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

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 wea...

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Príomhchruthaitheoirí: Pearce, N, Krojer, T, von Delft, F
Formáid: Journal article
Teanga:English
Foilsithe / Cruthaithe: International Union of Crystallography 2017
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author Pearce, N
Krojer, T
von Delft, F
author_facet Pearce, N
Krojer, T
von Delft, F
author_sort Pearce, N
collection OXFORD
description 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.
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spelling oxford-uuid:9eb73fe0-0208-4c16-99cf-9a43802646932022-03-27T00:52:10ZProper modelling of ligand binding requires an ensemble of bound and unbound statesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:9eb73fe0-0208-4c16-99cf-9a4380264693EnglishSymplectic Elements at OxfordInternational Union of Crystallography2017Pearce, NKrojer, Tvon Delft, FAlthough 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.
spellingShingle Pearce, N
Krojer, T
von Delft, F
Proper modelling of ligand binding requires an ensemble of bound and unbound states
title Proper modelling of ligand binding requires an ensemble of bound and unbound states
title_full Proper modelling of ligand binding requires an ensemble of bound and unbound states
title_fullStr Proper modelling of ligand binding requires an ensemble of bound and unbound states
title_full_unstemmed Proper modelling of ligand binding requires an ensemble of bound and unbound states
title_short Proper modelling of ligand binding requires an ensemble of bound and unbound states
title_sort proper modelling of ligand binding requires an ensemble of bound and unbound states
work_keys_str_mv AT pearcen propermodellingofligandbindingrequiresanensembleofboundandunboundstates
AT krojert propermodellingofligandbindingrequiresanensembleofboundandunboundstates
AT vondelftf propermodellingofligandbindingrequiresanensembleofboundandunboundstates