Tools for building a comprehensive modeling system for virtual screening under real biological conditions: The Computational Titration algorithm.

Computational tools utilizing a unique empirical modeling system based on the hydrophobic effect and the measurement of logP(o/w) (the partition coefficient for solvent transfer between 1-octanol and water) are described. The associated force field, Hydropathic INTeractions (HINT), contains much rich information about non-covalent interactions in the biological environment because of its basis in an experiment that measures interactions in solution. HINT is shown to be the core of an evolving virtual screening system that is capable of taking into account a number of factors often ignored such as entropy, effects of solvent molecules at the active site, and the ionization states of acidic and basic residues and ligand functional groups. The outline of a comprehensive modeling system for virtual screening that incorporates these features is described. In addition, a detailed description of the Computational Titration algorithm is provided. As an example, three complexes of dihydrofolate reductase (DHFR) are analyzed with our system and these results are compared with the experimental free energies of binding.

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.

The importance of being exhaustive. Optimization of bridging structural water molecules and water networks in models of biological systems.

Algorithms and protocols are described for the optimization for H-bonding of isolated singular H2O molecules and entire networks of H2O molecules. Unlike other approaches that are prone to being trapped in local energy minima, these methods rely on exhaustive searches of orientation space for the H2O molecules. The results are scored with the HINT hydropathic interaction model, but the algorithms should be general for any energy-scoring computation. Two examples are provided: 1) the tightly-bound H2O molecule 301 of HIV-1 protease is shown to be more reasonably oriented in terms of forming H-bonds with this method than with a molecular mechanics energy minimization method; and 2) the H2O network surrounding carbonmonoxymyoglobin is constructed and analyzed for a 1.80-A neutron-diffraction structure. The H-atom positions calculated with this method show a somewhat better agreement with the experimental results than do the H-atom positions calculated with molecular mechanics, and both are considerably better than random.