SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots

Abstract We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble ma...

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Autores principales:	Irina S. Moreira, Panagiotis I. Koukos, Rita Melo, Jose G. Almeida, Antonio J. Preto, Joerg Schaarschmidt, Mikael Trellet, Zeynep H. Gümüş, Joaquim Costa, Alexandre M. J. J. Bonvin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bcfd8d40f8554bfebb790c4ceb05f28f
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spelling	oai:doaj.org-article:bcfd8d40f8554bfebb790c4ceb05f28f2021-12-02T16:06:39ZSpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots10.1038/s41598-017-08321-22045-2322https://doaj.org/article/bcfd8d40f8554bfebb790c4ceb05f28f2017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08321-2https://doaj.org/toc/2045-2322Abstract We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble machine learning approach with up-sampling of the minor class. It was trained on 53 complexes using various features, based on both protein 3D structure and sequence. The SpotOn web interface is freely available at: http://milou.science.uu.nl/services/SPOTON/ .Irina S. MoreiraPanagiotis I. KoukosRita MeloJose G. AlmeidaAntonio J. PretoJoerg SchaarschmidtMikael TrelletZeynep H. GümüşJoaquim CostaAlexandre M. J. J. BonvinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Irina S. Moreira Panagiotis I. Koukos Rita Melo Jose G. Almeida Antonio J. Preto Joerg Schaarschmidt Mikael Trellet Zeynep H. Gümüş Joaquim Costa Alexandre M. J. J. Bonvin SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots
description	Abstract We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble machine learning approach with up-sampling of the minor class. It was trained on 53 complexes using various features, based on both protein 3D structure and sequence. The SpotOn web interface is freely available at: http://milou.science.uu.nl/services/SPOTON/ .
format	article
author	Irina S. Moreira Panagiotis I. Koukos Rita Melo Jose G. Almeida Antonio J. Preto Joerg Schaarschmidt Mikael Trellet Zeynep H. Gümüş Joaquim Costa Alexandre M. J. J. Bonvin
author_facet	Irina S. Moreira Panagiotis I. Koukos Rita Melo Jose G. Almeida Antonio J. Preto Joerg Schaarschmidt Mikael Trellet Zeynep H. Gümüş Joaquim Costa Alexandre M. J. J. Bonvin
author_sort	Irina S. Moreira
title	SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots
title_short	SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots
title_full	SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots
title_fullStr	SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots
title_full_unstemmed	SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots
title_sort	spoton: high accuracy identification of protein-protein interface hot-spots
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/bcfd8d40f8554bfebb790c4ceb05f28f
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SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots

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