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Protein Eng Des Sel. 2007 Mar;20(3):99-108. Epub 2007 Feb 21.

Design of MHC I stabilizing peptides by agent-based exploration of sequence space.

Author information

1
Center for Membrane Proteomics, Institute of Organic Chemistry and Chemical Biology, Johann Wolfgang Goethe-Universit├Ąt, Siesmayerstr. 70, D-60323 Frankfurt am Main, Germany. hiss@bioinformatik.uni-frankfurt.de

Abstract

Identification of molecular features that determine peptide interaction with major histocompatibility complex I (MHC I) is essential for vaccine development. We have developed a concept for peptide design by combining an agent-based artificial ant system with artificial neural networks. A jury of feedforward networks classifies octapeptides that are recognized by mouse MHC I protein H-2K(b). Prediction accuracy yielded a correlation coefficient of 0.94. Peptides were designed in machina by the artificial ant system and tested in vitro for their MHC I stabilizing effect. The behavior of the search agents during the design process was controlled by the jury network. The experimentally determined prediction accuracy was 89% for the designed stabilizing and 95% for the non-stabilizing peptides. Novel H-2K(b) stabilizing peptides were conceived that reveal extensions of known residue motifs. The combined network-agent system recognized context dependencies of residue positions. A diverse set of novel sequences exhibiting substantial activity was generated.

PMID:
17314106
DOI:
10.1093/protein/gzl054
[Indexed for MEDLINE]

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