Combining machine learning and optimization techniques to determine 3-D structures of polypeptides

Authors:
Márcio Dorn;Luciana S. Buriol;Luis C. Lamb
Affiliations:
Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil;Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil;Institute of Informatics, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
Venue:
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Year:
2011

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Abstract

One of the main research problems in Structural Bioinformatics is the analysis and prediction of three-dimensional structures (3-D) of polypeptides or proteins. The 1990's Genome projects resulted in a large increase in the number of protein sequences. However, the number of identified 3-D protein structures has not followed the same trend. The determination of protein structure is experimentally expensive and time consuming. This makes scientists largely dependent on computational methods that can predict correct 3-D protein structures only from extended and full amino acid sequences. Several computational methodologies and algorithms have been proposed as a solution to the Protein Structure Prediction (PSP) problem. We briefly describe the AI techniques we have been used to tackle this problem.