1. proABC-2: PRediction Of AntiBody Contacts v2 and its application to information-driven docking
- Author
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Ambrosetti, F, Olsen, T H, Olimpieri, P P, Jiménez-García, B, Milanetti, E, Marcatilli, P, Bonvin, A M J J, Sub NMR Spectroscopy, NMR Spectroscopy, Sub NMR Spectroscopy, and NMR Spectroscopy
- Subjects
Statistics and Probability ,Neural Networks ,AcademicSubjects/SCI01060 ,Computer science ,medicine.drug_class ,Computational biology ,Antigen-Antibody Complex ,Machine learning ,computer.software_genre ,Monoclonal antibody ,Convolutional neural network ,Biochemistry ,Computer ,03 medical and health sciences ,0302 clinical medicine ,Antigen ,medicine ,Molecular Biology ,Antibody ,030304 developmental biology ,0303 health sciences ,Binding Sites ,biology ,business.industry ,030302 biochemistry & molecular biology ,Binding Sites, Antibody ,Software ,Algorithms ,Neural Networks, Computer ,Rational design ,Applications Notes ,Structural Bioinformatics ,Computer Science Applications ,Computational Mathematics ,Computational Theory and Mathematics ,Docking (molecular) ,biology.protein ,Paratope ,Artificial intelligence ,business ,computer ,030217 neurology & neurosurgery - Abstract
Motivation Monoclonal antibodies are essential tools in the contemporary therapeutic armory. Understanding how these recognize their antigen is a fundamental step in their rational design and engineering. The rising amount of publicly available data is catalyzing the development of computational approaches able to offer valuable, faster and cheaper alternatives to classical experimental methodologies used for the study of antibody–antigen complexes. Results Here, we present proABC-2, an update of the original random-forest antibody paratope predictor, based on a convolutional neural network algorithm. We also demonstrate how the predictions can be fruitfully used to drive the docking in HADDOCK. Availability and implementation The proABC-2 server is freely available at: https://wenmr.science.uu.nl/proabc2/. Supplementary information Supplementary data are available at Bioinformatics online.
- Published
- 2020
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