QM-Polarized Ligand Docking: A novel research solution that combines the power of Glide with the accuracy of QSite

The first such algorithm of its kind, QM-Polarized Ligand Docking uses ab initio methodology to calculate ligand charges within the protein environment. Innovative and practical, QM-Polarized Ligand Docking offers substantially enhanced accuracy over pure MM docking algorithms.

Overview

Accurate treatment of electrostatic charges is crucial to the success of any docking algorithm. Although contemporary force fields are capable of modeling partial atomic charges on ligands with reasonable accuracy, they are generally incapable of considering charge polarization induced by the protein environment. The greater the role charge polarization plays in determining a ligand's bound conformation, the more difficult it will be for MM docking algorithms to perceive the correct binding mode. For research applications that demand the highest level of docking accuracy, Schrödinger introduces QM-Polarized Ligand Docking (QPLD), which uses ab inito charge calculations to overcome this limitation.

QPLD combines the docking power of Glide with the accuracy of QSite, Schrödinger's respected QM/MM software. The QPLD algorithm begins with a Glide docking job that generates several geometrically unique protein-ligand complexes. QSite then performs a single-point energy calculation on each complex, treating the ligand with ab initio methods and deriving partial atomic charges using electrostatic potential fitting. Glide then re-docks the ligand using each of the ligand charge sets calculated by QSite, and the QPLD algorithm returns the most energetically favorable pose. The fully automated algorithm is calibrated to provide useful default settings that can be modified at the user's discretion.

In keeping with Schrödinger's tradition of pairing innovation and practicality, QPLD calculations are effortlessly set up and launched using a single panel within the Maestro interface. Calculations are easily parallelized across multiple processors, and results are automatically incorporated into Maestro for visualization and analysis.