Article

Computational prediction of essential genes in an unculturable endosymbiotic bacterium, Wolbachia of Brugia malayi

New England Biolabs, 240 County Road, Ipswich, MA 01938-2723, USA.
BMC Microbiology (Impact Factor: 2.73). 11/2009; 9(1):243. DOI: 10.1186/1471-2180-9-243
Source: PubMed

ABSTRACT

Wolbachia (wBm) is an obligate endosymbiotic bacterium of Brugia malayi, a parasitic filarial nematode of humans and one of the causative agents of lymphatic filariasis. There is a pressing need for new drugs against filarial parasites, such as B. malayi. As wBm is required for B. malayi development and fertility, targeting wBm is a promising approach. However, the lifecycle of neither B. malayi nor wBm can be maintained in vitro. To facilitate selection of potential drug targets we computationally ranked the wBm genome based on confidence that a particular gene is essential for the survival of the bacterium.
wBm protein sequences were aligned using BLAST to the Database of Essential Genes (DEG) version 5.2, a collection of 5,260 experimentally identified essential genes in 15 bacterial strains. A confidence score, the Multiple Hit Score (MHS), was developed to predict each wBm gene's essentiality based on the top alignments to essential genes in each bacterial strain. This method was validated using a jackknife methodology to test the ability to recover known essential genes in a control genome. A second estimation of essentiality, the Gene Conservation Score (GCS), was calculated on the basis of phyletic conservation of genes across Wolbachia's parent order Rickettsiales. Clusters of orthologous genes were predicted within the 27 currently available complete genomes. Druggability of wBm proteins was predicted by alignment to a database of protein targets of known compounds.
Ranking wBm genes by either MHS or GCS predicts and prioritizes potentially essential genes. Comparison of the MHS to GCS produces quadrants representing four types of predictions: those with high confidence of essentiality by both methods (245 genes), those highly conserved across Rickettsiales (299 genes), those similar to distant essential genes (8 genes), and those with low confidence of essentiality (253 genes). These data facilitate selection of wBm genes for entry into drug design pipelines.

Download full-text

Full-text

Available from: Sanjay Kumar
    • "The default parameters for BLASTP were used to line up the potential drug targets from S. Typhimurium LT2 against the list of protein targets of compounds found within the Drug Bank. The selection criteria for filtering BLAST results were as described previously (Holman et al., 2009), that is, alignments with e-values less significant than 1 Â 10 –25 were removed. "
    [Show abstract] [Hide abstract]
    ABSTRACT: A computational, comparative genomics workflow was defined for the identification of novel therapeutic candidates against Salmonella Typhimurium LT2, with the aim that the selected targets should be essential to the pathogen, and have no homology with the human host. Bioinformatics analysis identified 43 proteins as non-host essential, which could serve as potential drug and vaccine targets. Additional prioritization parameters characterized 13 proteins as vaccine candidates while druggability of each of the identified proteins was evaluated by the Drug Bank database prioritized same number proteins suitable for drug targets. As a case study we built a homology model of one of the potential drug targets MurD ligase using MODELLER (9v12) software. The model has been further explored for in silico docking study with the inhibitors having druggability potential from the Drug Bank database. Results from this study could facilitate selective S. Typhimurium LT2 proteins for drug design and vaccine production pipelines. Copyright © 2015. Published by Elsevier Ltd.
    No preview · Article · Jan 2015 · Journal of Theoretical Biology
  • Source
    • "The comparison with DBD resulted in the identification of those FDA approved drugs or drug like compounds for which the experimental evidence of binding with proteins similar to the S. aureus is available. Hence, these steps helped in advancing the identification of potential drug or lead like molecules for future medicinal chemistry based approaches (Holman et al., 2009). Out of 51 prioritized targets, all belonged to the unique metabolic pathways of MRSA including two component system, β lactamase resistance, secondary bile acid biosynthesis, nitrogen metabolism, methane metabolism, peptidoglycan biosynthesis, phosphotransferase system, benzoate degradation, Dalanine metabolism, limonene, bacterial secretion system and pinene degradation. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Multiple Drug Resistant (MDR) bacteria are no more inhibited by the front line antibiotics due to extreme resistance. Methicillin Resistant Staphylococcus aureus (MRSA) is one of the MDR pathogens notorious for its widespread infection around the world. The high resistance acquired by MRSA needs a serious concern and efforts should be carried out for the discovery of better therapeutics. With this aim, we designed a comparison of the metabolic pathways of the pathogen, MRSA strain 252 (MRSA252) with the human host (i.e., Homo sapiens) by using well-established in silico methods. We identified several metabolic pathways unique to MRSA (i.e., absent in the human host). Furthermore, a subtractive genomics analysis approach was applied for retrieval of proteins only from the unique metabolic pathways. Subsequently, proteins of unique MRSA pathways were compared with the host proteins. As a result, we have shortlisted few unique and essential proteins that could act as drug targets against MRSA. We further assessed the druggability potential of the shortlisted targets by comparing them with the DrugBank Database (DBD). The identified drug targets could be useful for an effective drug discovery phase. We also searched the sequences of unique as well as essential enzymes from MRSA in Protein Data Bank (PDB). We shortlisted at least 12 enzymes for which there was no corresponding deposition in PDB, reflecting that their crystal structures are yet to be solved! We selected Glutamate synthase out of those 12 enzymes owing to its participation in significant metabolic pathways of the pathogen e.g., Alanine, Aspartate, Glutamate and Nitrogen metabolism and its evident suitability as drug target among other MDR bacteria e.g., Mycobacteria. Due to the unavailability of any crystal structure of Glutamate synthase in PDB, we generated the 3D structure by homology modeling. The modeled structure was validated by multiple analysis tools. The active site of Glutamate synthase was identified by not only superimposing the template structure (PDB ID: 1E0A) over each other but also by the Parallel-ProBiS algorithm. The identified active site was further validated by cross-docking the co-crystallized ligand (2-oxoglutaric acid; AKG) of PDB ID: 1LLW. It was concluded that the comparative metabolic in silico analysis together with structure-based methods provides an effective approach for the identification of novel antibiotic targets against MRSA. Copyright © 2014 Elsevier B.V. All rights reserved.
    Full-text · Article · Nov 2014 · Gene
    • "The default parameters for BLASTP were used to line up the potential drug targets from S. aureus against the list of protein targets of compounds found within the DrugBank. The selection criteria on BLASTP results is based on previous study (Holman et al., 2009), that is alignments with e-values less significant than 1 × 10 −25 were removed. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Now-a-days increasing emergence of antibiotic-resistant pathogenic microorganisms is one of the biggest challenges for management of disease. In the present study comparative genomics, metabolic pathways analysis and additional parameters were defined for the identification of 94 non-homologous essential proteins in Staphylococcus aureus genome. Further study prioritized 19 proteins as vaccine candidates where as druggability study reports 34 proteins suitable as drug targets. Enzymes from peptidoglycan biosynthesis, folate biosynthesis were identified as candidates for drug development. Furthermore, bacterial secretory proteins and few hypothetical proteins identified in our analysis fulfill the criteria of vaccine candidates. As a case study, we built a homology model of one of the potential drug target, MurA ligase, using MODELLER (9v12) software. The model has been further selected for in silico docking study with inhibitors from the Drug Bank database. Results from this study could facilitate selection of proteins for entry into drug design and vaccine production pipelines.
    No preview · Article · Jun 2014 · Journal of microbiological methods
Show more