Protein Sequence Analyzer
Protein Sequence Analyzer
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The Protein Sequence Analysis (PSA) E-mail server, has been
IMPROVED. Two types of sequence analysis are now supported, and the
server can analyze amino acid sequences of any length upto 1000
residues. In addition, the server uses new models for alpha-beta
proteins containing central beta sheets or beta barrels.
The PSA is available for researchers who have amino acid sequences for proteins of unknown structure and for which no homologous sequences are known. You send the server one amino acid sequence. The server may be instructed to analyze the sequence in either of two ways: using type-1 or type-2 DSMs. (DSMs are Discrete State-space Models for patterns of alpha-helices, strands, tight turns, and loops in specific structural classes).
Type-1 models are for complete sequences from monomeric, single-domain, globular, water-soluble proteins in several recognized structural classes. They are also appropriate for those subsequences of membrane-spanning proteins that are believed to extend beyond the membrane (based on a hydropathy profile). Type-2 models, in contrast, are for either partial or complete sequences from potentially large proteins that violate one or more of the modeling assumptions embodied in Type-1 models. For example, Type-2 models are appropriate for proteins that have one or more of the following properties: (1) they are multimeric; (2) they have more than one structural domain; or (3) they are not globular or soluble (e.g., membrane-spanning proteins).
The PSA server is maintained at the BioMolecular Engineering Research Center of Boston University. For information on usage, send an empty email message to psa-request@darwin.bu.edu with the word "help" in the subject field.
The analysis algorithm is based on optimal filtering and smoothing
algorithms as described in the paper "Structural analysis based on
state-space modeling" by C.M. Stultz, J.V. White, and T.F. Smith,
Protein Science (1993), 2, 305-314. The mathematical basis for the
models and algorithms is presented in "Protein Classification by
Stochastic Modeling and Optimal Filtering of Amino-Acid Sequences," by
J.V. White, C.M. Stultz, and T.F. Smith, Mathematical Biosciences
(1994), 119, 35-75.
Please send your comments and your suggestions to Yves Epelboin, epelboin@lmcp.jussieu.fr .
