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Proper modelling of ligand binding requires an ensemble of bound and unbound states

DOI: 10.1107/S2059798317003412 DOI Help

Authors: Nicholas Pearce (Structural Genomics Consortium, University of Oxford) , Tobias Krojer (Structural Genomics Consortium, University of Oxford) , Frank Von Delft (Structural Genomics Consortium, Nuffield Department of Medicine, University of Oxford; Diamond Light Source; University of Johannesburg)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Acta Crystallographica Section D Structural Biology , VOL 73 , PAGES 256 - 266

State: Published (Approved)
Published: March 2017

Open Access Open Access

Abstract: Although noncovalent binding by small molecules cannot be assumed a priori to be stoichiometric in the crystal lattice, occupancy refinement of ligands is often avoided by convention. Occupancies tend to be set to unity, requiring the occupancy error to be modelled by the B factors, and residual weak density around the ligand is necessarily attributed to `disorder'. Where occupancy refinement is performed, the complementary, superposed unbound state is rarely modelled. Here, it is shown that superior accuracy is achieved by modelling the ligand as partially occupied and superposed on a ligand-free `ground-state' model. Explicit incorporation of this model of the crystal, obtained from a reference data set, allows constrained occupancy refinement with minimal fear of overfitting. Better representation of the crystal also leads to more meaningful refined atomic parameters such as the B factor, allowing more insight into dynamics in the crystal. An outline of an approach for algorithmically generating ensemble models of crystals is presented, assuming that data sets representing the ground state are available. The applicability of various electron-density metrics to the validation of the resulting models is assessed, and it is concluded that ensemble models consistently score better than the corresponding single-state models. Furthermore, it appears that ignoring the superposed ground state becomes the dominant source of model error, locally, once the overall model is accurate enough; modelling the local ground state properly is then more meaningful than correcting all remaining model errors globally, especially for low-occupancy ligands. Implications for the simultaneous refinement of B factors and occupancies, and for future evaluation of the limits of the approach, in particular its behaviour at lower data resolution, are discussed.

Journal Keywords: crystallography; modelling; ligand binding; model validation

Subject Areas: Biology and Bio-materials, Chemistry


Instruments: I04-1-Macromolecular Crystallography (fixed wavelength)

Added On: 13/04/2017 14:16

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