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Bio-AIMS Chemoinformatics Web tools for proteins
1 , 2, 3 , 1 , 4 , * 1 , 5 , 1, 6
1  RNASA-IMEDIR Group, Information and Communication Technologies Department, Faculty of Computer Science, University of A Coruna, 15071 A Coruña, Spain
2  Department of Organic Chemistry II, Faculty of Science and Technology, University of the Basque Country UPV/EHU, 48940 Leioa, Vizcaya, Spain
3  IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Vizcaya, Spain
4  Stanford Cancer Institute, Stanford University, C.J. Huang Building, 780 Welch Road, Palo Alto, CA 94304, USA
5  Grupo BioFarma-USEF, Departamento de Farmacología, Facultad de Farmacia, Campus Universitario Sur s/n, 15782 Santiago de Compostela, Spain
6  Instituto de Investigación Biomédica de A Coruña (INIBIC), Complexo Hospitalario Universitario de A Coruña (CHUAC), 15006 A Coruña, Spain


The peptide biological screening represents a difficult task due to the complexity of the amino-acid sequences. One solution is the encoding of the molecular information using complex networks or graphs of the peptides into QSAR-like models in Web tools. Bio-AIMS contains free Web tools on an Artificial Intelligence Model Server in Biosciences: These in silico peptide screening tools are implementing models to predict different protein activities, drug – protein and protein – protein interactions. The inputs are using 3D protein structures or 1D peptide amino acid sequences and the SMILES formulas for drugs, and the classification models are based on Machine Learning techniques. The Web tools are implemented using Python, PHP and XHTML programming languages.

Keywords: molecular information, Machine Learning, protein graphs, Python scripts, QSAR models, Web tools