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A study of quality measures for protein threading models.

S Cristobal¹, A Zemla, D Fischer

¹Cell and Molecular Biology Department, Box 596. BMC Uppsala University, SE-751 24 Uppsala, Sweden. susana.cristobal@icm.uu.se

BMC Bioinformatics

|September 8, 2001

Summary

This study compared 21 protein structure prediction measures, finding that automatic measures closely replicate manual assessments. Combining alignment-dependent and independent methods is recommended for accurate protein model evaluation.

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Area of Science:

Computational biology
Structural bioinformatics
Biophysics

Background:

Protein structure prediction is a key challenge in biology.
The Critical Assessment of protein Structure Prediction (CASP) process evaluates prediction methods.
Existing performance measures require detailed examination.

Purpose of the Study:

To compare 21 different protein structure prediction measures.
To assess the ability of automatic measures to replicate manual assessments.
To inform the development of automatic measures for CASP and benchmarking.

Main Methods:

Compared 21 protein structure prediction measures, including those used in CASP3 and CASP2.
Analyzed the correlation between different measures using 1340 models for 23 targets.

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Evaluated the performance of alignment-dependent and alignment-independent measures.

Main Results:

Most measures show moderate correlation (r ≈ 0.5), with higher correlation for similar measure types.
Automatic measures can reproduce manual assessments with approximately 70% accuracy.
Alignment-independent measures identify more correct folds, while alignment-dependent measures better rank top models.

Conclusions:

Automatic measures can largely reproduce the CASP3 assessor rankings.
A combination of alignment-independent and alignment-dependent measures is optimal for replicating manual scoring.
Sufficient targets ensure manual and automatic measures yield nearly identical results.