Summary
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.
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Acknowledgements
We gratefully acknowledge partial support of this research by Virginia Commonwealth University and NIH NIAID grant 5R01AI052330 to Dr. Kevin A. Reynolds. We also thank Drs. Reynolds, Derek Cashman and Micaela Fornabaio for helpful discussions.
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Chen, D., Kellogg, G. A computational tool to optimize ligand selectivity between two similar biomacromolecular targets. J Comput Aided Mol Des 19, 69–82 (2005). https://doi.org/10.1007/s10822-005-1485-7
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DOI: https://doi.org/10.1007/s10822-005-1485-7