SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots.
SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots.
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DOI：
10.1038/s41598-017-08321-2
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发表时间：
2017-08-14
影响因子：
4.6
通讯作者：
Bonvin AMJJ
中科院分区：
文献类型：
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作者：
Moreira IS;Koukos PI;Melo R;Almeida JG;Preto AJ;Schaarschmidt J;Trellet M;Gümüş ZH;Costa J;Bonvin AMJJ
我们提出了SpotOn，一个Web服务器来识别和分类界面残留物热点（HS）和空点（NS）。SpotON实现了一个强大的算法，在一个独立的测试集上的准确度为0.95，灵敏度为0.98。预测器是使用集成机器学习方法开发的，其中对小类进行了上采样。它基于蛋白质3D结构和序列，使用各种特征对53个复合物进行了训练。SpotOn Web界面可在http://milou.science.uu.nl/services/SPOTON/上免费获得。
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/.