NDLI: Peptide design by artificial neural networks and computer-based evolutionary search

Content Provider	PubMed Central
Author	Schneider, Gisbert Wieland, Schrödl Gerd, Wallukat Müller, Johannes Nissen, Eberhard Wolfgang, Rönspeck Wrede, Paul Kunze, Rudolf
Copyright Year	1998
Abstract	A technique for systematic peptide variation by a combination of rational and evolutionary approaches is presented. The design scheme consists of five consecutive steps: (i) identification of a “seed peptide” with a desired activity, (ii) generation of variants selected from a physicochemical space around the seed peptide, (iii) synthesis and testing of this biased library, (iv) modeling of a quantitative sequence-activity relationship by an artificial neural network, and (v) de novo design by a computer-based evolutionary search in sequence space using the trained neural network as the fitness function. This strategy was successfully applied to the identification of novel peptides that fully prevent the positive chronotropic effect of anti-β1-adrenoreceptor autoantibodies from the serum of patients with dilated cardiomyopathy. The seed peptide, comprising 10 residues, was derived by epitope mapping from an extracellular loop of human β1-adrenoreceptor. A set of 90 peptides was synthesized and tested to provide training data for neural network development. De novo design revealed peptides with desired activities that do not match the seed peptide sequence. These results demonstrate that computer-based evolutionary searches can generate novel peptides with substantial biological activity.
Starting Page	12179
File Format	PDF
ISSN	10916490
e-ISSN	10916490
Journal	Proceedings of the National Academy of Sciences of the United States of America
Issue Number	21
Volume Number	95
Language	English
Publisher	The National Academy of Sciences
Publisher Date	1998-10-13
Access Restriction	Open
Rights Holder	The National Academy of Sciences
Subject Keyword	Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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