# LAMA help

- What does LAMA do?
- What can LAMA do for me?
- How does LAMA align blocks?
- Input for LAMA
  - Content of input
  - Format of input
  - Output options
- Output from LAMA
  - Format and content of output
  - Evaluating LAMA alignment scores
- Examples
  - Flavoproteins FAD binding and catalytic sites
  - Snake toxins and the CD59 extracellular domain
  - IS30 transposases DNA-binding domain
  - Hth motifs in the Blocks Database
- Supplements
  - Mean and standard deviation for scores expected by chance
  - Percentile of Z scores expected by chance
- Credits and citation

## What does LAMA do?

LAMA (Local Alignment of Multiple Alignments) is a program for comparing protein multiple sequence alignments with each other. The program can search databases of such multiple alignments. The search is for sequence similarities between conserved regions of protein families. The method is sensitive, detecting weak sequence relationships between protein families. Sequence similarities beyond the range of conventional sequence database searches can be detected by the method.

## What can LAMA do for me?

LAMA can identify protein families similar to your protein(s) of interest and protein motifs similar to conserved regions in your protein(s). The information known about these similar families and motifs can help you identify the function and structure of your protein and locate critical conserved regions in your protein(s). This can direct you in designing experiments to test your hypotheses.

LAMA compares multiple sequence alignments of proteins. If you have only a single protein sequence you first need to find other members of its family. The protein sequences also need to be multiply aligned. The Content of input section explains how to find related sequences and align them.

## How does LAMA align blocks?

The multiple alignments are first transformed into position specific scoring matrices (PSSMs). Each column in the PSSM corresponds to a position in the alignment and has the amino acid distribution of that position. The transformation into the PSSM is done with position-based sequence weights (Henikoff & Henikoff, 1994a) and odd ratios between the amino acid frequencies observed in the multiple alignments and the frequencies expected from protein databases (Henikoff & Henikoff, 1995). The transformation corrects possible overrepresentation of some sequences by sequence weighting and considers the background frequencies of the amino acids. The method was tested and calibrated with ungapped local multiple alignments (blocks) from the Blocks Database .

The matrices are treated as sequences of columns, enabling their alignment with one another. To use algorithms developed for aligning single sequences we need a measure for comparing pairs of matrix columns. This corresponds to the substitution matrices (PAM, BLOSUM etc.) used in single-sequence alignments. The measure used in our method to score the similarity between pairs of matrix columns is the Pearson correlation coefficient (r): where A(i) and B(i) are the values of amino acid i in columns A and B, respectively, and /A and /B are the means of the values in columns A and B. The correlation score ranges from 1 for columns with identical amino acid distributions to -1 for columns with opposite distributions (in each column only 10 amino acids occur and those 10 amino acids are different in the two compared columns).

The score of a block-to-block alignment is the sum of the scores from comparing the corresponding columns in the two block matrices:

    Local alignment of blocks.
    Positions 2 to 7 from block A aligned with positions 4 to 9 from
    block B. A column comparison score, s(Xn*Ym), is calculated for
    each pair of positions (A2*B4 to A7*B9). The score of the alignment
    of the two segments, S, is the sum of the column comparison scores.

The alignment is done using the Smith-Waterman algorithm for optimal local alignments. No gaps are allowed since the aligned objects are short conserved sequence regions. All alignments above the cutoff score are reported for each pair of compared blocks. There may be cases where parts of one long block are similar to several blocks:

    	AAAAAAAAAAAAAAAAAAA
    	 BBB       CCCCCC

## Input for LAMA

### Content of input

LAMA can compare any multiple alignment if it is in the correct format. However, the column comparison measure and the significance estimation of the scores are appropriate for protein sequence blocks - ungapped conserved multiple alignments. The use of other types of multiple alignments, such as global multiple alignments that include many gaps, may give misleading results. For example, the resulting alignments may not be optimal or their significance different from what the output suggests.

If you only have a single protein sequence or want to find more protein sequences related to yours you can search the sequence databases. One way to do this on the WWW is using the BLAST program to search the NCBI sequence databases. Links to other search methods can be found at the Baylor College of Medicine Human Genome Center Search Launcher site.

The BlockMaker WWW site can be used for finding blocks in your group of related protein sequences. There are various other methods for making protein multiple sequence alignments. Among these are the MEME system, Gibbs sampling programs, the MACAW interactive program, and the CLUSTAL-W progressive multiple alignment program. Several of these methods are available through the multiple sequence alignment page at the Baylor College of Medicine Human Genome Center.

Multiple alignments submitted to the program should be of conserved, relatively ungapped, protein sequence regions. A few gaps in the alignment are acceptable. The more sequences are in the alignment the better. In general, avoid alignments with less than 4 sequences.

### Format of input

LAMA only accepts input in the Block format. Other multiple alignments can be reformatted to the Block format. If you are not sure of your multiple alignment or just have a group of related sequences you can use the BlockMaker program for finding blocks in the sequences. Note that to avoid biassed sequence representation blocks include sequence weights.

### Output options

- Output level
The standard output displays pairs of blocks with alignment scores above a Z score cutoff. When both target and query blocks are given by the user there are options for also seeing the column scores composing the alignment score for every reported alignment and the PSSMs of all the compared blocks.
- Score cutoff
The default cutoff value is 5.6 Z scores. When both target and query blocks are given by the user different cutoffs can be specified. Giving a lower value will allow reporting of weaker alignments. Alignments with low values can occur by chance between unrelated blocks. Raising the cutoff score may exclude potentially genuine alignments. The expected number of occurrences should be used to evaluate the alignment scores.

Some of the examples included in this document illustrate the use of the options.

## Output from LAMA

### Content and format of output:

    LAMA version 1.00 October 96.

    Minimal length of reported alignments   4
    Score cutoff is 5.6 Z score units (in the top 7.7e-05 percentile of chance scores)

                                                alignment     Z-score  expected number for
    block 1   from:to       block 2   from:to   length                 searching 5000 blocks
    BL01063B   20 :  46 and BL00042B    3 :  29 (27) score  39 ( 7.2  1.3e-02) [ ?]
    BL01063B    5 :  39 and BL00324C    3 :  37 (35) score  27 ( 6.1  1.5e-01) [ ?]
    BL01063B   12 :  47 and BL00622     8 :  43 (36) score  33 ( 8.2  0.0e+00) [ ?]
    BL01063B   10 :  46 and BL00894A    1 :  37 (37) score  26 ( 5.7  3.2e-01) [ ?]
    BL01063B    4 :  42 and BL01043A    2 :  40 (39) score  29 ( 8.1  0.0e+00) [ ?]

The program version and execution parameters head the search output. Only alignments longer than the minimal length will be reported. The significance of very short alignments (fewer than 4 positions) cannot be reliably estimated. Alignments with scores equal or above the score cutoff will be reported. The score cutoff is specified as a Z score. Z score is the number of standard deviations between the score and the mean score. The mean score and the standard deviations were calculated for the random scores from the alignment of a large number of shuffled unbiassed blocks (7 million block pairs; see first supplement). The Z score is related to the percentile of the score in the shuffled blocks scores. This dependence is not linear but sigmoidal (see second supplement).
For each reported alignment the program shows the names of the two aligned blocks, their position relative to one another, the alignment length, the score, and the expected number of such scores when searching a given number of blocks. The expected number is for chance (random) alignments of unbiassed blocks. It is calculated from the score percentiles between the shuffled unbiassed blocks. In this example the expected number is for searching 5000 blocks. Blocks from the Blocks Database and from the Prints database will be linked to the database entries. The "alignment" link () shows the alignment of the two blocks. This can also be seen by following the "logos" () link that shows the sequence logos of aligned pairs of blocks. Sequence logos are graphical representations of the blocks. For example, here (PostScript viewer required) the logo of block BL00622 is shifted 4 positions relative to the logo of block BL01063B so that their similar segments (8-43 and 12-47) are aligned. Indeed, these segments both contain helix-turn-helix DNA binding motifs.

When both query and target blocks are provided by the user the output can also contain the column scores of each reported alignment and the PSSMs of every compared block.

Pay attention to any error or warning messages. Most will probably have to do with the format of the input.

### Evaluating LAMA alignment scores

The alignment score is the average of the column scores in the alignment multiplied by 100. Since the column scores have a range of -1 to 1 the alignment score will range from -100 to 100. An alignment score of 46 means that on average the aligned positions had a correlation coefficient of 0.46. The significance of the alignment score depends on the length of the compared blocks. Alignments between longer blocks will tend to be longer and have higher scores. The Z score and expected number let us estimate the significance of the scores and to compare alignments of different lengths. The higher the Z score the less likely the alignment is due to chance. How unlikely depends on the number of blocks searched. The more blocks searched the greater the probability to find chance high scores. For example, the output of the calibration with the shuffled blocks contained 7 million scores but no alignments with Z scores greater than 8.3 . Hence an alignment with a score equal or higher than that Z score is unlikely by chance in a comparable or smaller number of alignments. The expected number shows this directly. The expected number is shown for searching 5000 blocks since version 9.1 of the Blocks Database contains 3300 blocks. For example, searching this release of the Blocks Database and finding an alignment expected to appear 1.8e-01 times (0.18) suggests that this alignment is not due to chance. Alignments with expected occurrences of 7.5e-03 or even 0 are almost certainly genuine (or due to biassed blocks, see below).
A relation between two families by a single pair of blocks with a high Z score is termed a single hit. However, protein families often have a number of blocks. A multiple hit is when two or more block pairs from the same two families are similar:

                                                   multiple hit
         Family 1, blocks 1A, 1B, 1C, 1D.         1A=2B + 1D=2C
         Family 2, blocks 2A, 2B, 2C.

We expect the order of the blocks in the hit to be the same in both families (in this example 1A -> 1D and 2B -> 2C).
Individual block pairs with Z scores likely by chance by themselves can still indicate a genuine relation if they are in a multiple hit. While the shuffled blocks scores contained no single hit with Z score above 8.3, there were no multiple hit with Z scores less than 5.6 . Hence genuine relationships can also be indicated by several alignments whose Z scores are individually expected to occur by chance.

When comparing blocks against a database the Z score cutoff is set as 5.6, corresponding to expected occurrence rate of 0.385 per searching 5000 blocks. When both query and target blocks are provided other cutoffs can be chosen.

False positive (high score but no relation) and false negative (low score but genuine relation) hits are still possible and biological knowledge and common sense should be used. Compositionally biassed blocks (consisting of sequence segments rich in a few amino acids or short repeats) are a common cause for false positive hits. You can check if a block is biassed here. False negative hits can be caused by misalignment in the blocks .

Each entry in the Blocks Database version 8.6 (3174 blocks from 858 protein families) was searched against the other entries in the database. All block pairs with Z scores larger than 5.6 were saved. Protein families related by more then one saved score were considered as multiple hits and alignments with Z scores above 8.3 as single hits. This resulted in 141 pairs of families. Eighty percent of these were identified as genuine relationships (true positives) according to the family descriptions, by sharing common sequences, or by detailed examination. Compositional bias was responsible for another eight percent of the high scores. The remaining twelve percent of the high scores could not be classified as either genuine or false based on available evidence.

Distribution of top scoring family pairs
Relation type | Genuine(1) | Biassed Composition | Unknown | Total

    Multiple block hits- independent(2)

      24

      -

      1

      25

                       - repeats(3)

      11

      6

      9

      26

                       - inner repeats(4)

      15

      4

      2

      21

    Single block hits

      63

      1

      5

      69

Total

     113

     11

     17

     141

Fraction

      80%

      8%

     12%

    (1) Genuine relations were identified by the families prosite descriptions,
        detailed analysis of the literature or by sharing common sequences
        (22 of the single and independent-multiple hits).
    (2) An independent multiple hit is two different protein families
        related by two or more different block pairs.
    (3) A repeat multiple hit is two different protein families where a
        block from one family is similar with two or more blocks from the
        other family.
    (4) An inner-repeat multiple hit is a case where the similarities are
        between blocks from the same family.

## Examples

- ### Flavoproteins FAD binding and catalytic sites

  A comparison of all the Blocks Databases v8.6 entries with each other found the following hit between FAD flavoprotein subunits from two oxidoreductase enzyme complexes, BL00504 - succinate dehydrogenases (Sdh) and fumarate reductases (Frd) and BL00677 - D-amino oxidases (DAO):

                                                  alignment     Z-score  expected number for
      block 1   from:to       block 2   from:to   length                 searching 5000 blocks
      BL00504A    2 :  20 and BL00677A    2 :  20 (19) score  51 (10.0  0.0e+00) [logos ?]

  A comparison with a lower cutoff found another hit supporting the first one:

      BL00504D    3 :  35 and BL00677D   17 :  49 (33) score  26 ( 5.5  5.1e-01) [logos ?]

  Sequence annotations and a literature search revealed that block BL00504A is the FAD-binding site and BL00504D is the active site (Birch Machin et al., 1992) of the Sdh/Frd flavoproteins. Block BL00677A is the FAD-binding site of the DAO proteins. The FAD AMP-binding sites in both families are beta-alpha-beta ADP binding folds and were already noted as such (Birch-Machin et al., 1992; Schulz et al., 1982). This explains the first hit.

  The DAO BL00677D block has a conserved histidine important for enzymatic activity of pig DAO (Miyano et al., 1991). This histidine is aligned with a conserved and essential histidine in the Sdh/Frd flavoproteins catalytic site (Birch-Machin et al., 1992; Schroder et al., 1991). Other positions in these aligned regions are also similar (column scores 0.31 to 0.98). The dissimilar positions have column scores close to zero (0.04 to -0.14). This finding suggests that the active site of DAO flavoproteins is in the BL00677D region with the conserved histidine as the crucial residue.

  BLAST and FASTA searches of the SwissProt protein database could not identify this similarity. No sequence from one family identified any sequence from the other family. Optimal local alignments of all the sequence pairs from the two families had scores expected by chance. Searching the Blocks Database with the sequences from the two families identified the relation between the families with 6 Sdh/Frd flavoproteins sequences (multiple hits with 98.1 to 76.2 percentiles of scores with shuffled sequence queries and P values of 8.4*10-3 to 1.1*10-1) but not with the other two sequences from that family or any of the sequences from the DAO family (single hits with less then 60.0 score percentiles).

      Suggested catalytic site of DAO flavoproteins.
      A, positions 17-49 of DAO flavoproteins (block BL00677D) aligned with
      the catalytic region of Sdh/Frd flavoproteins (positions 3-35 of block
      BL00504D). The histidines important for the enzymes catalytic activity
      are outlined (the histidine in sequence DHSA_BACSU is misaligned due to
      a two aa insertion). The start and end coordinates flank the sequences.
      B, the column scores of the alignment.

  Birch-Machin, M. A., Farnsworth, L., Ackrell, B. A., Cochran, B., Jackson, S., Bindoff, L. A., Aitken, A., Diamond, A. G. & Turnbull, D. M. (1992). The sequence of the flavoprotein subunit of bovine heart succinate dehydrogenase. J. Biol. Chem. 267, 11553-11558.

  Miyano, M., Fukui, K., Watanabe, F., Takahashi, S., Tada, M., Kanashiro, M. & Miyake, Y. (1991). Studies on Phe-228 and Leu-307 recombinant mutants of porcine kidney D-amino acid oxidase: expression, purification, and characterization. J. Biochemistry 109, 171-177.

  Schroder, I., Gunsalus, R. P., Ackrell, B. A., Cochran, B. & Cecchini, G. (1991). Identification of active site residues of Escherichia coli fumarate reductase by site-directed mutagenesis. J. Biol. Chem. 266, 13572-13579.

  Schulz, G. E., Schirmer, R. H. & Pai, E. F. (1982). FAD-binding site of glutathione reductase. J. Mol. Biol. 160, 287-308.

- ### Snake toxins and the CD59 extracellular domain

  Conserved regions from snake toxins and the CD59 extracellular domain were found similar to each other. The alignment score is not very striking but the two families seem be quite dissimilar. What is the connection between snake toxins, small extracellular proteins that bind to nerve receptors, and the CD59 domain, a domain that is found in one or more copies on GPI-linked cell surface glycoproteins ? a closer look at the alignment was taken by requesting to see the column scores. These scores are shown above the score line for each of the 12 alignment positions (8,3 to 19,14):

      Column scores for optimal alignment of BL00272B and BL00983B -
        8, 3   9, 4  10, 5  11, 6  12, 7  13, 8  14, 9  15,10  16,11  17,12  18,13 19,14
       0.262  0.169  0.138  0.286  0.995  1.000  0.368  0.224  0.986 -0.067  1.000 1.000
      BL00272B    8 :  19 and BL00983B    3 :  14 (12) score  53 ( 6.5  6.0e-02) [logos ?]

  Five of the positions [(12,7), (13.8), (16,11), (18,13) and (19,14)] have very high column scores (0.986-1.000) indicating identical and almost identical amino acid distribution in these column pairs. The other positions contribute less to the alignment score and position (12,17) has a slightly negative score, actually detracting from the alignment.

  Upon requesting to see the PSSMs of the blocks (below) or their aligned logos (link to 'logos' above) you will note that 3 of the alignment positions contributing to the score are highly conserved cysteine residues. This raises the possibility of identical patterns of disulphide bonds in both regions. We might give this alignment more attention since disulphide bonds are known to be well conserved even between distantly related sequences. More information can be found by following the block links to the Blocks Database entries. Each family is accompanied by its InterPro annotation and the multiple alignment each block can be viewed as a graphical sequence logo. The structures of both proteins are known and confirm their relation. (The SWISS-3DIMAGE was the source for these images of the structures.)

      PSSM of BL00272B

        |                                       1   1   1   1   1   1   1   1   1   1
        |   1   2   3   4   5   6   7   8   9   0   1   2   3   4   5   6   7   8   9
      --+----------------------------------------------------------------------------
      A |   0   0   0  13   0   3   0   0   1   0   2   0   0   0   1   0   2   0   0
      C |  87  12  12  11   0   0   0   0  21   0   6 100 100   0   0   0   0  99   0
      D |   0   0   3   2  11   9   3   2   6   0   0   0   0   3   0  82  10   0   2
      E |   0   5   2   8   3   5   2   9   4   6   9   0   0   7   0   5   5   0   0
      F |   2   3   9   0   0   2   6   4   2   2   0   0   0   0   0   0   0   0   0
      G |   1   1   1   1   3   0  24   8   7   0   0   0   0   2   3   0   1   0   2
      H |   0   0   2   0   0   4   2   0   4   0  13   0   0   6   0   0   0   0   0
      I |   0   0   4   0   2   1   0  17   7  30   3   0   0   0   6   0   0   0   0
      K |   0   3  22   4  30   3   8   5  17   0  24   0   0  16   1   0  36   0   0
      L |   0   0   1   0   1   3   8   3   0  14   5   0   0   0   0   0   2   0   0
      M |   0   0   0   0  11   2   9   0   3   0   3   0   0   0   0   0   0   0   0
      N |   0   0   0   5   2   7   2   2   2   0   2   0   0  16   0  13  22   1  96
      P |   6  65   9   2   3  23   6   8   2   5   0   0   0   0   0   0   0   0   0
      Q |   0   2   6   0   0   1   0   1   6   0   8   0   0   3   0   0   0   0   0
      R |   0   2   4  15   8   2   6   6   2   3   8   0   0  10   0   0  19   0   0
      S |   1   4   4   6  13   3   0   4   6   2   1   0   0  19  16   0   0   0   0
      T |   3   4  14   5   5   5   1   5   0   4   3   0   0  18  72   0   0   0   0
      V |   0   0   3  28   5   1   0  19   1  22   6   0   0   0   0   0   1   0   0
      W |   0   0   0   0   0  22   0   0   0   0   0   0   0   0   0   0   0   0   0
      X |   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      Y |   0   0   5   0   3   2  23   7   9  11   7   0   0   0   0   0   2   0   0
      - |   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0

      PSSM of BL00983B

        |                                       1   1   1   1   1
        |   1   2   3   4   5   6   7   8   9   0   1   2   3   4
      --+--------------------------------------------------------
      A |   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      C |   0   0   0   0   0   0  91 100   0   0   0   0 100   0
      D |   0   0   0   0   0   0   0   0   0   0  76   0   0   0
      E |   0  17  29   0  20   0   0   0   0  42   0   0   0   0
      F |   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      G |  10   0   0   0   0   0   0   0  10   0   0   0   0   0
      H |   0   0   0   0   0  39   0   0   0   0   0   0   0   0
      I |  25   0   0   0   0   0   0   0   0   0   0   0   0   0
      K |   0   0   0  30   0   0   0   0  28  23   0   0   0   0
      L |   0   0  48   0   0   0   0   0   0   9   0 100   0   0
      M |   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      N |  25  23   0  13   0   0   0   0   0   0  24   0   0 100
      P |   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      Q |   0  15   0   0   0  13   0   0  29   0   0   0   0   0
      R |   0  12   0  12   0   0   0   0  24   0   0   0   0   0
      S |   0  20   0  11   0  18   0   0   9  12   0   0   0   0
      T |  23  13   0  23  35  10   0   0   0  14   0   0   0   0
      V |  16   0  22  11   0   8   9   0   0   0   0   0   0   0
      W |   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      X |   0   0   0   0   0   0   0   0   0   0   0   0   0   0
      Y |   0   0   0   0  45  13   0   0   0   0   0   0   0   0
      - |   0   0   0   0   0   0   0   0   0   0   0   0   0   0

  ("X" specifies unknown amino acids.)

- ### IS30 transposases DNA-binding domain

  Excision and insertion of bacterial insertion sequence elements (IS) require the activity of a transposase protein sometimes encoded by the ISs. The IS30 transposase family (Dong et al., 1992) is represented by five blocks in BLOCKS 8.6. A region of 21 positions from the first block had high scores (Z scores 6.7 to 8.8) only to helix-turn-helix DNA-binding motifs (hth) from four protein families (see the figure in the next example). Hth DNA binding motifs occur in many proteins that bind specific DNA sequences (Pabo & Sauer, 1992).

  BLAST searches of the SwissProt protein database with the IS30 sequences did not identify any protein with known hth region. Searching the Blocks Database with the IS30 sequences gave high scores with hth blocks for two of the sequences (98.1 and 93.1 percentiles of scores with shuffled sequence queries (Henikoff & Henikoff, 1994)). The other two sequences had low scores with hth blocks (30.8 and 18.1 score percentiles) and higher scores with non-hth blocks. However, each of the transposases putative DNA binding regions was detected by the method of Dodd and Egan (Dodd & Egan, 1990) as an almost certain hth domain.

  Classification of the first IS30 block as a hth motif is supported by the finding that the N-terminal region of an IS30 transposase, containing the putative hth DNA-binding region, binds the IS30 element (Stalder et al., 1990).

      Hth-like region in IS30 transposases.
      Block BL01043A of the IS30 transposases family. The regions similar to
      the hth motifs in the block to block searches are underlined. The start
      and end coordinates flank the sequences. The diagram shows the suggested
      position of the hth motifs found by the hth  algorithm (Dodd & Egan, 1990).
      The algorithm scores for hth motifs were 5.19 standard deviation
      units (SD), corresponding to 100% probability for TRA1_STRSL, 5.95 SD
      and 100% for TRA4_BACFR, 4.13 SD and 90% for TRA8_ALCEU, and 5.72 SD and
      100% for TRA8_ECOLI.

  Dodd, I. B. & Egan, J. B. (1990). Improved detection of helix-turn-helix DNA-binding motifs in protein sequences. Nucl. Acid. Res. 18, 5019-5026.

  Dong, Q., Sadouk, A., van der Lelie, D., Taghavi, S., Ferhat, A., Nuyten, J. M., Borremans, B., Mergeay, M. & Toussaint, A. (1992). Cloning and sequencing of IS1086, an Alcaligenes eutrophus insertion element related to IS30 and IS4351. J. Bacteriol. 174, 8133-8138.

  Henikoff, S. & Henikoff, J. G. (1994). Protein family classification based on searching a database of blocks. Genomics 19, 97-107.

  Pabo, C. O. & Sauer, R. T. (1992). Transcription factors: structural families and principles of DNA recognition. Annu. Rev. Biochem. 61, 1053-1095.

  Stalder, R., Caspers, P., Olasz, F. & Arber, W. (1990). The N-terminal domain of the insertion sequence 30 transposase interacts specifically with the terminal inverted repeats of the element. J. Biol. Chem. 265, 3757-3762.

- ### Hth motifs in the Blocks Database

  In comparing the entries in the Blocks Database v8.6 among themselves all fourteen hth blocks had high scores with two or more other hth blocks (Figure). The two high scoring non-hth blocks could be distinguished by relating to single hth block and having lower scores relative to the ones between the hth blocks. The blocks are from four types of protein families - bacterial regulatory proteins, homeobox domain proteins, sigma bacterial transcription initiation factors and IS transposases. Manual inspection of the Prosite annotation of the protein families in the Blocks Database and of blocks themselves found no other hth blocks in the database.

  The hth blocks included different number of sequences, from 4 to 185. There was no correlation between the number of sequences in a block and its relation to other blocks. This suggests that even blocks with 4-6 sequences can give a correct representation of conserved protein domains. More than 90% of the blocks in the database used had more than four sequences. This fraction is increasing with each release (>94% in BLOCKS 9.0) as the number of new protein sequences is higher than the number of new protein families (Green et al., 1993; Koonin et al., 1995; Koonin et al., 1994).

  Hth blocks illustrate the problem of distinguishing genuine relationships from chance ones and suggest a solution. Two of the hth blocks (BL00622 and BL01063B) lie below the threshold for detection single-hit relations (Z score >=8.3, bold lines in Figure). Protein families with hth-motifs usually have no other common blocks to support the relation between the hth blocks. However, hth motifs are found in several protein families. These hth blocks all have high scores with each other, but not all these scores are high enough to identify genuine relationships by themselves. Nevertheless, blocks with a number of such scores to known hth blocks can be identified as hth blocks too. The two non-hth blocks have high scores to single hth blocks, and do not form part of the connected graph. An analogous strategy is the basis for detecting weak similarities in single-sequence alignments using the BLAST3 program (Altschul & Lipman, 1990).

      High scores of helix-turn-helix DNA binding blocks.
      All 14 hth blocks found in BLOCKS 8.6 and their high scoring relationships
      with each other (true positives) and with other blocks (false positives,
      outward pointing lines). Each block had different sequences except two pairs
      of homeobox blocks that had common sequences (BL00027 with BL00032B and with
      BL00035B). Lines show scores above the 5.6 Z score cutoff. Thick lines
      correspond to scores above the 8.3 Z score cutoff. BRP - bacterial
      regulatory proteins.

  Since all the hth blocks are similar to one another we examined how well would one composite hth block identify other hth blocks. The ecmot database (Koonin et al., 1995) contains such a composite hth block, with 609 sequence segments from many hth families. The graphical representation (logo) of this block illustrates the conservation in each of its positions. This and the avoidance of particular amino acids at specific positions can also be seen in the PSSM of block EC0157. This block had high scores with 18 blocks in Blocks Database v8.6 (Table). Fourteen of those are the hth blocks discussed above. All the hth blocks had high to extremely high scores, the lowest one expected to occur 3.2e-3.
  (Here you will find block EC0157 in a format you can use in a LAMA search.)

  The four blocks at the end of the table have significantly lower scores (Z 5.6-6.5). These are non-hth blocks but their similarity to the composite hth block can be explained. Two of the blocks are from bacterial regulatory proteins families, occurring C-terminal to the hth motifs. One is a hth-similar region from the araC family (Brunelle & Schleif, 1989) and the other corresponds to the hth helix3 and DNA binding hinge helix in the E.coli lac repressor protein (Lewis et al., 1996). Another block is from the S3 ribosomal proteins (BL00548A). This protein binds RNA, and it is interesting to note the recent report of the RNA binding activity by a hth domain (Dubnau & Struhl, 1996). The last non-hth block is from L-lactate dehydrogenase (LDH) proteins. LDHs do not bind DNA but the crystal structure of the detected region (alpha-2f to Beta-G) is a helix-turn followed by a helix or strand in different proteins (Abad Zapatero et al., 1987; Grau et al., 1981; Iwata & Ohta, 1993).

  Blocks similar to composite hth block EC0157

      Protein family (1)

      Z  score

      'Homeobox' domain proteins

      18.4

      'Homeobox' antennapedia-type proteins

      13.2

      'POU' domain proteins

      11.7

      BRP crp family

      12.1

      BRP gntR family

      12.4

      BRP lysR family

      14.4

      BRP lacI family (2)

      11.7

      BRP luxR family

      12.4

      BRP arsR family

       8.0

      BRP deoR family

       8.7

      BRP tetR family

      14.1

      Sigma-54 factors family

       7.8

      Sigma-70 factors ECF subfamily

       8.3

      Transposases, IS30 family

      11.2

      BRP araC family

       6.5

      BRP lacI family (2)

       6.6

      Ribosomal S3 proteins

       5.8

      L-lactate dehydrogenase family

       5.8

      (1) The family Blocks Database entry numbers are in the previous figure
          except for BRP araC family - BL00041, L-lactate dehydrogenase - BL00064D
          and Ribosomal protein S3 proteins - BL00548A.
          The non-hth blocks are separated at the end of the table.
      (2) Two blocks from the lacI hth family are similar to the composite hth block -
          block BL00356A, the hth region, and block BL00356B, the following
          DNA-binding hinge region.

  Identifying all the hth regions in the Blocks Database illustrates the potential of the multiple alignment comparison method as an aid for annotating protein-family databases. Besides identifying the function of unknown regions, the approach outlined in this example can be useful in annotating databases that generate the multiple alignments automatically. Multiple alignments of characterized protein motifs (such as the hth, nucleotide binding folds or leucine zipper) could be used to identify other multiple alignments containing these motifs.

  Altschul, S. F. & Lipman, D. J. (1990). Protein database searches for multiple alignments. Proc. Natl. Acad. Sci. USA 87, 5509-5513.

  Abad Zapatero, C., Griffith, J., Sussman, J. & Rossmann, M. (1987). Refined crystal structure of dogfish M4 apo-lactate dehydrogenase. J Mol Biol 198, 445-467.

  Brunelle, A. & Schleif, R. (1989). Determining residue-base interactions between AraC protein and araI DNA. J Mol Biol 209, 607-622.

  Dubnau, J. & Struhl, G. (1996). RNA recognition and translational regulation by a homeodomain protein. Nature 379, 694-699.

  Grau, U., Trommer, W. & Rossmann, M. (1981). Structure of the active ternary complex of pig heart lactate dehydrogenase with S-lac-NAD at 2.7 A resolution. J Mol Biol 151, 289-307.

  Green, P., Lipman, D., Hillier, L., Waterston, R., States, D. & Claverie, J. M. (1993). Ancient conserved regions in new gene sequences and the protein databases. Science 259, 1711-1716.

  Iwata, S. & Ohta, T. (1993). Molecular basis of allosteric activation of bacterial L-lactate dehydrogenase. J Mol Biol 230, 21-27.

  Koonin, E., Tatusov, R. & Rudd, K. (1995). Sequence similarity analysis of Escherichia coli proteins: functional and evolutionary implications. Proc Natl Acad Sci USA 92, 11921-11925.

  Koonin, E. V., Bork, P. & Sander, C. (1994). Yeast chromosome III: new gene functions. EMBO J. 13, 493-503.

  Lewis, M., Chang, G., Horton, N. C., Kercher, M. A., Pace, H. C., Schumacher, M. A., Brenan, R. G. & Lu, P. (1996). Crystal Structure of the Lactose Operon Repressor and Its Complexes with DNA and Inducer. Science 271, 1247 1254.

## Supplements

To calibrate the LAMA scores the Blocks Database was purged from biassed blocks, the PSSMs of the remaining blocks were each shuffled and then compared against the blocks from the unshuffled database. The best score from each of the resulting 7 million comparisons was saved. These scores are due to chance and were used to estimate the significance of alignment scores between blocks. The mean and variance of chance alignments depend on the length of the compared blocks. Longer blocks will give longer alignments and higher scores by chance alone. Grouping the chance scores by the length of the shorter block in each comparison gave very similar score distributions. The mean and standard deviation of each group was used to transform each score into a Z score. The percentiles of all these Z scores was then calculated. These percentiles are used to estimate the expected number each score should appear not due to genuine relationship.

Following are links to tables with this data. Note that the scores in the tables are the raw scores of the alignments. The scores shown in the LAMA output are normalized by dividing the raw score by the alignment length.

- Mean and standard deviation for scores expected by chance
- Percentile of Z scores expected by chance

## Credits and citation

The multiple alignment comparison method and LAMA program were developed by Shmuel Pietrokovski in the lab of Steve Henikoff at the Fred Hutchinson Cancer Research Center, Seattle.

An article describing the method and its uses
"Searching Databases of Conserved Sequence Regions by Aligning Protein Multiple-Alignments"
appeared in Nucleic Acids Research 24(19) 3836-3845 (October 96'). This article should be cited in research using this method.

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Page last modified <MODIFICATION_DATE>January 1997</MODIFICATION_DATE> (thanks for Liz G.Wiz for useful comments)