PSI-Blast.

        PSI stands for Position Specific Iterated.  This search method makes use of a profile, which is a position-specific accounting of what amino acid residues are found in a family of aligned homologous proteins.  PSI-Blast accepts a protein sequence as input and first conducts a normal BlastP search to identify homologues in the database.  A profile is constructed from the spectrum of sequences found in the initially identified homologues.  This profile is used as the search key to identify more distant relatives.  The process is then iterated, each time refining the profile based on inclusion of the new members.  Ideally, the process is expected to converge on a unique set of genes.  In practice, the search may at some point begin to include proteins that are related by chance similarity.  The user must use judgement to recognize when proteins of known and unrelated functions begin to appear in the list of finds.
 

Access to Psi-Blast.

Pro's and con's of using Psi-Blast in the different environments:

• At NCBI:
• Has the most features, and new features show up here first.
• Has the most flexible formatting of results
• Has the most flexible means for confining searches to subsets of the database.
• Plentiful documentation, although some documents are out of date.
• Turn around from site sometimes bogs down.
• Interface requires user to reinitiate each iteration.  This allows some tinkering with the sequences that make up the PSSM for the next iteration.  It also makes working through multiple iterations somewhat tedious.
• NetPsiBlast at UTHSCSA
• Note that this is not the same as NetBLASt command in the GCG package.
• Accessible by a standard web browser interface by individuals with a UTHSCSA bioinf account.
• Main benefit: Fast turnaround, because access is limited to UTHSCSA account holders.
• This is a slightly less full-featured Psi-Blast server than the one implemented directly at NCBI.  For an accounting of differences in capabilities see the local blast help file.  This server can be found implemented at other computing centers.  The thing to pay attention to from one site to the next is what is the database searched and how up-to-date is it.
• UTHSCSA databases are nightly updated mirrors of NCBI's databases.
• Similar interactive interface as at NCBI, requiring resubmission of each iteration.
• Links to sequences in the output are back to Entrez at NCBI, not to the local database.
• Stand alone Blast suite at UTHSCSA
• Accessed from a terminal window by the command blastpgp.  For syntax and options see the local blast help file.
• Searches the local UTHSCSA-maintained databases, so may be faster than the NCBI web site at times.  But it is slower than the web interface.
• Main benefit: has many options not available in the web interfaces, including batch searches and automatic multi-iteration searches.  See the local blast help file for summary of uses.
• GCG PSIBLAST at UTHSCSA
• By default this searches the local GCG databases, which are out-of-date.
• Use the -INfile2=$BLAST_DB/<database name> parameter on the command line to direct it to search the daily updated databases instead.  See the list of local blast databases for names of valid databases.
• Has fewer capabilities than the Blast suite blastpgp program.  Type genhelp PSIBLAST for summary of features.
• Main benefit: uses GCG formatted search key.
• GCG SeqWeb PSIBLAST at UTHSCSA - has been discontinued.
 

BLAST page  with references and tutorials.

BLAST FAQs.

Blast Help Page.

Profiles.

Reference:

Summary of the algorithm.

1. The method of searching with a profile is to assign a weight at each position depending on how frequently the observed residue appears in that position in a set of aligned sequences that are believed to be valid representatives of the family, and then to combine these weights into a total matching score.
1. The aligned sequences are called a "training set".
2. The formal mathematical name for this construct is a "Hidden Markov Model" or HMM.  See  Sean Eddy's description of the program HMMer 2.1.1 (http://hmmer.wustl.edu/) for commentary on the variety of HMM engines in use.
3. Some documentation has taken to calling the profile a "consensus".  This is confusing, since "consensus" has long been used to mean a single sequence composed of  the most common residue at each position in a multiple alignment.
2. Whereas it would also be possible to use position-specific gap penalities, PSI-blast uses the same gap penalty function as ordinary blast.
3. The position specific matrix used is a composite of a standard substitution matrix and the information derived from the aligned sequence.  Hence one starts with a reasonable scoring matrix and biases it towards the residues found in homologues.  This prevents poor performance in the typical case where the aligned sequences are too few to independently generate a statistically valid position-specific matrix.
4. Sequences that are marginally included at one iteration can be tossed out in a later iteration.  However, the original key is always included.  The algorithm has a vulnerability to including a nonhomologue by chance matching and then dragging in more sequences related to the errant one such that the profile is taken over by an unrelated family.  The biased retention of the original key provides some resistance against that happening.

Tutorial.

        However, reciprocol inclusion may also fail for meaningful relationships.  Note the paper by Avarind, L. and Koonin, E.V.  [(1999) Gleaning non-trivial structural, functional and evolutionary information about proteins by iterative database searches. J. Mol. Biol, 287:1023-1040] cited on the reading list of the BLAST tutorial page.  It emphasizes how the ability of PSI-blast to bridge to divergent families is dependent on there being a range of close and medium related proteins in the database with which to build the profile.   Hence, if your protein sequence fails to hit much in the first iteration, you could still ask if it belonged to a postulated distant family by keying the PSI-blast search with a member of that family and seeing if you protein became included.

        If your sequence is not in GenBank, then there does not appear to be a simple way to include it other than as the key.  You can consider some closely related sequence that is in GenBank as a surrogate.  It is also possible to download PSI-blast and the relevant part of the database and search on your own computer where you can include arbitrary sequences.
 

Options.

Limit by Entrez Query.

• Over some years the limit was dropped on subsequent Psi-Blast iterations.  In other years the limit was maintained in subsequent iterations.
• Recently (10/14/2006) the convention that multiword identifiers should be enclosed in qoutes was altered.  "Homo sapiens"[orgn] now returns no sequences but Homo sapiens[orgn] returns human sequences.  This implies that other elements of the Entrez query language may not work as expected, so controls would be advisable when using this feature.  This has been reported to NCBI, and presumably may change again.  The Entrez limit box on the format part of the Psi-Blast page and Entrez itself continue to work according to the previous convention.

Related programs.

• PHI-Blast and regular expression searching.
• BlastP - The first round of Psi-Blast is the same as BlastP.  If one isn't looking for distant homologues, then BlastP will suffice.  In addtion to the above sites, BlastP is available at all major bioinformatics sites.  Some commercial DNA analysis packages contain Psi-Blast clients.  A Psi-Blast client submits the search over the internet to another site (usually NCBI), and retieves the results.  Three such packages with a site liscense at UTHSCSA are the Wisconsin GCG package, Lasergene (DNA star), and Vector NTI.  Vector NTI advocates a storage system for Blast results.  You can also download a BlastP client for virtually any platform from NCBI.
• Psi-Tblastn: This is a strategy to make a PSSM by Psi-Blast in the normal way, and then use it to search a DNA sequence in all 6 frames.  Psi-Tblastn is implemented in the Standalone Blast Suite on bioinf.
• RPS-Blast - The key sequence is searched versus a library of premade PSSMs representing known protein families.  RPS-Blast can be accessed at NCBI CDD search page.  An RPS-Blast search is automatically conducted during Psi-Blast searching at NCBI if the CD-search box is checked on the submission form.  RPS-Blast can be run from the UTHSCSA NetBlast page, and from the linux command line (local blast help file).
• HMMER.  HMMER searches are a similar strategy to RPS-Blast.  HMMER uses a Hidden Markov Model (HMM) rather than a PSSM to represent the known protein families.  HMMs are more efficient at dealing with gaps in comparisons between distant homologues.  The best place to search a sequence against libraries of protein families is at the Sanger Center Pfam site.  See also the local HMMER help file, and comparison of different protein family alignment tools, for the capabilities of the UTHSCSA HMMER installation.
• SAM.  For matching a sequence to the greatest range of superfamily members, use SAM.  A sequence can be extensively analyzed to the level of fold recognition at the UCSC SAM site.  See also the local SAM help file, for extended capabilities offered by the local installation of the SAM suite.
• PsiPred - Psipred is a secondary structure prediction system that first aligns homologues using Psi-Blast, and then issues a consensus secondary structure prediction.  PsiPred predictions can be done at the Psipred web site.  PsiPred can also be run locally from bioinf.