CS # 594-Group 13 ( Tools and softwares )

The protein and DNA sequence library are growing very rapidly, almost 50% per year. The major problem faced by the biologists , is the need to compare one sequence against all the sequences in the database in a reasonable time. A newly discovered sequence is compared to the known sequences in the database. Often this search provides the first insight into the mechanism of action of a new sequence. Many softwares and tools have been developed for this purpose. Each having its own trade off in terms of selectivity, sensitivity and speed. We here in this paper present few of them ( FASTA, BLAST, Gapped BLAST, PSI-BLAST, Pip Maker, MACAW, Motif Explore r and the five tools for finding conserved sequences in multiple alignment) 1.0 Introduction: The DNA and Protein sequences are the blueprint for an organism’s structure and function. All the information about the living world is encoded as different sequences in these units. Analyzing them gives us lots of information regarding the various biological aspects of life and their evolution. The protein and DNA sequence library are growing very rapidly, almost 50% per year, owing to the more efficient cloning techniques and more productive sequence procedures. Some of the major DNA & protein databases are the EMBL, GenBank, DDBJ, Prosite. The importance of the database is to provide current view of know sequences quickly and to learn new biology. A newly discovered sequence is compared to the known sequences in the database. Often the matched sequences obtained from a database search provide the first insight into the mechanism of action of a new sequence. Now equipped with this vast amount of data in the form of sequences, the foremost problem on hands of the biologists is the need to compare one sequence against all the sequences in the database in a reasonable time. This problem can be dated back to 1980’s, but then the database ware small. The Dynamic Programming methods for comparing two sequences, more precisely, the alignment of two sequences (global or local) allows to obtain an optimal alignment in time proportional to the product of the lengths of the two sequences, i.e. when applied to the entire database the computational time would grow linearly to the size of the database. At present time, the size of a database is much greater and the approach of Dynamic Programming will be impractical for searching large databases unless we use supercomputer or some parallel processors [2]. This was the motivation behind developing new algorithms and software tools. A brief overview of some of the algorithms and tools used are given in the following paragraphs. David Lipman and William R. Pearson in 1985 described the FASTP program for searching protein sequence libraries. FASTP combines a rapid technique for focusing on those regions in a pair of sequence that share a high density of identities with a scoring procedure that uses the PAM250 scoring matrix for high sensitivity. It decreased the typical search time from 6hours to 10 min. The FASTA , is a resent improved version of FASTP. It combines the function of the FASTP and FASTN (modified version of FASTP for DNA sequence). It along with calculating this initial score also checks to see if several initial regions can be joined together in a single alignment to increase the initial score, thus improving sensitivity. In addition, the FASTA package includes programs fro comparing a protein sequence to a DNA sequence database (TFASTA), for identifying local sequence similarities or duplications in sequences (LFASTA, PLFASTA), and for evaluating the statistical significance of a similarity score (RDF2). The BLAST software or program is a set of comparison algorithms i ntroduced in 1990 by S.F. Altschul that employs a measure based on mutation scores [2]. The results are directly approximated as opposed to dynamic programming. These are used to search sequence databases for optimal local alignments for a given query sequence. The main strategy of BLAST is to quickly seek or locate un-gapped similar regions between the query sequence and sequences from the database. Given a cutoff score S as parameter, The BLAST first generates all the words of length w formed with the alphabet of the sequences and then each word of the query is compared with each word of this set and a similarity threshold T is recorded. It then selects only those words that contain a word pair with a score of at least T, thus generating a list of words of length w whose score is more than T. The next step is to compare every word of the list with score atleast equal to T, with each word in the database. All exact matches with DB sequences detected are called hits. Every hit is then extended in both directions to determine whether this hit is part of a larger segment of similarity i.e. if it is contained within a segment pair whose score is greater than or equal to S. Every such hit is retained and called an HSP (high scoring segment pair) and the best scoring HSP is the MSP (maximal segment pair) is reported. In Gapped BLAST, as the name says, gapped alignments have been introduced to find alignments in a sequence that are with in some limited value instead of finding several un gapped alignments from the sequence. This essentially increases the initial database scan, but we need to locate only one of the essential HSPs in order obtain a success. The second refinement is the “two – hit” method, were extensions are made only if there are two non overlapping word pairs within some distance A. The advantage of this is that the program executes three times faster because only a few hits are extended [4]. Another version of BLAST is the PSI-BLAST for position specific iterated BLAST, which involves a series of repeated steps. First, a database search of a protein sequence database is performed. The results of the search are visually inspected to see if any sequence from the database is related to the query sequence. If so then the search is repeated again. The scoring sequence matches found from the first iteration are aligned. From this alignment a sequence motif (short amino acid sequence), which indicates the differences at each position of the alignment is produced. The database is searched again with this motif, thus expanding the search to include sequences that match the variations found in the motif at each sequence position. The results, which are obtained, indicate that new sequences are found which are more significantly related to the motif than the previously found sequences. Pipmaker is a WWW site for comparing two long DNA sequences to identify conserved segments and for producing informative, high-resolution displays of the resulting alignments. One display is a percent identity plot (pip), which shows both the position in one sequence and the degree of similarity for each aligning segment between the two sequences in a compact and easily understandable form. Positions along the horizontal axis can be labeled with features such as exons of genes and repetitive elements, and colors can be used to clarify and enhance the display. Another display is a plot of locations of those segments in both species (similar to a dot-plot). PipMaker is appropriate for comparing genomic sequences from any two related species, although the types of information that can be inferred depend on the level of conservation and the time and divergence rate since the separation of the species. PipMaker is capable of returning the alignments generated by BlastZ in any or all of four different formats: a pip, a dot plot, a conventional textual alignment, and a compact listing of the coordinates of the aligning segments. Multiple Alignment Construction & Analysis Workbench (MACAW) is an interactive program that allows you to to construct multiple alignments by locating, analyzing, editing, and combining “blocks” of aligned sequence segments. MACAW incorporates several novel features. (1) Regions of local similarity are located by a new search algorithm that avoids many of the limitations of previous techniques. (2) The statistical significance of blocks of similarity is evaluated using a recently developed mathematical theory. (3) Candidate blocks may be evaluated for potential inclusion in a multiple alignment using a variety of visualization tools. (4) A user interface permits each block to be edited by moving its boundaries or by eliminating particular segments, and blocks may be linked to form a composite multiple alignment. Motif explorer is a software tool, which uses indexing structure based on generalized suffix trees for high performance motif searches, and makes the interactive motif exploration possible. It’s fast enough to provide answers within seconds. It combines the implementation of large-scale GST structures with the GST regular expression search algorithm. The GST is created and processed as linear steams of data, using limited main memory and without random access to the entire structure. The motif explorer uses the GST regular expression search performance predictor to improve the performance of the search. It has a World Wide Web (WWW) based interface and presents the results as HTML docs. It also gives the WWW links to other appropriate database containing information of the matching sequences. The motif Explorer, in its average and median search timings, is less by approximately an order of 20 when compared to the grep program. Another important problem for molecular biologists and computer scientists is distinguishing functional regions from those whose similarity reflects the residual common ancestral sequence that has not yet changed via evolutionary drift. Here will be presenting five of them. Two of five methods described in this part are aimed at finding protein-binding sites on DNA. Such sites are usually a series of consecutive positions, one or more of which can vary somewhat without measurably changing the binding affinity. Thus it is desira