An evolutionary approach for structure-based design of natural and non-natural peptidic ligands

TitleAn evolutionary approach for structure-based design of natural and non-natural peptidic ligands
Publication TypeJournal Article
Year of Publication2001
AuthorsBudin N., Ahmed S., Majeux N., Caflisch A.
JournalCombinatorial Chemistry & High Throughput Screening
Volume4
Issue8
Pagination661-673
Date Published2001 Dec
Type of ArticleResearch Article
ISSN1386-2073
KeywordsAlgorithms, Alkyl and Aryl Transferases, Amino Acid Sequence, Biological Evolution, Combinatorial Chemistry Techniques, Drug Design, Enzyme Inhibitors, Farnesyltranstransferase, Ligands, Molecular Sequence Data, Peptide Library, Peptides, Protein-Tyrosine Kinases, Static Electricity
Abstract

A new computational approach (PEP) is presented for the structure-based design of linear polymeric ligands consisting of any type of amino acid. Ligands are grown from a seed by iteratively adding amino acids to the growing construct. The search in chemical space is performed by a build-up approach which employs all of the residues of a user-defined library. At every growing step, a genetic algorithm is used for conformational optimization of the last added monomer inside the binding site of a rigid target protein. The binding energy with electrostatic solvation is evaluated to select sequences for further growing. PEP is tested on the peptide substrate binding site of the insulin receptor tyrosine kinase and farnesyltransferase. In both test cases, the peptides designed by PEP correspond to the sequence motifs of known substrates. For tyrosine kinase, tyrosine residues are suggested at position P and P+2. While the tyrosine at P is in agreement with the experimental data, the one at P+2 is a prediction which awaits experimental validation. For farnesyltransferase, it is shown that electrostatic solvation is necessary for the correct design of peptidic inhibitors.

DOI10.2174/1386207013330652
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Alternate JournalComb. Chem. High Throughput Screen.
PubMed ID11812261
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