Dataset Information

MolProbity for the masses-of data.

ABSTRACT: MolProbity is a powerful software program for validating structures of proteins and nucleic acids. Although MolProbity includes scripts for batch analysis of structures, because these scripts analyze structures one at a time, they are not well suited for the validation of a large dataset of structures. We have created a version of MolProbity (MolProbity-HTC) that circumvents these limitations and takes advantage of a high-throughput computing cluster by using the HTCondor software. MolProbity-HTC enables the longitudinal analysis of large sets of structures, such as those deposited in the PDB or generated through theoretical computation-tasks that would have been extremely time-consuming using previous versions of MolProbity. We have used MolProbity-HTC to validate the entire PDB, and have developed a new visual chart for the BioMagResBank website that enables users to easily ascertain the quality of each model in an NMR ensemble and to compare the quality of those models to the rest of the PDB.

SUBMITTER: Chen VB

PROVIDER: S-EPMC4577456 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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MolProbity for the masses-of data.

Chen Vincent B VB Wedell Jonathan R JR Wenger R Kent RK Ulrich Eldon L EL Markley John L JL

Journal of biomolecular NMR 20150721 1

MolProbity is a powerful software program for validating structures of proteins and nucleic acids. Although MolProbity includes scripts for batch analysis of structures, because these scripts analyze structures one at a time, they are not well suited for the validation of a large dataset of structures. We have created a version of MolProbity (MolProbity-HTC) that circumvents these limitations and takes advantage of a high-throughput computing cluster by using the HTCondor software. MolProbity-HT ...[more]

PMID: 26195077

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Project description:Misfit sidechains in protein crystal structures are a stumbling block in using those structures to direct further scientific inference. Problems due to surface disorder and poor electron density are very difficult to address, but a large class of systematic errors are quite common even in well-ordered regions, resulting in sidechains fit backwards into local density in predictable ways. The MolProbity web site is effective at diagnosing such errors, and can perform reliable automated correction of a few special cases such as 180 degrees flips of Asn or Gln sidechain amides, using all-atom contacts and H-bond networks. However, most at-risk residues involve tetrahedral geometry, and their valid correction requires rigorous evaluation of sidechain movement and sometimes backbone shift. The current work extends the benefits of robust automated correction to more sidechain types. The Autofix method identifies candidate systematic, flipped-over errors in Leu, Thr, Val, and Arg using MolProbity quality statistics, proposes a corrected position using real-space refinement with rotamer selection in Coot, and accepts or rejects the correction based on improvement in MolProbity criteria and on chi angle change. Criteria are chosen conservatively, after examining many individual results, to ensure valid correction. To test this method, Autofix was run and analyzed for 945 representative PDB files and on the 50S ribosomal subunit of file 1YHQ. Over 40% of Leu, Val, and Thr outliers and 15% of Arg outliers were successfully corrected, resulting in a total of 3,679 corrected sidechains, or 4 per structure on average. Summary Sentences: A common class of misfit sidechains in protein crystal structures is due to systematic errors that place the sidechain backwards into the local electron density. A fully automated method called "Autofix" identifies such errors for Leu, Val, Thr, and Arg and corrects over one third of them, using MolProbity validation criteria and Coot real-space refinement of rotamers.

Dataset Information

MolProbity for the masses-of data.

Publications

MolProbity for the masses-of data.

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