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Target selection for structural genomics.

¹Department of Plant & Microbial Biology, University of California, Berkeley 94720-3102, USA. brenner@compbio.berkeley.edu

Nature Structural Biology

|December 5, 2000

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Structural genomics generates protein models using high-throughput methods. Target selection computationally identifies tractable proteins with unknown structures for experimental characterization.

Area of Science:

Proteomics and structural biology
Computational biology and bioinformatics

Background:

Structural genomics aims to create a comprehensive catalog of protein structures.
Experimental structure determination (crystallography, NMR) is resource-intensive.

Purpose of the Study:

To define and outline the computational process of target selection in structural genomics.
To prioritize protein targets for structure determination based on tractability, novelty, and accessibility.

Main Methods:

Computational analysis of protein databases to identify candidate proteins.
Filtering candidates based on structural tractability and novelty (unknown structure).
Prioritization algorithms considering biological interest and experimental accessibility.

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Main Results:

A defined computational pipeline for selecting protein targets.
Criteria for assessing protein tractability and accessibility are established.
Prioritization framework balances scientific interest with experimental feasibility.

Conclusions:

Computational target selection is crucial for efficient structural genomics.
A systematic approach ensures resources are focused on high-value, achievable protein structure targets.
This strategy accelerates the expansion of the protein structure database.