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Systematic assessment of accuracy of comparative model of proteins belonging to different structural fold classes

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Abstract

In the absence of experimental structures, comparative modeling continues to be the chosen method for retrieving structural information on target proteins. However, models lack the accuracy of experimental structures. Alignment error and structural divergence (between target and template) influence model accuracy the most. Here, we examine the potential additional impact of backbone geometry, as our previous studies have suggested that the structural class (all-α, αβ, all-β) of a protein may influence the accuracy of its model. In the twilight zone (sequence identity ≤ 30%) and at a similar level of target-template divergence, the accuracy of protein models does indeed follow the trend all-α > αβ > all-β. This is mainly because the alignment accuracy follows the same trend (all-α > αβ > all-β), with backbone geometry playing only a minor role. Differences in the diversity of sequences belonging to different structural classes leads to the observed accuracy differences, thus enabling the accuracy of alignments/models to be estimated a priori in a class-dependent manner. This study provides a systematic description of and quantifies the structural class-dependent effect in comparative modeling. The study also suggests that datasets for large-scale sequence/structure analyses should have equal representations of different structural classes to avoid class-dependent bias.

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Acknowledgments

We thank Sucheta Godbole for helping us with the profile–profile alignments. We thank Zhanwen Li of the Godzik Laboratory at the Burnham Institute for helping us with the Fold and Function Assignment (FFAS) server when investigating the test cases of profile–profile alignments. SC thanks Prof. Ming-Ming Zhou for encouragement. The study was supported by the National Institute of General Medicine at the National Institutes of Health [grant 1R01GM081713 (RS)], and South Dakota State University’s (SDSU) Agricultural Experiment Station and Center for Biological Control and Analysis by Applied Photonics (BCAAP) [grant 3SG163 (SC)].

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Authors and Affiliations

  1. Department of Chemistry & Biochemistry, South Dakota State University, Box 2202, Brookings, SD, 57007, USA

    Suvobrata Chakravarty

  2. Department of Structural and Chemical Biology, Mount Sinai School of Medicine, Box 1677, 1425 Madison Avenue, New York, NY, 10029, USA

    Dario Ghersi & Roberto Sanchez

  3. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, 08540, USA

    Dario Ghersi

Authors
  1. Suvobrata Chakravarty
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  2. Dario Ghersi
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  3. Roberto Sanchez
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Correspondence to Suvobrata Chakravarty or Roberto Sanchez.

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Chakravarty, S., Ghersi, D. & Sanchez, R. Systematic assessment of accuracy of comparative model of proteins belonging to different structural fold classes. J Mol Model 17, 2831–2837 (2011). https://doi.org/10.1007/s00894-011-0976-9

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  • DOI: https://doi.org/10.1007/s00894-011-0976-9

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