|Appears in Collections:||Computing Science and Mathematics Book Chapters and Sections|
|Title:||Evolving L-systems to capture protein structure native conformations|
van, Hemert J
|Citation:||Escuela G, Ochoa G & Krasnogor N (2005) Evolving L-systems to capture protein structure native conformations. In: Keijzer M, Tettamanzi A, Collet P, van Hemert J, Tomassini M (ed.). Genetic Programming: 8th European Conference, EuroGP 2005, Lausanne, Switzerland, March 30-April 1, 2005, Proceedings. Lecture Notes in Computer Science, 3447, Berlin Heidelberg: Springer, pp. 74-84.|
|Series/Report no.:||Lecture Notes in Computer Science, 3447|
|Abstract:||A protein is a linear chain of amino acids that folds into a unique functional structure, called its native state. In this state, proteins show repeated substructures like alpha helices and beta sheets. This suggests that native structures may be captured by the formalism known as Lindenmayer systems (L-systems). In this paper an evolutionary approach is used as the inference procedure for folded structures on simple lattice models. The algorithm searches the space of L-systems which are then executed to obtain the phenotype, thus our approach is close to Grammatical Evolution. The problem is to find a set of rewriting rules that represents a target native structure on the lattice model. The proposed approach has produced promising results for short sequences. Thus the foundations are set for a novel encoding based on L-systems for evolutionary approaches to both the Protein Structure Prediction and Inverse Folding Problems.|
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