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Title: Incorporating knowledge of secondary structures in a L-system-based encoding for protein folding
Author(s): Ochoa, Gabriela
Escuela, Gabi
Krasnogor, Natalio
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Editor(s): Talbi, E-G
Liardet, P
Collet, P
Lutton, E
Schoenauer, M
Citation: Ochoa G, Escuela G & Krasnogor N (2006) Incorporating knowledge of secondary structures in a L-system-based encoding for protein folding. In: Talbi E, Liardet P, Collet P, Lutton E & Schoenauer M (eds.) Artificial Evolution: 7th International Conference, Evolution Artificielle, EA 2005, Lille, France, October 26-28, 2005, Revised Selected Papers. Lecture Notes in Computer Science, 3871. Berlin Heidelberg: Springer, pp. 247-258.;
Issue Date: 2006
Date Deposited: 20-Feb-2013
Series/Report no.: Lecture Notes in Computer Science, 3871
Abstract: An encoding scheme for protein folding on lattice models, inspired by parametric L-systems, was proposed. The encoding incorporates problem domain knowledge in the form of predesigned production rules that capture commonly known secondary structures: α-helices and β-sheets. The ability of this encoding to capture protein native conformations was tested using an evolutionary algorithm as the inference procedure for discovering L-systems. Results confirmed the suitability of the proposed representation. It appears that the occurrence of motifs and sub-structures is an important component in protein folding, and these sub-structures may be captured by a grammar-based encoding. This line of research suggests novel and compact encoding schemes for protein folding that may have practical implications in solving meaningful problems in biotechnology such as structure prediction and protein folding.
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DOI Link: 10.1007/11740698_22
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