The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.

/pdf/the-protein-data-bank-4lbxxcio6v.pdf

The Protein Data Bank

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

/pdf/initial-sequencing-and-analysis-of-the-human-genome-5dapk1rsx1.pdf

Initial sequencing and analysis of the human genome.

Protein identification and analysis software performs a central role in the investigation of proteins from two-dimensional (2-D) gels and mass spectrometry. For protein identification, the user matches certain empirically acquired information against a protein database to define a protein as already known or as novel. For protein analysis, information in protein databases can be used to predict certain properties about a protein, which can be useful for its empirical investigation. The two processes are thus complementary. Although there are numerous programs available for those applications, we have developed a set of original tools with a few main goals in mind. Specifically, these are: 1. To utilize the extensive annotation available in the Swiss-Prot database wherever possible, in particular the position-specific annotation in the Swiss-Prot feature tables to take into account posttranslational modifications and protein processing. 2. To develop tools specifically, but not exclusively, applicable to proteins prepared by two dimensional gel electrophoresis and peptide mass fingerprinting experiments. 3. To make all tools available on the World-Wide Web (WWW), and freely usable by the scientific community. In this chapter we give details about protein identification and analysis software that is available through the ExPASy World Wide Web server.

Protein identification and analysis tools in the ExPASy server

Countless millions of people have died from tuberculosis, a chronic infectious disease caused by the tubercle bacillus. The complete genome sequence of the best-characterized strain of Mycobacterium tuberculosis, H37Rv, has been determined and analysed in order to improve our understanding of the biology of this slow-growing pathogen and to help the conception of new prophylactic and therapeutic interventions. The genome comprises 4,411,529 base pairs, contains around 4,000 genes, and has a very high guanine + cytosine content that is reflected in the biased amino-acid content of the proteins. M. tuberculosis differs radically from other bacteria in that a very large portion of its coding capacity is devoted to the production of enzymes involved in lipogenesis and lipolysis, and to two new families of glycine-rich proteins with a repetitive structure that may represent a source of antigenic variation.

/pdf/deciphering-the-biology-of-mycobacterium-tuberculosis-from-56gdir9h56.pdf

Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequence

Summary : The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available, HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise. Contact: eddy@genetics.wustl.edu.

Profile hidden Markov models.

The PROSITE database consists of biologically significant patterns and profiles formulated in such a way that with appropriate computational tools it can help to determine to which known family of protein (if any) a new sequence belongs, or which known domain(s) it contains.

/pdf/the-prosite-database-its-status-in-1997-1pn4nq9kcj.pdf

The PROSITE database, its status in 1997

The PROSITE database (http://www.expasy.ch/sprot/prosite.htm l) consists of biologically significant patterns and profiles formulated in such a way that with appropriate computational tools it can help to determine to which known family of protein (if any) a new sequence belongs, or which known domain(s) it contains.

/pdf/the-prosite-database-its-status-in-1999-l8zye6m03u.pdf

The PROSITE database, its status in 1999.

A general syntax for expressing biomolecular sequence motifs is described, which will be used in future releases of the PROSITE data bank and in a similar collection of nucleic acid sequence motifs currently under development. The central part of the syntax is a regular structure which can be viewed as a generalization of the profiles introduced by Gribskov and coworkers. Accessory features implement specific motif search strategies and provide information helpful for the interpretation of predicted matches. Two contrasting examples, representing E. coli promoters and SH3 domains respectively, are shown to demonstrate the versatility of the syntax, and its compatibility with diverse motif search methods. It is argued, that a comprehensive machine-readable motif collection based on the new syntax, in conjunction with a standard search program, can serve as a general-purpose sequence interpretation and function prediction tool.

/pdf/a-generalized-profile-syntax-for-biomolecular-sequence-3t3ro8ia4z.pdf

A Generalized Profile Syntax for Biomolecular Sequence Motifs and its Function in Automatic Sequence Interpretation

PROSITE is a compilation of sites and patterns found in protein sequences; it can be used as a method of determining the function of uncharacterized proteins translated from genomic or cDNA sequences

/pdf/prosite-recent-developments-xxd2xkjllh.pdf

PROSITE: recent developments

The PROSITE database consists of biologically significant patterns and profiles formulated in such a way that with appropriate computational tools it can help to determine to which known family of proteins (if any) a new sequence belongs or which known domain(s) it contains.

Philip Bucher

Papers

The PROSITE database, its status in 1997

The PROSITE database, its status in 1999.

A Generalized Profile Syntax for Biomolecular Sequence Motifs and its Function in Automatic Sequence Interpretation

PROSITE: recent developments

The PROSITE Database, Its Status in 1995