Assessing the Role of Polarization in Docking Christopher J. R. Illingworth, † Garrett M. Morris, ‡ Kevin E. B. Parkes, § Christopher R. Snell, § and Christopher A. Reynolds* ,† Department of Biological Sciences, UniVersity of Essex, WiVenhoe Park, Colchester CO4 3SQ, United Kingdom, The Scripps Research Institute, Department of Molecular Biology, MB-5 10550 North Torrey Pines Road La Jolla, California 92037-1000, and MediVir UK Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, United Kingdom ReceiVed: October 19, 2007; ReVised Manuscript ReceiVed: August 11, 2008 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.2008112 Introduction A variety of virtual screening protocols are used in drug discovery for both hit generation and lead optimization and consequently there is much effort to improve both the efficiency and the accuracy of these methods. Here we present initial quantum mechanical/molecular mechanics (QM/MM) studies on the inclusion of polarization in both the ligand and the target. Current virtual screening approaches range from pharmaco- phore-based methods, 1 through empirical or knowledge-based methods 2-7 to physics-based methods. 8-15 Each approach has its merits. For instance, pharmacophore-based methods are not susceptible to the same kinds of errors as physics-based ones, whereas empirical methods can be parametrized to reproduce known binding constantssprovided that they are used on systems similar to those used in the parametrization. Various combinations of these approaches are also used. Typically, the physics-based methods employ molecular mechanics to evaluate the ligand-target interaction energy and the errors in such force- field-based methods are well understood from their use in molecular dynamics and Monte Carlo simulations. 16 Explicitly modeled molecular mechanics polarization is frequently absent from most such simulations, from many hybrid QM/MM (quantum mechanical/molecular mechanics) studies and from most docking experiments. 16,17 Past approaches to modeling MM polarization include those based around a fluctuating charge model, 18-22 those based on a Drude Oscillator model 23-27 and those based around induced dipoles. 28-42 The latter approach is the most widespread, and the SIBFA implementation 43 is one of a small number of programs with a long track record in terms of application to ligand-receptor interactions. Other recent specific approaches to polarization are reviewed elsewhere. 44 Our method as presented here is distinct from these, as it is based upon modifications to the MM charges of a QM/MM system, induced through the influence of the QM region. Compared to purely MM approaches, QM treatment is convenient in that it avoids the need for parametrization of new ligands. In contrast to the induced dipole and Drude Oscillator models, it holds the advantage of being expressed purely in modifications to already existent point charges, making for easier integration with packages, such as AutoDock, that use point charges to model the electrostatics of a protein system. Previous work on the modeling of polarization through induced charges in QM/MM models has shown significant improvement in calculated energy values. 45 Our approach to docking employs AutoDock and is based on an extension to the QM/MM approach of Friesner et al. 46 It includes not only the quantum mechanical polarization of the ligand as in Friesner et al.’s approach but also the polarization of the target macromolecule. The implementation described here involves (a) knowledge of the structure of the complex and (b) iteration of quantum mechanical calculations and is not pre- sented as a practical tool in docking but rather to catalyze developments that eventually lead to routine docking to polar- * Corresponding author. E-mail: reync@essex.ac.uk. † The University of Essex. ‡ The Scripps Research Institute. § Medivir UK. J. Phys. Chem. A 2008, 112, 12157–12163 12157 10.1021/jp710169m CCC: $40.75  2008 American Chemical Society Published on Web 11/06/2008