Successful structure based drug discovery/design is dependent upon accurate protein:ligand structure determination and characterization. Gaining an understanding of the protein:ligand complex structure along with the proper protonation, explicit solvent effects, and binding mode is crucial for obtaining meaningful results from docking, thermodynamic calculations, active site exploration, and ultimately lead optimization. Our work has allowed us to accurately refine protein:ligand structure through the integration of our linear-scaling, semiempirical, quantum mechanics (SE-QM)/molecular mechanics (QM/MM) engine with the Phenix crystallography platform. During this work, we found that SE-QM based macromolecular refinement is very sensitive to the choice of a protonation state/tautomer form of ligands and residues. We have developed a novel scoring method, called XModeScore, which incorporates both a rigorous statistical analysis of electron difference density distribution and the ligand strain energy. When studying problems in fragment based drug design (FBDD), we found similar problems: using X-ray crystallography it is generally difficult to experimentally determine the binding mode of fragments along with the protomeric/tautomeric state(s) of the fragment and of the surrounding active site - even at higher resolutions. Traditionally, determination of these binding modes required NMR or neutron diffraction; however, with XModeScore, we can incorporate both a rigorous statistical analysis of electron difference density distribution and the ligand strain energy and use this method to determine the experimental binding mode of small, dynamic fragments. The presentation will focus on the expansion of this method and its application to model fragment studies in both homogeneous and heterogeneous fragment populations. Methods and results will be discussed in detail.

From protons to fragments with XModeScore: How we can use x-ray data coupled with quantum mechanics to explore these elusive species in binding

253rd National Meeting (2017)

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