TUTORIAL: PAIRWISE SIMILARITY SEARCHES

ALIGN documentation: $doc/fasta/align.txt
LALIGN documentation: $doc/fasta/lalign.txt
PRSS documentation: $doc/fasta/prss.txt

Example: Antifreeze Proteins

The goal of the previous tutorial ( RetrievingSequences by Keyword), was to retrieve entries containing antifreeze proteins. A set of PIR entries whose annoatation contained the word 'antifreeze'was retrieved into the file antifreeze.pir .Inspection of this file shows that antifreeze proteins from a number of species were retrieved. It is not immediately apparent whether all belong to a single family. This tutorial will illustrate how similarity between related proteins can be analyzed.

1. Read entries into GDE

GDE can read GenBank entries from the Open menu, but not PIR entries. To read PIR entries, choose File --> Import Foreign Format, and type in the name of the file. Don't forget to press Enter after the end of the filename.

2. Comparisons between two closely-related sequences

To illustrate a pairwise comparison between two closely-related sequences, select two antifreeze proteins, A30238 and A31075. Before running any of the Needleman-Wunsch type alignment programs, it's worth doing a dot-matrix plot of these proteins using Similarity --> PXHOM, with COMPRESSION=4 and MIN. PERCENT SIMILARITY=30. [A30238vsA31075.p1hom ]. Note, PXHOM is the protein counterpart of DXHOM.

ALIGN performs rigorous global alignments. That is, all of both proteins is fit into the alignment. Choose Similarity --> ALIGN to get the ALIGN menu:

Since these sequences are known to be very closely-related, it probably makes sense to use a menu like PAM120, rather than the default, for the most precise score.

ALIGN calculates a global alignment of two sequences
 version 2.0uPlease cite: Myers and Miller, CABIOS (1989) 
>A30238 88 bp                                        88 aa vs.
>A31075 87 bp                                        87 aa
scoring matrix: /home/psgendb/dat/fasta/pam120.mat, gap penalties: -12/-4
80.7% identity;         Global alignment score: 372

               10        20        30        40        50        60
gde208 MKSAILTGLLFVLLCVDHLSSASQSVVATQLIPINTALTPIMMKGQVVNPAGIPFAEMSQ
       :::.::::::::::::::.. ::::::::::::.:.::::.:: :.:.:: :::::::::
A31075 MKSVILTGLLFVLLCVDHMT-ASQSVVATQLIPMNSALTPVMMEGKVTNPIGIPFAEMSQ
               10        20         30        40        50         

               70        80        
gde208 IVGKQVNRPVAKDETLMPNMVKTYRAAK
       .:::::::::::..:.:::::::: :.:
A31075 MVGKQVNRPVAKGQTIMPNMVKTYAAGK
      60        70        80

(Note on output: Two windows will pop up, the output from the search and a narrow window with names of sequences in the search file.The latter can usually be discarded.)

When similarity is this high, it is easier to view the mismatches, rather than the matches:

ALIGN calculates a global alignment of two sequences
 version 2.0uPlease cite: Myers and Miller, CABIOS (1989) 
>A30238 88 bp                                        88 aa vs.
>A31075 87 bp                                        87 aa
scoring matrix: /home/psgendb/dat/fasta/pam120.mat, gap penalties: -12/-4
80.7% identity;         Global alignment score: 372

               10        20        30        40        50        60
gde208 MKSAILTGLLFVLLCVDHLSSASQSVVATQLIPINTALTPIMMKGQVVNPAGIPFAEMSQ
          x              xx             x x    x  X x x  X         
A31075 MKSVILTGLLFVLLCVDHMT-ASQSVVATQLIPMNSALTPVMMEGKVTNPIGIPFAEMSQ
               10        20         30        40        50         

               70        80        
gde208 IVGKQVNRPVAKDETLMPNMVKTYRAAK
       x           xx x        X x 
A31075 MVGKQVNRPVAKGQTIMPNMVKTYAAGK
      60        70        80

3. Comparisons between two distantly-related sequences

The file antifreeze.pir also contains proteins from a number of species.Dot-matrix analysis shows that antifreeze proteins A31075 and B30839 from Macrozoarces americanus (ocean pout) have diverged substantially.This is illustrated in a dot-matrix search [A31075vsB30839.p1hom ].

The ALIGN output also shows substantial divergence, compared to that seen for among the two proteins.

ALIGN calculates a global alignment of two sequences
 version 2.0uPlease cite: Myers and Miller, CABIOS (1989) 
>A31075 87 bp                                        87 aa vs.
>B30839 91 bp                                        91 aa
scoring matrix: BLOSUM50, gap penalties: -12/-2
62.6% identity;         Global alignment score: 330

               10        20         30        40        50         
gde208 MKSVILTGLLFVLLCVDHMT-ASQSVVATQLIPMNSALTPVMMEGKVTNPIGIPFAEMSQ
       :::::::::::::::::::. :.::::::::::.:.::: :::  .:  : :::  .. .
B30839 MKSVILTGLLFVLLCVDHMSSANQSVVATQLIPINTALTLVMMTTRVIYPTGIPAEDIPR
               10        20        30        40        50        60

      60        70        80          
gde208 MVGKQVNRPVAKGQTIMPNMVKTYA--AGK-
       .:. :::. :  : :.::.::: :   : : 
B30839 LVSMQVNQAVPMGTTLMPDMVKFYCLCAPKN
               70        80        90

4. Comparison of sequences with low similarity

Not all similarities will be as straightforward to interpret as those shown above. A dot-matrix search between antifreeze glycopreptide AFGP polyprotein precursors from the arctic fish Boreogadus saida and yeast reveals little obvious similarity. [T44768vsT51008.p1hom ]

For sequences that are not closely-related, it is not appropriate to use global alignment programs such as ALIGN, because a global alignment tries to force all parts of both sequences into an alignment, regardless of whether those parts share significant similarity. LALIGN and LFASTA search for local alignments, building alignments locally until extension of the alignment results in a decreased, rather than an in increased score.

Select T44768 and T51008 and choose Similarity --> LALIGN. The LALIGN menu will pop up. Since we're assuming distant relationships, choose the BLOSUM50 scoring matrix. The output gives several alignments, the longest shown below: