Jerrine Joseph

Mycobacteriophage Genome Database

Mycobacteriophage genome database (MGDB) is an exclusive repository of the 64 completely sequenced mycobacteriophages with annotated information. It is a comprehensive compilation of the various gene parameters captured from several databases pooled together to empower mycobacteriophage researchers. The MGDB (Version No.1.0) comprises of 6086 genes from 64 mycobacteriophages classified into 72 families based on ACLAME database. Manual curation was aided by information available from public databases which was enriched further by analysis. Its web interface allows browsing as well as querying the classification. The main objective is to collect and organize the complexity inherent to mycobacteriophage protein classification in a rational way. The other objective is to browse the existing and new genomes and describe their functional annotation. Availability The database is available for free at http://mpgdb.ibioinformatics.org/mpgdb.php

Molecular Docking of Phytoligands to the viral protein receptor P. monodon Rab7

The development of shrimp aquaculture has been severely affected by viral diseases resulting in a huge economic burden to the industry. White spot disease (WSD) has caused severe mortality in farmed shrimp in many countries. Globally aquaculture industries face huge economic losses due to rapid spread of White Spot Syndrome Virus (WSSV) disease that can cause 100% mortality in a short period of 3-10 days. In the present study in order to prevent the spread of WSSV disease in shrimps, the receptor, PmRab7 has been chosen as the drug target. Due to the absence of a precise 3D structure of the target, homology-modeling approach was employed to obtain the structure that was validated later. This structure was then used as a template to screen selective phytomolecules as potential antiviral agents and their docking results with the target are analyzed based on their energy scores. Identification of the drug-like molecule obtained from the docking analysis would be used to optimize to a candidate drug. This is expected to play a role of the inhibitor that blocks the binding of the viral protein to the receptor, duly preventing the WSSV disease.

Druggability and Binding Site Interaction Studies of Potential Metabolites Isolated from Marine Sponge Aurora globostellata against Human Epidermal Growth Factor Receptor-2

To study the involvement of compounds stigmasterol and oleic acid isolated from marine sponge Aurora globostellata and docking against the Human Epidermal Growth Factor Receptor-2 in breast cancer. The comparative molecular docking was performed with the natural compounds from marine sponge and the synthetic drugs used in breast cancer treatment against the target HER2. The molecular docking analysis was done using GLIDE in Schrodinger software package. The ADME properties were calculated using the Qikprop. The observation of the common binding site for all the ligands confirms the binding pocket; where the isolated compound Stigmasterol agrees well with the binding residues and thus can be optimized further to arrive at a molecule that has a high binding affinity and low binding constant. The results of the docking studies carried out on HER2 provide an insight for the compound stigmasterol to have drug like properties than oleic acid. These results are supportive to confirm the marine sponges as a better lead for cancer therapeutics.

Functional assignment of the 64 mycobacteriophages into gene families

Abstract Objective To functionally annotate the protein sequences for 64 mycobacteriophage genomes using the ACLAME database and to discuss how structured information on mycobacteriophage encoded proteins helps global in silico analysis. Methods Each of the protein sequences of 64 mycobacteriophage genomes were searched against ACLAME database Version 0.4 using BLAST and were further classified based on function. The default setting of ACLAME 0.4 BLAST was used. Results Based on ACLAME, assignment of 72 protein functional families was done for the 64 sequenced genomes, and families were compared among and across genomes. Conclusions The finding of the present study provides scope for designing novel approaches to decipher this huge chunk of unknown proteins by experimental methods.

In silico sequence and structure analysis for mycobacteriophages

Abstract Objective To do a comparative homology search for the 32 mycobacteriophages. Methods This can be estimated as 3 400 proteins from 32 mycobacteriophages assuming each phage has 80-100 genes. The algorithm most widely used for homology detection in comparative genomics is Basic Local Alignment Search Tool (BLAST). Usually a stringent score cutoff is applied to distinguish putative homologs from possible false positive hits. As a consequence, some BLAST hits are discarded or put into insignificant hits that are in fact homologous. Assigning function to protein sequences is important. Here, we review the status of sequence (BLAST) based and domain based approaches to proteins that can provide functional insights such as database on Protein Families (PFAM). Results The findings showed that 31% of proteins showed similarities with homologous protein with known function. Conclusions In the present study only 31% of mycobacteriophage proteins functions were able to be predicted. Only for 6 proteins, the template structures were available but then they were not directly involved in phage lifecycle. Hence this emphasizes the importance of exploring the structures for mycobacteriophage proteins in order to understand their function and evolutionary significance. Ab initio methods for protein structure prediction can be only alternative for the rest of the proteins but accuracy of prediction is not highly dependable.