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Beyond Single Chains: Benchmarking Macromolecular Complex Prediction Methods With the Continuous Automated Model

Xavier Robin^1,2, Peter Škrinjar^1,2, Andrew M Waterhouse^1,2

¹Biozentrum, University of Basel, Basel, Switzerland.

|September 29, 2025

Summary

This summary is machine-generated.

Continuous Automated Model EvaluatiOn (CAMEO) offers weekly, automated benchmarking for protein structure prediction servers. This platform complements CASP experiments by providing ongoing assessment of prediction methods and their limitations.

Keywords:

3D structure prediction CASP16 macromolecular complexes protein structure protein‐ligand complexes

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Area of Science:

Computational biology
Structural biology
Bioinformatics

Background:

Accurate protein structure prediction is crucial for understanding biological function and disease.
Periodic assessments like CASP are vital but infrequent, creating a need for continuous evaluation.
Automated benchmarking platforms can provide timely feedback on prediction method performance.

Purpose of the Study:

To introduce the Continuous Automated Model EvaluatiOn (CAMEO) platform.
To describe CAMEO's role in providing regular, automated benchmarking of protein structure prediction servers.
To highlight CAMEO's complementary function to established, less frequent assessments like CASP.

Main Methods:

Development of a platform for automated, weekly benchmarking of protein structure prediction servers.
Implementation of blind assessment protocols within the CAMEO framework.
Continuous integration of new prediction methods and server submissions for evaluation.

Main Results:

CAMEO provides consistent, weekly performance data for numerous structure prediction servers.
The platform enables the identification of emerging trends and limitations in structure prediction methodologies.
Automated benchmarking facilitates rapid feedback loops for method developers.

Conclusions:

CAMEO serves as an essential tool for the ongoing evaluation of protein structure prediction methods.
Regular, automated assessments are critical for advancing the field of structural biology.
The CAMEO platform significantly enhances the ability to track and improve state-of-the-art structure prediction.