Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model EvaluatiOn (CAMEO)

Q: What type of study is this?

This is a Quantitative Study study.

Xavier Robin; Peter Škrinjar; Andrew Waterhouse; Gabriel Studer; Gerardo Tauriello; Janani Durairaj; Torsten Schwede

doi:10.1002/prot.70060

September 28, 2025Proteins Structure Function and Bioinformatics

Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model EvaluatiOn (CAMEO)

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Key Points

The CAMEO platform assesses structure prediction methods weekly, and identifies limitations in current technologies.
It complements CASP experiments by providing a consistent evaluation framework for structure prediction servers.
Independent evaluations of structure prediction methods are crucial for advancing computational biology.
Automated evaluations like CAMEO allow for faster identification of state‐of‐the‐art performance metrics in the field.

Implication

Automated benchmarking of structure prediction in macromolecular complexes highlights limitations, guiding future research.

Abstract

Independent, blind assessment of structure prediction methods is essential for establishing state‐of‐the‐art performance, identifying limitations, and guiding future developments. The Continuous Automated Model EvaluatiOn (CAMEO) platform provides weekly, automated benchmarking of structure prediction servers, complementing the biennial Critical Assessment of Structure Prediction (CASP) experiments.

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Cite This Study

Robin et al. (2025) studied this question.

synapsesocial.com/papers/68dd89defe798ba2fc497cb2 https://doi.org/10.1002/prot.70060

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Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model EvaluatiOn (CAMEO)

Key Points

Implication

Abstract

Discussion

Cite This Study

Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model EvaluatiOn (CAMEO)

Key Points

Implication

Abstract

Discussion

Cite This Study

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