Commentary

MalVac: Database of malarial vaccine candidates

Rupanjali Chaudhuri^* , Shakil Ahmed^* , Faraz Alam Ansari^* , Harinder Vir Singh and Srinivasan Ramachandran

G.N Ramachandran Knowledge Centre for Genome Informatics, Institute of Genomics and Integrative Biology (Council of Scientific and Industrial Research), Mall Road, Delhi 110007, India

author email corresponding author email* Contributed equally

Malaria Journal 2008, 7:184doi:10.1186/1475-2875-7-184

Published:	23 September 2008

Abstract

Background

The sequencing of genomes of the Plasmodium species causing malaria, offers immense opportunities to aid in the development of new therapeutics and vaccine candidates through Bioinformatics tools and resources.

Methods

The starting point of MalVac database is the collection of known vaccine candidates and a set of predicted vaccine candidates identified from the whole proteome sequences of Plasmodium species provided by PlasmoDb 5.4 release (31st October 2007). These predicted vaccine candidates are the adhesins and adhesin-like proteins from Plasmodium species, Plasmodium falciparum, Plasmodium vivax and Plasmodium yoelii. Subsequently, these protein sequences were analysed through 20 publicly available algorithms to obtain Orthologs, Paralogs, BetaWraps, TargetP, TMHMM, SignalP, CDDSearch, BLAST with Human Ref. Proteins, T-cell epitopes, B-cell epitopes, Discotopes, and allergen predictions. All of this information was collected and organized with the ORFids of the protein sequences as primary keys. This information is relevant from the view point of Reverse Vaccinology in facilitating decision making on the most probable choice for vaccine strategy.

Results

Detailed information on the patterning of the epitopes and other motifs of importance from the viewpoint of reverse vaccinology has been obtained on the most probable protein candidates for vaccine investigation from three major malarial species. Analysis data are available on 161 adhesin proteins from P. falciparum, 137 adhesin proteins from P. vivax and 34 adhesin proteins from P. yoelii. The results are displayed in convenient tabular format and a facility to export the entire data has been provided. The MalVac database is a "community resource". Users are encouraged to export data and further contribute by value addition. Value added data may be sent back to the community either through MalVac or PlasmoDB.

Conclusion

A web server MalVac for facilitation of the identification of probable vaccine candidates has been developed and can be freely accessed.