi

Steven CH Hoi

T Clackson

T Kortemme

TB Fischer

X Zhu

Y Dehouck

Y Ofran

BMC Bioinformatics

PubMed

Background: 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. © 2014 Liu et al.; licensee BioMed Central Ltd

Liu, Q

Hoi, SCH

Kwoh, CK

Wong, L

Li, J

OPUS - University of Technology Sydney

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, 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 versio

Liu, Qian

Hoi, Steven Chu Hong

Kwoh, Chee Keong

Wong, Limsoon

Li, Jinyan

DR-NTU (Digital Repository of NTU)

LIU, Qian

HOI, Steven C. H.

KWOH, Chee Keong

WONG, Limsoon

LI, Jinyan

Institutional Knowledge at Singapore Management University

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

Liu, Q.

Hoi, S.C.H.

Kwoh, C.K.

Wong, L.

Li, J.

ScholarBank@NUS

Chee Kwoh

Springer - Publisher Connector

Crossref

Digital Repository - Nanyang Technological University

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=4948&amp;context=sis_research

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

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OPUS - University of Technology Sydney

DR-NTU (Digital Repository of NTU)

Institutional Knowledge at Singapore Management University

ScholarBank@NUS

Institutional Knowledge at Singapore Management University

Springer - Publisher Connector

Crossref

Springer - Publisher Connector

Digital Repository - Nanyang Technological University