""""""""MolProbity Validation and Corrections: for Crystallography, PDB, and Biomedicine"""""""" Summary: The criteria and services of our MolProbity web site and related resources have become accepted by the professional crystallography community as state-of-the-art for improving and validating structural accuracy. Macromolecular crystal structures represent extremely reliable scientific information, but they can still often contain local errors that hurt interpretation in their crucial role in applications such as understanding enzymatic reactions or molecular machines, or drug design. This complex and heavily used web service needs continued upgrading of efficiency and good practice, to maintain transparently easy and reliable use for the rapidly growing user base that now depends upon it. Differently presented MolProbity output will soon be required for worldwide PDB use in the new standards recommended by the wwPDB Validation Task Forces. Further automation is needed for error corrections incorporating all-atom contacts, application of them sooner in the structure-solution process, and integration into more of the standard software systems -- especially to help ensure reliability and productivity for the growing number of laboratories who do occasional crystal structures in support of their primary biological and biomedical work. Current research on ways of improving accuracy at lower resolutions and for large protein/nucleic acid complexes should become part of MolProbity, along with better treatment of multiple conformations at very high resolution, re-examination of underlying parameters, and additional features tailored for NMR, prediction, and simulation uses. Wider implementation of MolProbity corrections will aid all end-users of structures by improving their overall accuracy, while easy MolProbity validation helps end-users evaluate the reliability of structural details in local regions of direct relevance to their work. A goal of this proposal is essentially to put ourselves out of business by building MolProbity-style corrections into the future pipelines of structure solution and database deposition. )

Public Health Relevance

MolProbity is a web service for structure validation and correction. Use of this methodology is already improving accuracy of biologically and medically important macromolecular structures, as seen in statistics across the worldwide PDB database. We seek to increase MolProbity's ease, effectiveness and scope and to integrate its criteria into the standard procedures of structure determination, for the benefit of structural biologists, databases, and biomedical end-users. )

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM073919-05
Application #
8077177
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Edmonds, Charles G
Project Start
2006-07-01
Project End
2015-03-31
Budget Start
2011-04-01
Budget End
2012-03-31
Support Year
5
Fiscal Year
2011
Total Cost
$329,100
Indirect Cost
Name
Duke University
Department
Biochemistry
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Richardson, Jane S; Williams, Christopher J; Hintze, Bradley J et al. (2018) Model validation: local diagnosis, correction and when to quit. Acta Crystallogr D Struct Biol 74:132-142
Williams, Christopher J; Headd, Jeffrey J; Moriarty, Nigel W et al. (2018) MolProbity: More and better reference data for improved all-atom structure validation. Protein Sci 27:293-315
Richardson, Jane S; Williams, Christopher J; Videau, Lizbeth L et al. (2018) Assessment of detailed conformations suggests strategies for improving cryoEM models: Helix at lower resolution, ensembles, pre-refinement fixups, and validation at multi-residue length scale. J Struct Biol 204:301-312
Hintze, Bradley J; Richardson, Jane S; Richardson, David C (2017) Mismodeled purines: implicit alternates and hidden Hoogsteens. Acta Crystallogr D Struct Biol 73:852-859
Richardson, Jane S; Videau, Lizbeth L; Williams, Christopher J et al. (2017) Broad Analysis of Vicinal Disulfides: Occurrences, Conformations with Cis or with Trans Peptides, and Functional Roles Including Sugar Binding. J Mol Biol 429:1321-1335
Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S et al. (2016) BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design. J Comput Biol 23:413-24
Hintze, Bradley J; Lewis, Steven M; Richardson, Jane S et al. (2016) Molprobity's ultimate rotamer-library distributions for model validation. Proteins 84:1177-89
Jain, Swati; Richardson, David C; Richardson, Jane S (2015) Computational Methods for RNA Structure Validation and Improvement. Methods Enzymol 558:181-212
Zhou, Huiqing; Hintze, Bradley J; Kimsey, Isaac J et al. (2015) New insights into Hoogsteen base pairs in DNA duplexes from a structure-based survey. Nucleic Acids Res 43:3420-33
Kapral, Gary J; Jain, Swati; Noeske, Jonas et al. (2014) New tools provide a second look at HDV ribozyme structure, dynamics and cleavage. Nucleic Acids Res 42:12833-46

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