title: Gaussian docking functions.
abstract: A shape-based Gaussian docking function is constructed which uses Gaussian functions to represent the shapes of individual atoms. A set of 20 trypsin ligand-protein complexes are drawn from the Protein Data Bank (PDB), the ligands are separated from the proteins, and then are docked back into the active sites using numerical optimization of this function. It is found that by employing this docking function, quasi-Newton optimization is capable of moving ligands great distances [on average 7 A root mean square distance (RMSD)] to locate the correctly docked structure. It is also found that a ligand drawn from one PDB file can be docked into a trypsin structure drawn from any of the trypsin PDB files. This implies that this scoring function is not limited to more accurate x-ray structures, as is the case for many of the conventional docking methods, but could be extended to homology models.
authors.affiliation: Open Eye Scientific Software, Santa Fe, NM 87501, USA.
authors.forename: Mark R
authors.initials: MR
authors.lastname: McGann
authors.forename: Harold R
authors.initials: HR
authors.lastname: Almond
authors.forename: Anthony
authors.initials: A
authors.lastname: Nicholls
authors.forename: J Andrew
authors.initials: JA
authors.lastname: Grant
authors.forename: Frank K
authors.initials: FK
authors.lastname: Brown
mesh_terms: D001665:Binding Sites; D003198:Computer Simulation; D030562:Databases, Protein; D008024:Ligands; D016011:Normal Distribution; D011485:Protein Binding; D011487:Protein Conformation; D013816:Thermodynamics; D014357:Trypsin / Q000737:chemistry* / Q000378:metabolism*
chemical_list: D008024:Ligands; D014357:Trypsin