skip to main content

DOE PAGESDOE PAGES

Title: Improved ligand geometries in crystallographic refinement using AFITT in PHENIX

Modern crystal structure refinement programs rely on geometry restraints to overcome the challenge of a low data-to-parameter ratio. While the classical Engh and Huber restraints work well for standard amino-acid residues, the chemical complexity of small-molecule ligands presents a particular challenge. Most current approaches either limit ligand restraints to those that can be readily described in the Crystallographic Information File (CIF) format, thus sacrificing chemical flexibility and energetic accuracy, or they employ protocols that substantially lengthen the refinement time, potentially hindering rapid automated refinement workflows.PHENIX–AFITTrefinement uses a full molecular-mechanics force field for user-selected small-molecule ligands during refinement, eliminating the potentially difficult problem of finding or generating high-quality geometry restraints. It is fully integrated with a standard refinement protocol and requires practically no additional steps from the user, making it ideal for high-throughput workflows.PHENIX–AFITTrefinements also handle multiple ligands in a single model, alternate conformations and covalently bound ligands. Here, the results of combiningAFITTand thePHENIXsoftware suite on a data set of 189 protein–ligand PDB structures are presented. Refinements usingPHENIX–AFITTsignificantly reduce ligand conformational energy and lead to improved geometries without detriment to the fit to the experimental data. Finally, for the data presented,PHENIX–AFITTrefinements result in more chemically accurate models for small-molecule ligands.
Authors:
 [1] ;  [2] ;  [3] ;  [1] ;  [1] ;  [4] ;  [5]
  1. Rutgers Univ., Piscataway, NJ (United States). BioMaPs Inst., Center for Integrative Proteomics Research; Rutgers Univ., Piscataway, NJ (United States). Dept. of Chemistry and Chemical Biology
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging
  3. Novartis Inst. for BioMedical Research Inc., Cambridge, MA (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Molecular Biophysics and Integrated Bioimaging; Univ. of California, Berkeley, CA (United States). Dept. of Bioengineering
  5. OpenEye Scientific Software, Santa Fe, NM (United States)
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Acta Crystallographica. Section D. Structural Biology
Additional Journal Information:
Journal Volume: 72; Journal Issue: 9; Journal ID: ISSN 2059-7983
Publisher:
IUCr
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC); National Institutes of Health (NIH)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 59 BASIC BIOLOGICAL SCIENCES; macromolecular refinement; ligands; geometry restraints; PHENIX; AFITT
OSTI Identifier:
1377454

Janowski, Pawel A., Moriarty, Nigel W., Kelley, Brian P., Case, David A., York, Darrin M., Adams, Paul D., and Warren, Gregory L.. Improved ligand geometries in crystallographic refinement using AFITT in PHENIX. United States: N. p., Web. doi:10.1107/S2059798316012225.
Janowski, Pawel A., Moriarty, Nigel W., Kelley, Brian P., Case, David A., York, Darrin M., Adams, Paul D., & Warren, Gregory L.. Improved ligand geometries in crystallographic refinement using AFITT in PHENIX. United States. doi:10.1107/S2059798316012225.
Janowski, Pawel A., Moriarty, Nigel W., Kelley, Brian P., Case, David A., York, Darrin M., Adams, Paul D., and Warren, Gregory L.. 2016. "Improved ligand geometries in crystallographic refinement using AFITT in PHENIX". United States. doi:10.1107/S2059798316012225. https://www.osti.gov/servlets/purl/1377454.
@article{osti_1377454,
title = {Improved ligand geometries in crystallographic refinement using AFITT in PHENIX},
author = {Janowski, Pawel A. and Moriarty, Nigel W. and Kelley, Brian P. and Case, David A. and York, Darrin M. and Adams, Paul D. and Warren, Gregory L.},
abstractNote = {Modern crystal structure refinement programs rely on geometry restraints to overcome the challenge of a low data-to-parameter ratio. While the classical Engh and Huber restraints work well for standard amino-acid residues, the chemical complexity of small-molecule ligands presents a particular challenge. Most current approaches either limit ligand restraints to those that can be readily described in the Crystallographic Information File (CIF) format, thus sacrificing chemical flexibility and energetic accuracy, or they employ protocols that substantially lengthen the refinement time, potentially hindering rapid automated refinement workflows.PHENIX–AFITTrefinement uses a full molecular-mechanics force field for user-selected small-molecule ligands during refinement, eliminating the potentially difficult problem of finding or generating high-quality geometry restraints. It is fully integrated with a standard refinement protocol and requires practically no additional steps from the user, making it ideal for high-throughput workflows.PHENIX–AFITTrefinements also handle multiple ligands in a single model, alternate conformations and covalently bound ligands. Here, the results of combiningAFITTand thePHENIXsoftware suite on a data set of 189 protein–ligand PDB structures are presented. Refinements usingPHENIX–AFITTsignificantly reduce ligand conformational energy and lead to improved geometries without detriment to the fit to the experimental data. Finally, for the data presented,PHENIX–AFITTrefinements result in more chemically accurate models for small-molecule ligands.},
doi = {10.1107/S2059798316012225},
journal = {Acta Crystallographica. Section D. Structural Biology},
number = 9,
volume = 72,
place = {United States},
year = {2016},
month = {8}
}

Works referenced in this record:

PHENIX: a comprehensive Python-based system for macromolecular structure solution
journal, January 2010
  • Adams, Paul D.; Afonine, Pavel V.; Bunkóczi, Gábor
  • Acta Crystallographica Section D Biological Crystallography, Vol. 66, Issue 2, p. 213-221
  • DOI: 10.1107/S0907444909052925

Improved methods for building protein models in electron density maps and the location of errors in these models
journal, March 1991
  • Jones, T. A.; Zou, J. Y.; Cowan, S. W.
  • Acta Crystallographica Section A Foundations of Crystallography, Vol. 47, Issue 2, p. 110-119
  • DOI: 10.1107/S0108767390010224