Computational sequence analysis revisited: new databases, software tools, and the research opportunities they...

Area of Science:

• Bioinformatics
• Computational Biology
• Molecular Biology

Background:

• Increasing volumes of protein and nucleic acid sequence/structural data present challenges and opportunities.
• Emerging practical computer tools facilitate data analysis and information retrieval for researchers.

Purpose of the Study:

• To discuss recent advancements in computational tools for analyzing biological sequence and structural data.
• To illustrate these methods with practical examples in lipid research.
• To highlight the utility of these tools for discovering relationships and insights in protein families.

Main Methods:

• Fast database searching algorithms.
• Multiple sequence alignment techniques.
• Molecular modeling and 3D structure analysis.
• Development of windows-based, mouse-driven software for information retrieval.

Main Results:

• Determined connections between cholesteryl ester transfer protein, bactericidal permeability-increasing protein, and lipopolysaccharide-binding proteins.
• Identified novel repetitive sequence motifs in mammalian and yeast prenyltransferases.
• Gained biochemical insights into human apolipoprotein D using insect lipocalin models.
• Reviewed the relationship between apolipoprotein D and human breast gross cystic disease fluid protein.
• Described prospects for modeling apolipoprotein E-related proteins.

Conclusions:

• New computational tools are essential for navigating and interpreting large-scale biological data.
• These tools significantly advance lipid research by enabling detailed sequence and structural analysis.
• The described methods and databases provide valuable resources for future biomedical research.