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Related Experiment Videos

Assessment of progress over the CASP experiments.

Ceslovas Venclovas1, Adam Zemla, Krzysztof Fidelis

  • 1Biology and Biotechnology Research Program, Lawrence Livermore National Laboratory, Livermore, California, USA.

Proteins
|October 28, 2003
PubMed
Summary

Structural modeling in CASP5 shows significant progress in fold recognition via meta-servers, but limited improvement in comparative modeling accuracy. Model quality relies heavily on template similarity and alignment quality, with no new methods surpassing template copying.

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Progress and Bottlenecks for Deep Learning in Computational Structure Biology: CASP Round XVI.

Proteins·2025

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein modeling

Background:

  • The Critical Assessment of protein Structure Prediction (CASP) experiments evaluate the accuracy of protein structure models.
  • Previous CASP experiments have shown consistent progress in various protein modeling regimes.
  • Advancements in computational methods, including meta-servers, aim to improve model prediction accuracy.

Purpose of the Study:

  • To compare the quality of protein structure models from the CASP5 experiment with those from earlier CASP rounds.
  • To identify progress and stagnation in different protein modeling approaches, specifically comparative and fold recognition modeling.
  • To assess the factors influencing model accuracy, such as template similarity and sequence alignment quality.

Main Methods:

Related Experiment Videos

  • Comparative analysis of protein structure models submitted to CASP5 against models from previous CASP experiments.
  • Evaluation of model quality based on accuracy metrics relevant to comparative modeling and fold recognition.
  • Analysis of the correlation between model accuracy and factors like sequence identity to templates and alignment quality.

Main Results:

  • Significant progress was observed in fold recognition, largely attributed to the development and use of meta-servers for generating consensus models.
  • Limited improvement was found in comparative modeling accuracy, especially for targets with sequence identities greater than 30%.
  • Model accuracy for low-sequence identity comparative models and fold recognition models was primarily dependent on the fraction of the target structure similar to a template and the alignment quality.

Conclusions:

  • Current methods do not effectively improve model quality beyond accurately copying a template structure.
  • Progress in modeling proteins with previously unknown folds appears to have plateaued, although more groups are producing high-quality models.
  • Despite challenges in identifying year-to-year progress, the history of CASP experiments indicates steady overall advancement in all modeling domains.