X-ray crystallography and to a lesser extent cryogenic electron microscopy (cryo-EM) are the primary techniques used to determine the three-dimensional (3D) structure of protein:ligand and protein:protein complexes, and these methods play a central role in Structure Based Drug Design (SBDD). During the model building stage of X-ray and Cryo-EM refinement, a significant challenge in ligand model placement is determination of the correct ligand orientation especially when the experimental density is weak or incomplete. We have addressed this ligand placement and refinement problem with the use of our MovableType fast free energy based docking algorithm (MTDock) coupled with a built-in realspace (RS) refinement engine in which geometry energy and gradients - derived using a QM, MM or mixed QM/MM Hamiltonian - are combined with electron density values/gradients derived from X-ray data / Cryo-EM maps. In this work, we will present this integrated RS-MTDock protocol which involves automated electron density blob selection followed by MT-driven ligand placement and RS refinement. Each refined pose is then scored using MTScore in order to determine which pose is correct. For ease of use and maximum performance, these steps have been fully integrated within QuantumBio's Discovery Suite and therefore do not require external third-party software to execute. We’ve validated the RS-MTDock protocol using 480 protein:ligand structures taken from the Iridium and PDBBind sets. We demonstrated top scored ligand poses have RMSD to the published structures below 0.3 Å and/or similar or actually exhibit better fit versus the electron density in over 90% cases.

RS-MTDock: movable type ligand docking method using X-ray / Cryo-EM experimental density and integrated realspace refinement

ACS Spring 2022

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