ResiRole: residue-level functional site predictions to gauge the accuracies of protein structure prediction techniques.
ResiRole: residue-level functional site predictions to gauge the accuracies of protein structure prediction techniques.
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DOI:
10.1093/bioinformatics/btaa712
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发表时间:
2021-04-20
期刊:
影响因子:
--
通讯作者:
McLaughlin WA
中科院分区:
文献类型:
--
作者:
Toth JM;DePietro PJ;Haas J;McLaughlin WA
Methods to assess the quality of protein structure models are needed for user applications. To aid with the selection of structure models and further inform the development of structure prediction techniques, we describe the ResiRole method for the assessment of the quality of structure models. Structure prediction techniques are ranked according to the results of round-robin, head-to-head comparisons using difference scores. Each difference score was defined as the absolute value of the cumulative probability for a functional site prediction made with the FEATURE program for the reference structure minus that for the structure model. Overall, the difference scores correlate well with other model quality metrics; and based on benchmarking studies with NaïveBLAST, they are found to detect additional local structural similarities between the structure models and reference structures. Automated analyses of models addressed in CAMEO are available via the ResiRole server, URL http://protein.som.geisinger.edu/ResiRole/. Interactive analyses with user-provided models and reference structures are also enabled. Code is available at github.com/wamclaughlin/ResiRole. Supplementary data are available at Bioinformatics online.
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