Improving protein tertiary structure prediction with conformational propensities of amino acid residues

The study of proteins and the prediction of their three-dimensional (3-D) structure is one of the most challenging problems in Structural Bioinformatics. Over the last years, several computational strategies have been proposed as a solution to this problem. As revealed by recent CASP experiments, the best results have been achieved by knowledge-based methods. Despite the advances in the development of computational methods, systems and algorithms for solving this complex problem, further research remains to be done. In this paper, we use a computational strategy to obtain structural information from experimentally determined protein structures called Angle Probability List (APL) combined with a distributed knowledge-based Genetic Algorithm to predict the 3-D structure of proteins. The proposed method has been tested with eight protein sequences. The results show that predicted 3-D structures are topologically comparable to their correspondent experimental ones.