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

The connection among cholesteryl ester transfer protein, bactericidal permeability-increasing protein, and lipopolysaccharide-binding proteins is determined and novel repetitive sequence motifs in mammalian farnesyltransferase subunits and related yeast prenyltransferases are derived.

Abstract

The increasing quantity and complexity of sequences and structural data for proteins and nucleic acids create both problems and opportunities for biomedical researchers. Fortunately, a new generation of practical computer tools for data analysis and integrated information retrieval is emerging. Recent developments in fast database searching, multiple sequence alignment, and molecular modeling are discussed and windows-based, mouse-driven software for CD-ROM and network information retrieval are described. Each method is illustrated with a practical example pertinent to lipid research. In particular, the connection among cholesteryl ester transfer protein, bactericidal permeability-increasing protein, and lipopolysaccharide-binding proteins is determined; novel repetitive sequence motifs in mammalian farnesyltransferase subunits and related yeast prenyltransferases are derived; biochemical insights from a three-dimensional model of human apolipoprotein D based on two insect lipocalins are discussed; the relationship between apolipoprotein D and gross cystic disease fluid protein from human breast is reviewed; and prospects for modeling apolipoprotein E-related proteins are described. In addition, information on a number of general and special-purpose sequence, motif, and structural databases is included.