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Bioinformatics Advance Access published online on September 16, 2004
Bioinformatics, doi:10.1093/bioinformatics/bti028
Bioinformatics © Oxford University Press 2004; all rights reserved
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Received February 24, 2004
Revised August 20, 2004
Accepted August 31, 2004

Article

SPAAN: A software for prediction of adhesins and adhesin-like proteins using neural networks

Gaurav Sachdeva 1, Kaushal Kumar 1, Preti Jain 1, and Srinivasan Ramachandran 1*

1 G.N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, Mall Road, Delhi - 110 007, India

* To whom correspondence should be addressed. E-mail: ramu{at}igib.res.in; ramucbt@yahoo.com.


  Abstract

Motivation: The adhesion of microbial pathogens to host cells is mediated by adhesins. Experimental methods used for characterizing adhesins are time consuming and demand large resources. The availability of specialized software can rapidly aid experimenters in simplifying this problem. We have employed 105 compositional properties and ANN to develop SPAAN, which predicts the probability of a protein being an adhesin (Pad).

Results: SPAAN had optimal sensitivity of 89% and specificity of 100% on a defined test set and could identify 97.4% of known adhesins at high Pad value from a wide range of bacteria. Further, SPAAN guided in improved annotation of several proteins as adhesins. Novel adhesins were identified in 17 pathogenic organisms causing diseases in humans and plants. In the Severe Acute Respiratory Syndrome (SARS) associated human corona virus, the spike glycoprotein and nsp's (nsp1, nsp5, nsp6 and nsp7) were identified with adhesin-like characteristics. These results offer new leads for rapid experimental testing.

Availability: SPAAN is freely available through ftp from either 203.195.151.45 or 203.90.127.75. Retrieve SPAAN.tar.gz.


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