Assessing the role of polarization in docking.
We describe a strategy for including ligand and protein polarization in docking that is based on the conversion of induced dipoles to induced charges. Induced charges have a distinct advantage in that they are readily implemented into a number of different computer programs, including many docking programs and hybrid QM/MM programs; induced charges are also more readily interpreted. In this study, the ligand was treated quantum mechanically to avoid parametrization issues and was polarized by the target protein, which was treated as a set of point charges. The induced dipole at a given target atom, due to polarization by the ligand and neighboring residues, was reformulated as induced charges at the given atom and its bonded neighbors, and these were allowed to repolarize the ligand in an iterative manner. The final set of polarized charges was evaluated in docking using AutoDock 4.0 on 12 protein-ligand systems against the default empirical Gasteiger charges, and against nonpolarized and partially polarized potential-derived charges. One advantage of AutoDock is that the best rmsd structure can be identified not only from the lowest energy pose but also from the largest cluster of poses. Inclusion of polarization does not always lead to the lowest energy pose having a lower rmsd, because docking is designed by necessity to be rapid rather than accurate. However, whenever an improvement in methodology, corresponding to a more thorough treatment of polarization, resulted in an increased cluster size, then there was also a corresponding decrease in the rmsd. The options for implementing polarization within a purely classical docking framework are discussed.
Illingworth
Christopher J R
CJ
Department of Biological Sciences, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, United Kingdom.
Morris
Garrett M
GM
Parkes
Kevin E B
KE
Snell
Christopher R
CR
Reynolds
Christopher A
CA
D000818:Animals; D001665:Binding Sites; D002417:Cattle; D018360:Crystallography, X-Ray; D030562:Databases, Protein; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D011789:Quantum Theory
D008024:Ligands; D011506:Proteins