Trends in Biochemical Sciences
Computer CornerNPS@: Network Protein Sequence Analysis
Section snippets
Single-sequence analysis
A typical example of a sequence similarity search is illustrated in Fig. 2. This search can be performed on several protein sequence databases (SWISS-PROT, SP-TrEMBL, TrEMBL, PIR, GenPept, NRL_3D) by using parallel versions of BLAST, PSI-BLAST (Ref. 2), SSEARCH and FASTA (Ref. 3). A common HTML interface (Fig. 2a) has been developed to display the similarity search results graphically. Such an interface is useful to analyse successive runs of PSI-BLAST quickly. In the results page, three links
Personal databank
The second input point available is a personal databank that can be uploaded in NPS@ server from a local computer. On this databank, the user can apply all the various analyses described above and shown in Fig. 2d.
User-defined pattern
The third input point is user-defined patterns that are used in the PattInProt program that we have developed. This program scans a protein sequence or a databank for the presence of sites and signatures. The search can be performed with one or several mismatches or after setting a similarity level in order to detect more degenerate sequences. A recursive procedure allows for the successive searches of different patterns. This feature is particularly useful to generate and filter protein
Concluding remarks
A strong point and unique feature of this server is the coupling of secondary structure predictions with multiple alignments, performed on a sequence subset extracted following a similarity search (BLAST, PSI-BLAST, SSEARCH, FASTA or PattInProt). Indeed, all methods are interconnected in such a way that the output of a given analysis can be used as the starting point for another analysis. Efforts have been made to describe analytical methods and how to use the server through online help (//pbil.ibcp.fr/help/help_npsaindex.html
Acknowledgements
The authors like to acknowledge financial support from CNRS, MENESR and Région Rhône-Alpes and thank all computing teams that have developed biocomputing methods for protein sequence analysis. C. Combet is the recipient of an ANRS doctoral fellowship. Thanks are due to D. Mandelman for textual improvements.
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