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Issues in predicting protein function from sequence.

¹Department of Human Anatomy and Genetics, University of Oxford, UK. Chris.Ponting@anat.ox.ac.uk

Briefings in Bioinformatics

|July 24, 2001

Summary

This summary is machine-generated.

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Predicting gene function from evolutionary relatives (homologues) is complex. This review explores methods for inferring function across scales, emphasizing careful analysis of various biological clues.

Area of Science:

Bioinformatics
Computational Biology
Evolutionary Genomics

Background:

Identifying homologous genes (shared ancestry) is simplified by advanced sequence similarity searches.
Quantifying functional similarity between homologues remains challenging, making function prediction qualitative.

Purpose of the Study:

To review diverse approaches for predicting protein function from atomic to organismal scales.
To highlight the variability in functional similarity among homologues across different scales and protein families.

Main Methods:

Discusses various computational and analytical strategies for inferring gene function.
Emphasizes integrating multiple lines of evidence, including orthologue identification and domain co-occurrence.
Addresses potential pitfalls in database searching, such as amino acid compositional bias.

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Main Results:

Functional similarity between homologues varies significantly depending on the biological scale and protein domain family.
A multi-faceted approach, considering various biological clues, is crucial for accurate function prediction.

Conclusions:

Predicting protein function by homology requires careful consideration of diverse evidence, not just sequence similarity.
Attention to orthologue identification, residue conservation, and domain co-occurrence enhances predictive accuracy.