Availability of gene and protein sequences of parasite has provided a remarkable amount of data that can be useful in drug target identification and vaccine development. Although extensive researches are on way in order to control the disease caused by eukaryotic parasites and to develop drug(s) against them, till date no effective vaccine or specific drug is available. Subtractive genomics approach is one of the recently adopted methodology in which the subtraction of sequence between the host and parasite proteome provides information for a set of proteins that are likely to be essential to the parasite but absent in the host. We have used the same methodology to analyse the proteome of the human parasite Leishmania donovani.Our analysis showed that out of the 446 protein sequences of the parasite, 29 represent unique to parasite and predicted as putative drug targets. 16 membrane, 5 nuclear, 3 cytoplasmic along with 2 mitochondrial are found to be the potential drug targets by using subtractive genomics approach. The preliminary work presented here identifies a small subset of the L. donovani proteome that might be investigated further for identifying potential drug and vaccine candidate in this parasite.

Pseudomonas syringae is a plant pathogen which infects a wide range of plant species, and is also the causative organism of bacterial brown spot of bean. The complete genome sequence of pathogen has provided all the determinants of host-pathogen interactions and possible drug targets, computational methods for selecting suitable candidates for further experimental analyses are currently limited. We have performed comparative analysis of genomes and metabolic pathways of the pathogen P. syringae and the host phaseolus vulgaris (kidney bean) and identified eight potent therapeutic targets. After critical evaluations of the targets we have considered murD and murE as the potent targets for virtual screening of lead molecules. Virtual screening was carried out using the high throughput virtual screening protocol and PubChem drug database. The interaction studies provided promising ligands for future experimental screening to inhibit the proliferation of Pseudomonas syringae. KEY WORDS Pseudomonas, database of Essential Genes (DEG), comparative microbial genomics, comparative metabolomics, homology, drug targets, virtual screening.

For most proteins in the genome databases, function is predicted via sequence comparison. In spite of the popularity of this approach, the extent to which it can be reliably applied is unknown. We address this issue by systematically investigating the relationship between protein function and structure. We focus initially on enzymes classi®ed by the Enzyme Commission (EC) and relate these to structurally classi®ed proteins in the SCOP database. We ®nd that the major SCOP fold classes have different propensities to carry out certain broad categories of functions. For instance, alpha/beta folds are disproportionately associated with enzymes, especially transferases and hydrolases, and all-alpha and small folds with non-enzymes, while alpha ‡ beta folds have an equal tendency either way. These observations for the database overall are largely true for speci®c genomes. We focus, in particular, on yeast, analyzing it with many classi®cations in addition to SCOP and EC (i.e. COGs, CATH, MIPS), and ®nd clear tendencies for fold-function association,