Understanding the cell in terms of structure and function: insights from structural genomics

Area of Science:

• Biochemistry
• Structural Biology
• Bioinformatics

Background:

• Structural genomics initiatives are producing a large number of protein structures.
• The focus on structural novelty is rapidly advancing our understanding of protein folds.
• This growth presents a challenge in annotating the function of newly discovered protein structures.

Purpose of the Study:

• To address the challenge of structure-based function annotation for proteins with limited known information.
• To highlight the development and diversity of bioinformatics approaches for predicting protein structure function.
• To explore methods for integrating various data sources to improve function prediction.

Main Methods:

• Utilizing a growing database of experimentally determined protein structures.
• Employing diverse bioinformatics algorithms for structure-based function prediction.
• Investigating strategies for data integration from multiple sources.

Main Results:

• Significant progress in cataloging the protein fold universe through structural genomics.
• Emergence of various bioinformatics tools capable of predicting protein function from structure.
• Increasing attention towards combining prediction methods and other data types.

Conclusions:

• The rapid increase in protein structures necessitates advanced methods for function annotation.
• Bioinformatics plays a crucial role in deciphering protein functions from structural data.
• Future efforts should focus on integrating diverse data streams for robust function prediction.