A computational tool to optimize ligand selectivity between two similar biomacromolecular targets.
Algorithms for a new computer program designed to increase ligand-receptor selectivity between two proteins are described. In this program ligand-receptor selectivity is increased by functional modifications to the ligand so as to increase the calculated binding affinity of it to one protein and/or decrease the calculated binding affinity of it to the other protein. The structure of the ligand is modified by selective replacement of atoms and/or functional groups in silico based on a specific set of steric and/or hydropathic complementarity rules involving atoms and functional groups. Relative binding scores are calculated with simple grid-based steric penalty, hydrogen bond complementarity, and with the HINT score model. Two examples are shown. First, modifying the structure of the ligand CB3717 is illustrated in a number of ways such that the binding selectivity to wild type L. casei thymidylate synthase or its E60Q mutant may be improved. Second, starting with a non-selective lead compound that had been co-crystallized with both plant and mammalian 4-hydroxyphenylpyruvate dioxygenases, new compounds (similar to selective ligands discovered by screening) to improve the selectivity of (herbicidal) inhibitors for the plant enzyme were designed by the program.[1]References
- A computational tool to optimize ligand selectivity between two similar biomacromolecular targets. Chen, D.L., Kellogg, G.E. J. Comput. Aided Mol. Des. (2005) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg