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

• Autor(a) principal: Moreira, Irina S.
• Data de Publicação: 2017
• Outros Autores: Koukos, Panagiotis I., Melo, Rita, Almeida, José G., Preto, Antonio J., Schaarschmidt, Joerg, Trellet, Mikael, Gümüş, Zeynep H, Costa, Joaquim, Bonvin, Alexandre M. J. J.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/108366; https://doi.org/10.1038/s41598-017-08321-2
• topic: Animals; Binding Sites; Humans; Machine Learning; Protein Binding; Protein Interaction Mapping; Sequence Analysis, Protein; Software

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/ .