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Evaluation of the template-based modeling in CASP12.

Andriy Kryshtafovych1, Bohdan Monastyrskyy1, Krzysztof Fidelis1

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This study evaluated CASP12 protein models, finding significant improvements in accuracy, especially for backbone atoms and non-template regions. Advancements in modeling strategies and refinement methods contributed to better protein structure prediction.

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Area of Science:

  • Structural Bioinformatics
  • Computational Biology
  • Protein Modeling

Background:

  • The Critical Assessment of protein Structure Prediction (CASP) is a community-wide experiment for protein structure prediction.
  • CASP12 evaluated models for targets with identifiable structural templates and high server-model accuracy.
  • Assessing model quality involves comparing predictions against experimental structures, focusing on backbone accuracy, local geometry, and error estimation.

Purpose of the Study:

  • To numerically evaluate protein models submitted to CASP12.
  • To analyze the accuracy of CASP12 models against experimental structures.
  • To assess the performance of research groups and automatic servers in protein structure prediction.

Main Methods:

  • Numerical evaluation of CASP12 models.
  • Analysis of model details, backbone accuracy, all-atom local geometry, and local error estimation.
  • Separate performance analyses for human groups and automated servers.

Main Results:

  • Significant improvements observed in CASP12 models compared to previous CASP assessments.
  • Enhanced accuracy in protein backbone atoms, sequence alignment, and modeling of non-template regions.
  • Models demonstrated increased accuracy beyond simple template copying.

Conclusions:

  • Advancements in ab initio modeling of non-template regions contributed to improved accuracy.
  • Better algorithms for multi-template combination and enhanced refinement methods were key.
  • Improved methods for model accuracy estimation were also identified.