A database of patterns PROF_PAT, and
using the patterns to detect local similarities
Theoretical Department, Research Institute of Molecular Biology,
SRC VB 'Vector', Koltsovo, Novosibirsk region, 633159, Russia,
Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia
ABSTRACT
Motivation.
When analyzing novel protein sequences, it is now essential to extend search strategies
to include a range of 'secondary' databases. Pattern databases have become vital tools for
identifying distant relationships in sequences, and hence for predicting protein function
and structure. The main drawback of such methods is the relatively small representation of
proteins in trial samples at the time of their construction. Therefore a negative result
of an amino acid sequence comparison with such a databank forces a researcher to search
for similarities in the original protein banks. We developed a database of patterns
constructed for groups of related proteins with maximum representation of amino acid
sequences of SWISS-PROT in the groups.
Results.
Software tools and a new method have been designed to
construct patterns of protein families. By using such method, a databank of
protein family patterns, PROF_PAT is produced. This bank is based on SWISS-PROT and TrEMBL
banks, and contains patterns of more than 10,000 groups of related proteins in a format
similar to that of the PROSITE. Motifs of patterns, which had the minimum level of
probability to be found in random sequences, were selected. Flexible fast search program
accompanies the bank. The researcher can specify a similarity matrix (the type PAM (PAM,
BLOSUM and other). Variable levels of similarity can be set (permitting search strategies
ranging from exact matches to increasing levels of "fuzziness").
Availability.
The Internet address for comparing sequences with the bank are: http://wwwmgs.bionet.nsc.ru/mgs/programs/prof_pat/.
The local version of the bank and search programs (approximately 50 Mb) are available
via ftp: ftp://ftp.bionet.nsc.ru/pub/biology/vector/prof_pat/,
and ftp://ftp.ebi.ac.uk/pub/databases/prof_pat/.
Contact.
E-mail: bachin@vector.nsc.ru
INTRODUCTION
Up to now, the main method of suggesting possible functions of the newly deciphered
amino acid sequences has been to search them for similarity with sequences available in
protein banks such as PIR (Barker et al., 1999), SWISS-PROT (Bairoch and Apweiler, 1999)
and others. As these banks grow larger, such comparisons become more promising but at the
same time more time-consuming. In addition, in the case of distant proteins the search for
global similarity of complete sequences may fail to show a positive result, because the
conservative blocks responsible for their special functions may prove to be relatively
short and scattered all over the sequence. This may be why a number of works appeared in
the last few years, aimed at the selection of sites in groups of related proteins. These
sites are representative of a protein family as a whole, and both identify new proteins
and refine structural and functional properties of those already known. Such databases as
PROSITE (Hofmann, et al., 1999), BLOCKS (Henikoff and Henikoff, 1991, Henikoff, et al.,
1999), PRINTS (Attwood et al., 1999) are among the most well known and accessible via
Internet. There is also a number of other similar databases i.e. PFAM (Bateman, et al.,
1999), SBASE (Murvai, et al., 1999), IDENTIFY (Nevill-Manning, et al. 1998).
The advantages of such databases, representing protein families, arise from comparing
an amino acid sequence with a relatively small pattern as a representative of a protein
family, and not with a set of long sequences of this family. Furthermore, comparison
algorithms could be simplified because there is no need of sequence alignment, which also
speeds up the process. The level of noise (random similarity) is lower, because comparison
is usually made with patterns that are already characterized and represent conservative
intervals of positions. This appears most clearly when a family is represented by a few
relatively short pattern motifs.
However the common shortcoming found for the most part in secondary databases is the
fact that they contain a limited number of patterns (profiles, motifs, alignments or other
representations of protein families). In general, PROSITE contains
well-defined manually constructed patterns. BLOCKS and PRINTS in the beginning were in
some extent expansions of PROSITE with subsequent developments. IDENTIFY is in turn based
on BLOCKS and PRINTS.
We have devoted our efforts to develop a technique and construct patterns for the
greatest possible number of proteins belonging to the SWISS-PROT+TrEMBL (Bachinsky et al.,
1996, 1997). We are convinced that if a secondary bank is not really representative, it
would not be widely used. It is because of negative results in the comparison of a
sequence with this bank force the user to consult other banks or make direct comparisons
of the sequence with large banks of sequences.
SYSTEMS AND METHODS
Programs for using patterns were written in Microsoft Visual C++ 5.0. for IBM
compatible computers running Windows 95 or Windows NT. Amino acid sequences were taken
from SWISS-PROT and TrEMBL. The selection of related proteins was made using modified
FASTA 2.0. algorithm (Pearson, 1994). Multiple alignments of the amino acid sequences were
performed by means of CLUSTALV program (Higgins, et al., 1992) and the default set of
parameters.
ALGORITHMS
The selection and concurrent alignment of related protein groups. All
full-length sequences of prototype banks that had more than 30 amino acids in lengths were
combined in one file. In order to select groups of related proteins, a special program was
written based on FASTA 2.0 (Pearson, 1994). The first sequence of the file was compared
with all other sequences. The sequences were regarded as similar if score/ln(l1)/ln(l2)*ln100*ln100
>80. The sequences similar in the sense of FASTA form a primary set of related
proteins. Then the next sequence not included in a group of related proteins was compared
with all other proteins, and so on.
It is known that in the case of distant protein homology many algorithms of multiple
alignment lead to doubtful results strongly dependent on parameters such as, insertion
penalties, similarity matrix, etc. To provide quality alignment, the pairwise similarity
level was prescribed 30% or more, for it is known that at smaller similarity global
alignment often makes no sense (Vogt, et al., 1995; Patthy, 1987). Pairwise similarity of
the proteins belonging to a set was assessed by the program CLUSTALV (Higgins et al.,
1992). Then, if not all pairs of proteins had 30% similarity, the set was divided into
subsets so that all pairwise similarities were at least 30%..
Proteins of every subset were aligned together. The files containing aligned sequences
were supplemented with two fields: DE - description(s) of proteins forming the
group, and KW - key words (mainly the union of values of field KW for proteins
falling into the set). Patterns were constructed based on such aligned families.
The construction of patterns of protein families. We will regard the combination
of motifs that represent relatively conservative intervals of positions of aligned
proteins of the family as a pattern of a family of related proteins.
Let there be an interval of positions of an aligned family of related proteins of
length n. Ai denotes a subset of amino acids of 20
standard ones, located in a position i of the interval. An amino acid sequence of
length n will be considered to belong to the given interval (motif), if for every
position ai belongs to i,
where ai is the amino acid located in position i
of the sequence. To every position i of a group of aligned proteins the value 
that is the frequency of occurrence in proteins
one of amino acids from Ai located in this position may
be ascribed. Here pl is the frequency of occurrence in
proteins of amino acid al, located in this position. Qj
- the product of the values Pi for positions falling into
interval of positions j may accordingly be the characteristic of this interval. The
value Qj constitutes an assessment of probability that a
random amino acid sequence of length n will belong to interval j. The
smaller Qj is, the smaller is the probability that in a
protein (a random sequence), not related to the given group, a fragment belonging to the
interval can be found. Thus the smaller Qj is, the
greater is its ability to differentiate fragments of proteins of the trial sample from
fragments of other proteins, i.e. its specificity.
Some positions may be marked as ‘passive’ or ‘non-meaningful’ (in comparison
with patterns of PROSITE). They do not influence the definition of value Qj,
and comparison of these positions is not implemented in pattern analysis (any amino acids
are acceptable). In our case all positions that had more than 5 amino acids and/or the
total frequency of amino acid occurrence more than 0.2, were regarded as passive. Having
analyzed the structure of the bank PROSITE, we found out that about 80% of the bank’s
patterns fall into the following boundaries: up to 10 ‘active’ positions and a total
length of no more than 20 positions. We also used these limits when choosing pattern
motifs.
Having set some critical value of the Q’, for a series of chosen proteins one
can get a set of motifs R(Q’, l1, l2),
the borders of which are limited to l1, l2.
Characteristics of motif j are the value Qj that
determines its specificity, and length n.
To ensure an effective realization of comparison algorithm between sequences and
patterns, we demand that every motif should contain an ungapped section of no less than 4
active positions.
The motifs of patterns are represented by ambiguous words of the type: K-[D,E] - F - [I,V] - C - X - [A, S, T] - X - [M, N, D]... Thus, an
initial pattern of a protein family is an ordered combination of non-overlapping motifs of
the type r:A1-A2-A3-...-An.
Here r is position number of an aligned group of proteins (the trial sample), where
the motif begins, Ai is a set of amino acids, located in r+i-1
position of the trial sample. For a passive position Ai=X:
any amino acid is acceptable. The number of motifs doesn't exceed 5 per 100 positions.
Each pattern is compared with all sequences of the initial file. If not less than 60
per cent of motifs of a pattern reveale similarity with a sequence that is not included in
other families, an attempt to include this sequence into the trial sample is made. If any
motif is non-specific (i.e. it matches many sequences, but other motifs of the pattern do
not match them) the motif is excluded from the pattern.
COMPARISON OF AMINO ACID SEQUENCES WITH PATTERNS
The searches for exact matching between amino acid sequences’ fragments and
pattern motifs. The main algorithm for comparing an amino acid sequence with the
pattern database uses the modification of finite automaton of Aho-Corasic (Aho and
Corasic, 1975), constructed based on a set of samples, which are to be searched for in the
input text. The automaton is presented as an oriented tree-like graph, where nodes are
states of the automaton and arcs are admissible transitions from some states to the
others, marked with symbols from the alphabet S of the amino acids’ designation.
The automaton works in cycles. In every cycle one more symbol of a text is read, which
determines the automaton’s transition from the current state into a new one. The
automaton’s behavior is characterized by three functions: function of transitions G(s,a);
rejections’ function F(s) and output function O(s). The values of these
functions are calculated once when constructing the automaton based on a given set of
samples. In Figure 1. The functions of the automaton constructed on
the set of samples R={r1, r2,
r3, r4, r5}
= {HE, SHE, HIS, HER, HERS} are illustrated.
Fig. 1. Illustrations of the
functions of the Aho-Corasic automaton constructed on the set of samples R={r1,
r2, r3, r4,
r5} = {HE, SHE, HIS, HER, HERS}: a) graph representation of
transition function G(s,a); b) rejections’ function F(s); c) output
function O(s); d) automaton’s transition from state to state if the input text is
"ushers"
The function of transitions s'=G(s,a) determines into what state s’ the
automaton passes from a current state s, if the input symbol is 'a'. When
there is no admissible transition, a situation called ‘rejection’ arises which
indicates that the comparison has failed.
The values of the rejections’ function F(s) are calculated in the situations,
when G(s,a) = ‘rejection’. In this case there does not occur a backward move
through the text to the beginning of another fragment of the sequence (exit to the initial
state of the automaton). A new sample is being examined from the break site of the
previous one. It provides linear dependence of the search time on the length of the query
sequence. F(s) indicates into what state the automaton passes from a current state s,
if the next symbol of the text does not coincide with a label of any of the arcs, which go
out from s. The transitions ‘upon rejections’ are the ones that guarantee the
returnless manner of text scanning.
The output function O(s) indicates the list of motifs, represented by a sample
(as a sequence of arc labels on the way from initial state "0" into
"s"), a successful search for which is realized as the automaton passes
into state s.
When constructing the automaton in every motif, 4 neighbouring positions are chosen
(the core of a motif), having minimum value of the product P1
and containing no passive positions. Then this core is converted into exactly determined
words of length 4 that act as samples in constructing automaton. If coincidence of a
current fragment of an input sequence and one of the automaton samples is observed,
comparison is performed (up to the first non coincidence) of all the other motif positions
from the list of the output function, and the corresponding fragments of the sequence (the
stage of extending the core). According to the results of this stage, the final decision
is made on whether there is similarity or not.
The search for distant similarity. To reveal a distant similarity, the algorithm
of comparison is modified. The user specifies the matrix of similarity of amino acid
residues (e.g., using the one from families PAM (Dayhoff, 1978), BLOSUM, etc.) and D
- the level of similarity within the limits of motif. For all states of the automaton, the
function of rejection is set to zero. Besides, a sequence as a whole does not input to the
automaton, but specially processed words. Preparing words, additional to the initial
fragment and the search process are as follows:
A. For every fragment of the input sequence of length 4 the value S04
is calculated - the sum of values of diagonal elements of the matrix of similarity for
amino acids of the fragment. Then the value S0 = S04
+ 6*Sm is calculated, where 
is average value of diagonal elements sii
of the scoring matrix, pl is the frequency of occurrence
in proteins of amino acid i. The coefficient 6 is chosen because of the length 10
is the most usual for motifs.
B. Supplementary ‘similar’ words are constructed. For each possible word of
length 4, the sum of elements of the similarity matrix 
is calculated. Here k and l are indices of amino acids of the
initial fragment and the supplementary word in corresponding positions i, 
is an element of the similarity matrix. If S
does not differ from the sum of diagonal elements for the corresponding amino acids of the
fragment by a value greater than (100-D)*So/100, where
D(%) is the point of similarity, specified by the user, the word is accepted.
C. All these words are passed to the entry of the automaton consecutively. In
the case of coincidence with the sample, the following values are calculated: 
- the sum of diagonal values of the similarity
matrix for amino acids of the fragment, corresponding to active positions of the motif,
and 
- similarity of the motif to the
fragment. Here k is index of amino acid, located in the first position of the
fragment, max(
) is the maximum value
of similarity for amino acid k of the fragment and amino acids l, located in
position i of the motif. If S1> 
*D/100, then the decision is made about
the existence of the prescribed degree of similarity.
The comparison of patterns with the parent banks. To examine the recognizing
ability of the patterns and exclude certain motifs, which are non-specific for a given
family, all patterns were compared with all the proteins of the SWISS-PROT+TrEMBL. In the
routine comparison between patterns and the banks, only exact similarities of two or more
motifs per a pattern were registered, i.e. the cases when fragments of amino acid
sequences belong to the motifs. The comparisons made the inclusion of hundreds of
sequences into trial samples possible.
The similarity is regarded as ‘positive’ one, if at least one of the two following
conditions is met. 1. Query sequence belongs to the trial sample. 2. All
words of one of the DE fields of the pattern (the names of the proteins forming the
family) are present in the field DE (protein name) of the sequence. The last condition
needs some clarification. Proteins are considered to be related to the trial sample
proteins, if they have the same name that the trial sample has, possibly supplemented with
words HYPOTHETICAL, PROBABLE, POSSIBLE, PRECURSOR, CHAIN, etc., descriptions of
localization of sequences (MITOCHONDRION, CHLOROPLAST, PLASMID), its composition in the
case of polyproteins, a note concerning the type of the chain, etc.
The similarity is considered ‘conditionally positive’ (UNKNOWN), if at least one of
the DE or KW words of the pattern coincides with one of the words determined in fields DE
and/or KW of the sequence. Thus, proteins are defined as conditionally related if they
possess some common function (e.g., hydrolases, dehydrogenases, oxidoreductases, etc.) or
some specific features of their structure (for instance, transmembrane segments). All
other cases of similarity are regarded as false positive. As a result of comparison with
the bank, a pattern bank entry is created, similar in its structure to entries of PROSITE.
The example of such entry is given in Figure 2. Descriptions of
the fields are given in Table 1.
ID 00004;
DT Thu Aug 5 14:35:08 1999
DE 4-HYDROXYPHENYLPYRUVATE DIOXYGENASE (EC 1.13.11.27) (4HPPD)
KW OXIDOREDUCTASE; DIOXYGENASE; IRON; ACETYLATION.
PR P32754, P49429, Q02110, Q22633, Q27203, Q00415,
PR O42764, Q53586;
RE SWISS-PROTEIN(rl.37)+TREMBL(rl.8)
AC 00004_1 (47-56)
PA [FW]-[AVWY]-V-G-N-A-K-Q-[AV]-A
FR frequency = 4.02065e-12
DR P32754, T; P49429, T; Q02110, T; Q22633, T; Q27203, T;
DR Q00415, T; O42764, T; Q53586, T;
NR /TOTAL=8(8); /POSITIVE=8(8); /UNKNOWN=0(0); /FALSE_POS=0(0);
NR /FALSE_NEG=0;
*/
...
AC 00004_12 (391-400)
PA D-R-P-T-[LV]-F-[FILY]-E-[IV]-I
FR frequency = 4.6197e-12
DR P32754, T; P49429, T; Q02110, T; Q22633, T; Q27203, T;
DR O23920, T; Q00415, T; O42764, T; Q53586, T; Q18347, ?;
NR /TOTAL=10(10); /POSITIVE=9(9); /UNKNOWN=1(1); /FALSE_POS=0(0);
NR /FALSE_NEG=0;
*/
//
Fig. 2. An example of the pattern bank entry.
Table 1.
Descriptions of fields of PROF_PAT 1.3. entries
Identificator of a field |
Value of the field |
ID |
Unique identificator of a pattern (entry) |
DT |
Date of creation/edition |
DE |
Description of the pattern, usually - descriptions (DE) of
sequences of the trial sample |
KW |
Key words |
PR |
The set of ACs of sequences of the trial sample |
RE |
Release of parent bank |
AC |
Identificator and margins of the pattern's motif |
PA |
Pattern's motif |
FR |
Occurrence frequency of matching of the motif to random
fragment of amino acid sequence |
DR |
The set of ACs of amino acid sequences of parent bank that
match the motif: Ò - true, ? - unknown, F - false positive |
NR |
The statistics of matches of the motif to amino acid
sequences of the parent bank: Õ(Ó), where Õ - the total No of matches, Ó - the No of
sequences where matches have been revealed |
*/ |
The end of the motif |
// |
The end of the pattern |
DISCUSSION
In the first version of PROF_PAT, patterns were selected in accordance with the
principle of small variability of several physicochemical properties of amino acids
(Bachinsky, et al., 1997). However, the use of this bank in actual practice revealed its
shortcomings. Its large size and the time-consuming procedure of comparison compelled us
to modify to a certain extent its construction principles.
In recent versions the total number of motifs in more than 10,000 patterns is over
200,000 with specificities varying from one expected false positive prediction in 108
tests and higher. The total combined length of motifs is over 2,000,000 positions.
To find a distant similarity, a very fast flexible comparison procedure is employed,
using the modified algorithm of Aho-Corasic (Aho and Corasic, 1975), various matrices of
similarity/distance for amino acid residues, the predetermined grade of similarity between
a fragment of an amino acid sequence and a pattern motif.
Almost all sequences of the trial samples are recognized by all motifs of the
corresponding patterns. Certain violations of this rule are due only to the presence of
non-standard symbols in the particular sequences of the trial samples that have fallen
into the intervals of positions represented by pattern motifs.
A number of cases of false-positive similarity may be divided into two classes.
Sometimes it is a really chance similarity. However, sometimes two or more pattern motifs
show similarity to the fragments of a certain sequence; the order of the fragments’
locations often correspond to that of the motifs’ locations, which increases even more
the certainty that the similarity is not random. In most cases, false-positive similarity
is revealed with sequences described only as products of some genes, and this information
is not included into descriptions of patterns (see some examples in Table
2.).
Table 2.
Some cases of false-positive similarity have been
revealed, when patterns of PROF_PAT 1.1. bank were searched for SWISS-PROT+TrEMBL bank
Descriptions of protein
families (patterns) |
Entry names of related
sequences |
No. of similar motifs/
No. of motifs in the pattern |
Descriptions of sequences |
Comments |
| SERINE THREONINE KINASE |
Q26345 |
5/15 |
FU (FUM1)=SEGMENT POLARITY
GENE FUSED {28-BP DELETION}. |
The sequence matches motifs
of the N-end of the pattern |
| FLORAL HOMEOTIC PROTEIN AGL AGAMOUS PROTEIN
MADS BOX PROTEIN
DAL2 PROTEIN |
Q41876 |
5/9 |
ZAG1. |
|
| COLLAGEN |
Q20927 |
4/7 |
F57B7.3. |
|
| RNA-DIRECTED RNA POLYMERASE (EC 2.7.7.48) READTHROUGH PROTEIN REPLICASE
REPLICATION-ASSOCIATED PROTEIN |
Q84126
Q88598 |
20/66
20/66 |
52KDA UNKNOWN IN FUNCTION
PROTEIN
54 KDA PROTEIN |
The sequences match motifs
of the C-end of the pattern |
| ZINC-FINGER PROTEIN |
Q60980 |
6/19 |
BKLF. |
|
| PHOSPHOLIPASE |
Q63693 |
29/30 |
PHODPHOLIPASE C
DELTA4. |
An error in protein DE |
| ATP SYNTHASE A CHAIN (EC 3.6.1.34) (PROTEIN 6) ATPASE
ATP SYNTHASE SUBUNIT 6 |
Q35294 |
4/12 |
URF-RMC |
The sequence matches motifs
of the N-end of the pattern |
| PROTEIN B15 |
VC16_VACCC |
4/8 |
PROTEIN C16/B22. |
|
| CANAVALIN BETA-CONGLYCININ |
Q39816 |
11/23 |
7S STORAGE PROTEIN ALPHA
SUBUNIT. |
The sequence matches motifs
of the C-end of the pattern |
| TRANSPOSASE MARINER
PROTEIN |
YKC6_CAEEL |
5/10 |
HYPOTHETICAL 29.3 KD PROTEIN
B0280.6 IN CHROMOSOME III. |
The sequence matches motifs
of the C-end of the pattern |
| MASC PROTEIN |
Q50586 |
4/15 |
HYPOTHETICAL 63.1 KD
PROTEIN. |
|
| MUCIN |
Q22902 |
9/11 |
COSMID C16D9. |
The sequence matches motifs
of the N-end of the pattern |
| NUCLEOLAR PROTEIN NUCLEOPHOSMIN-RETINOIC
ACID RECEPTOR
ALPHA FUSION PROTEIN |
Q14115 |
7/14 |
P80 PROTEIN. |
The sequence matches motifs
of the N-end of the pattern |
| PROTEIN KINASE |
Q24096
Q24590 |
4/18
4/18 |
LATS.
TUMOR SUPPRESSOR. |
|
| RNA-DIRECTED RNA POLYMERASE (EC 2.7.7.48) REPLICASE |
Q65014
Q83423
Q83426 |
8/29
5/29
5/29 |
PROTEIN OF 33 KDA.
PROTEIN 29.
29K PROTEIN. |
The sequences match motifs
of the N-end of the pattern |
| SPLICING FACTOR RNA
BINDING PROTEIN 1 |
Q62093 |
4/5 |
PR264/SC35. |
The sequence matches motifs
of the N-end of the pattern |
| SUPPRESSOR OF FORKED PROTEIN CLEAVAGE STIMULATION FACTOR |
Q24539 |
13/34 |
39 KD PROTEIN. |
The sequence matches motifs
of the N-end of the pattern |
| TRANSCRIPTION FACTOR |
Q18694 |
3/9 |
C47G2.2. |
|
| TRANSPOSASE TNIA |
Q47380 |
9/26 |
INVASIN |
The sequence doesn't match
the INVASIN pattern. The membership to this class of proteins is doubtful |
| TRANSALDOLASE (EC 2.2.1.2) |
Q49705
Q49698 |
6/18
6/18 |
B1496_F2_65.
B1496_F1_27. |
The sequences match motifs
of the N-end (Q49705) and C-end (Q49698) of the pattern |
| TRANSPOSASE |
ADPR_LACLA |
5/12 |
ATP-DEPENDENT PROTEASE (EC
3.4.21.-). |
The sequence doesn't match
the patterns of ATP-dependent proteases |
| PROBABLE TRANSPOSASE FOR INSERTION SEQUENCE
ELEMENT IS701 |
Q55975
Q55976 |
5/11
5/11 |
HYPOTHETICAL 16.4 KD PROTEIN
HYPOTHETICAL 13.5 KD PROTEIN. |
The sequences match motifs
of the N-end (Q55975) and C-end Q55976) of the pattern |
| RECEPTOR-LIKE TYROSINE-PROTEIN KINASE (EC 2.7.1.112) |
Q23677 |
12/15 |
ZK938.5. |
The sequence matches motifs
of the C-end of the pattern |
| CAPSID PROTEIN |
COA3_AAV2 |
13/32 |
PROBABLE COAT PROTEIN 3. |
|
| PROTEIN VP2 |
Q84387 |
4/23 |
HYPOTHETICAL 7.9 KD PROTEIN. |
It is a C-fragment of VP2
protein |
| ANAEROBIC RIBONUCLEOSIDE-TRIPHOSPHATE REDUCTASE (EC 1.17.4.2) |
Q38428 |
19/28 |
ORF 55.11). |
The virus genome contains a
C-fragment of bacterial protein |
| DIHYDROPYRIMIDINASE |
Q21773 |
8/20 |
R06C7.3 |
|
| REVERSE TRANSCRIPTASE |
Q63305 |
15/57 |
LONG INTERSPERSED REPETITIVE
DNA CONTAINING 7 ORF'S. |
It is a C-fragment of
transcriptase |
| DEHYDROGENASE DIOXYGENASE |
Q52459 |
9/9 |
THE FIRST START CODON IN THE
ORF IS FOUND AT POSITION 2466. |
Besides of the sequence
matches all motifs of the pattern, it hasn't 30%similarity with all proteins of the trial
sample |
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