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.