Protein sequence similarity

The mechanisms of corticosteroid receptor regulation of transcription have been elucidated. Both type I and type II corticosteroid receptors are members of a superfamily of ligand-activated transcription factors defined by protein sequence similarity. Included in this superfamily are various other steroid receptors, such as the estrogen receptor, as well as members of the retinoic acid receptor... 

Figure 11,4. ExPASy Proteomic tools. ExPASy server provides various tools for proteomic analysis which can be accessed from ExPASy Proteomic tools. These tools (locals or hyperlinks) include Protein identification and characterization, Translation from DNA sequences to protein sequences. Similarity searches, Pattern and profile searches, Post-translational modification prediction, Primary structure analysis, Secondary structure prediction, Tertiary structure inference, Transmembrane region detection, and Sequence alignment.

Zhang, Z., et al., Protein sequence similarity searches using patterns as seeds. Nucleic Acids Res, 1998. 26(17) p. 3986-90. 

In summary, the gene conservation option provides a compact overview on protein sequence similarities in all genomes included in a dedicated genome browser. 

Globular proteins illustrate the concept of tertiary structure - which arises from folding of the polypeptide chain upon itself. Unlike secondary structure, which is caused by interactions between amino acids close to each other, tertiary structures are seen to be stabilized by interactions between amino acids that are often far apart. Tertiary structures have little regularity. Because they arise from folding of secondary structures, which are dependent on the primary amino acid sequence, tertiary structures are specific for each protein sequence. Similarities in tertiary structure can usually be seen, however, in proteins with similar amino acid sequences. 

Poly(ADP-ribose) polymerase homology to other proteins. Sequence similarity comparison of the polymerase with the National Biomedical Center s protein data bases revealed no extensive identities with other proteins (> 4200 proteins searched). Although no extensive similarities were observed, the polymerase exhibits some short but interesting identities. The most statistictdly significant identity is with the catalytic site of the ricin A chain, a cytotoxic plant protein which inactivates the 60S ribosome. This may represent the active site of the enzyme, based upon the catalytic... 

Hanke and Reich used Kohonen nets as a visualization tool for the analysis of protein sequence similarity (ISO). The proeedure eonverts sequenee (domains, aligned sequences, and segments of seeondary strueture) into a ehar-acteristie signal matrix. This eonversion depends on the property or replaee-ment seore vector selected by the user. The trained Kohonen network is functionally equivalent to an unsupervised nonlinear eluster analyzer. Protein families, or aligned sequences, or segments of similar seeondary strueture aggregate as clusters and their proximity may be inspeeted. 

The protein sequence database is also a text-numeric database with bibliographic links. It is the largest public domain protein sequence database. The current PIR-PSD release 75.04 (March, 2003) contains more than 280 000 entries of partial or complete protein sequences with information on functionalities of the protein, taxonomy (description of the biological source of the protein), sequence properties, experimental analyses, and bibliographic references. Queries can be started as a text-based search or a sequence similarity search. PIR-PSD contains annotated protein sequences with a superfamily/family classification. 

Attempts have also been made at predicting the secondary stmcture of proteins from the propensities for residues to occur in the a-helix or the P-sheet (23). However, the assignment of secondary stmcture for a residue only has an average accuracy of about 60%. A better success rate (70%) is achieved when multiple-aligned sequences having high sequence similarity are available. 

Figure 1 The basis of comparative protein structure modeling. Comparative modeling is possible because evolution resulted in families of proteins, such as the flavodoxin family, modeled here, which share both similar sequences and 3D structures. In this illustration, the 3D structure of the flavodoxin sequence from C. crispus (target) can be modeled using other structures in the same family (templates). The tree shows the sequence similarity (percent sequence identity) and structural similarity (the percentage of the atoms that superpose within 3.8 A of each other and the RMS difference between them) among the members of the family.

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