Insilico Proteome Screening to Identify Prospective Drug Targets in Bacillus anthracis

Various Insilico based genome screening methods helped us in identifying the key drug targets for  a pathogen. The accuracy of the predictions are systematically based on the benchmarks at different stages of methodology and the kind of dataset which is considered for the study. In the current study, we made an effort to screen the entire proteome of Bacillus anthracis for identification of putative drug targets. B. anthracis is the causautive agent for anthrax disease. Instead of genome sequence, the metabolically classified proteome of B. anthracis from JCVI-CMR database was considered for the present study. The entire proteome is been categorized into 25 different metabolisms and in each sub-categorised metabolisms respective protein sequences were retrieved and subjected to screening against Database of Essential Genes (DEG) and Human-Basic Local Alignment Search Tool (H-BLAST) databases. In total 136 essential genes/proteins were obtained from the DEGp (protein) screening whereas 145 Non-Human Homologs (NHHs) were predicted. The identified 145 NHHs are further subjected to criteria based selection to identify the most suitable, functional, putative drug targets. The 8 common hits of both DEG and H-BLAST were considered to be better potential targets as they justify the criteria of being an essential gene/protein, non-human homolog, availability of the 3D structure in PDB and having a significant functional role in the cellular biochemical processes. 

Pathway Hunter Tool (PHT) � A Platform for Metabolic Network Analysis and Potential Drug Targeting

Metabolic network analysis will play a major role in �Systems Biology� in the future as they represent the backbone of molecular activity within the cell. Recent studies have taken a comparative approach toward interpreting these networks, contrasting networks of different species and molecular types, and under varying conditions. We have developed a robust algorithm to calculate shortest path in the metabolic network using metabolite chemical structure information. A divide and conquer technique using Maximal Common Subgraph (MCS) approach and binary fingerprint was used to map each substrate onto its corresponding product. Then for the calculation of the shortest paths (using modified Breadth First Search algorithm) the two biochemical criteria �local� and �global� structural similarity were used, where �local similarity� is defined as the similarity between two intermediate molecules and �global similarity� is defined as the amount of conserved structure found between the source metabolite and the destination metabolites after a series of reaction steps. The pathway alignment was introduced to find enzyme(s) preference in the pathway of various organisms (a local and global outlook to metabolic networks). This was also used to predict potentially missing enzymes in the pathway. A novel concept called �load points� and �choke points� identifies hot spots in the network. This was used to find important enzymes in the pathogens metabolic network for potential drug targets

Development of anti-infectives using phage display: biological agents against bacteria, viruses, and parasites

The vast majority of anti-infective therapeutics on the market or in development are small molecules; however, there is now a nascent pipeline of biological agents in development. Until recently, phage display technologies were used mainly to produce monoclonal antibodies (MAbs) targeted against cancer or inflammatory disease targets. Patent disputes impeded broad use of these methods and contributed to the dearth of candidates in the clinic during the 1990s. Today, however, phage display is recognized as a powerful tool for selecting novel peptides and antibodies that can bind to a wide range of antigens, ranging from whole cells to proteins and lipid targets. In this review, we highlight research that exploits phage display technology as a means of discovering novel therapeutics against infectious diseases, with a focus on antimicrobial peptides and antibodies in clinical or preclinical development. We discuss the different strategies and methods used to derive, select, and develop anti-infectives from phage display libraries and then highlight case studies of drug candidates in the process of development and commercialization. Advances in screening, manufacturing, and humanization technologies now mean that phage display can make a significant contribution in the fight against clinically important pathogens

Branched-chain amino acid aminotransferase and methionine formation in Mycobacterium tuberculosis

BACKGROUND: Tuberculosis remains a major world-wide health threat which demands the discovery and characterisation of new drug targets in order to develop future antimycobacterials. The regeneration of methionine consumed during polyamine biosynthesis is an important pathway present in many microorganisms. The final step of this pathway, the conversion of ketomethiobutyrate to methionine, can be performed by aspartate, tyrosine, or branched-chain amino acid aminotransferases depending on the particular species examined. RESULTS: The gene encoding for branched-chain amino acid aminotransferase in Mycobacterium tuberculosis H37Rv has been cloned, expressed, and characterised. The enzyme was found to be a member of the aminotransferase IIIa subfamily, and closely related to the corresponding aminotransferase in Bacillus subtilis, but not to that found in B. anthracis or B. cereus. The amino donor preference for the formation of methionine from ketomethiobutyrate was for isoleucine, leucine, valine, glutamate, and phenylalanine. The enzyme catalysed branched-chain amino acid and ketomethiobutyrate transamination with a Km of 1.77 – 7.44 mM and a Vmax of 2.17 – 5.70 μmol/min/mg protein, and transamination of ketoglutarate with a Km of 5.79 – 6.95 mM and a Vmax of 11.82 – 14.35 μmol/min/mg protein. Aminooxy compounds were examined as potential enzyme inhibitors, with O-benzylhydroxylamine, O-t-butylhydroxylamine, carboxymethoxylamine, and O-allylhydroxylamine yielding mixed-type inhibition with Ki values of 8.20 – 21.61 μM. These same compounds were examined as antimycobacterial agents against M. tuberculosis and a lower biohazard M. marinum model system, and were found to completely prevent cell growth. O-Allylhydroxylamine was the most effective growth inhibitor with an MIC of 78 μM against M. marinum and one of 156 μM against M. tuberculosis. CONCLUSION: Methionine formation from ketomethiobutyrate is catalysed by a branched-chain amino acid aminotransferase in M. tuberculosis. This enzyme can be inhibited by selected aminooxy compounds, which also have effectiveness in preventing cell growth in culture. These compounds represent a starting point for the synthesis of branched-chain aminotransferase inhibitors with higher activity and lower toxicity

Omics‐Based Systems Vaccinology for Vaccine Target Identification

Preclinical Research Omics technologies include genomics, transcriptomics, proteomics, metabolomics, and immunomics. These technologies have been used in vaccine research, which can be summarized using the term “vaccinomics.” These omics technologies combined with advanced bioinformatics analysis form the core of “systems vaccinology.” Omics technologies provide powerful methods in vaccine target identification. The genomics‐based reverse vaccinology starts with predicting vaccine protein candidates through in silico bioinformatics analysis of genome sequences. The VIOLIN V axign vaccine design program ( http://www.violinet.org/vaxign ) is the first web‐based vaccine target prediction software based on the reverse vaccinology strategy. Systematic transcriptomics and proteomics analyses facilitate rational vaccine target identification by detesting genome‐wide gene expression profiles. Immunomics is the study of the set of antigens recognized by host immune systems and has also been used for efficient vaccine target prediction. With the large amount of omics data available, it is necessary to integrate various vaccine data using ontologies, including the G ene O ntology ( GO ) and V accine O ntology ( VO ), for more efficient vaccine target prediction and assessment. All these omics technologies combined with advanced bioinformatics analysis methods for a systems biology‐based vaccine target prediction strategy. This article reviews the various omics technologies and how they can be used in vaccine target identification.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94576/1/ddr21049.pd

Protein-protein interactions: network analysis and applications in drug discovery

Physical interactions among proteins constitute the backbone of cellular function, making them an attractive source of therapeutic targets. Although the challenges associated with targeting protein-protein interactions (PPIs) -in particular with small molecules are considerable, a growing number of functional PPI modulators is being reported and clinically evaluated. An essential starting point for PPI inhibitor screening or design projects is the generation of a detailed map of the human interactome and the interactions between human and pathogen proteins. Different routes to produce these biological networks are being combined, including literature curation and computational methods. Experimental approaches to map PPIs mainly rely on the yeast two-hybrid (Y2H) technology, which have recently shown to produce reliable protein networks. However, other genetic and biochemical methods will be essential to increase both coverage and resolution of current protein networks in order to increase their utility towards the identification of novel disease-related proteins and PPIs, and their potential use as therapeutic targets

Enzymes in Thymidylate Synthesis in Ureaplasma parvum as Medical Targets

The wall less bacterium Ureaplasma parvum (Up) is associated with ureathritis in adults and pneumonia in neonates. Up lack de novo nucleotide synthesis genes and has to import all DNA precursors. This thesis investigates known DNA biosynthesis pathways as targets for new antibiotics and concerns two enzymes in Up thymidylate synthesis; a thymidylate synthase (TS) and thymidine kinase (UpTK). TS activity was detected in Up-extracts and UU572 DNA could rescue a TS mutant E. coli. UU572 appeared to be proteolytic cleaved and cell cycle regulated in Up. Codon modified UU572 was cloned for expression in E. coli. However, no protein expression could be detected. A codon optimized synthesized UU572 homolog; MPN358 from Mycoplasma pneumonia was expressed in E. coli and showed TS activity. Low sequence homology to existing TSs suggests that UU572 and its homologs, belong to a new class of TS enzymes, which may contribute to future antibiotic development in human and veterinary medicine. Thirteen click chemistry-synthesized 3´-triazole thymidine analogs (1-13), using AZT as backbone, were evaluated with UpTK and hTK1. The bacterial TK exhibited a more open 3D structure than hTK1 explaining its substrate efficiency, while hTK1 seemed to have more closed structure as reflected by higher inhibition by the analogs. Docking models with 13 in TK1 structures revealed amino acid substitutions in the active site and most likely explain the different enzyme specificity. In addition, molecular docking could explain the 6-fold higher inhibition by the nucleoside analog 3´-azido-methyl-deoxythymidine (AZMT) with UpTK compared to hTK1. Nucleoside analogs have been used for fighting viruses with minimal side-effects. Why not use this strategy to control bacterial infections? The results presented in this thesis contribute towards attaining this goal

Computational analysis of protein interaction networks for infectious diseases

Infectious diseases caused by pathogens, including viruses, bacteria and parasites, pose a serious threat to human health worldwide. Frequent changes in the pattern of infection mechanisms and the emergence of multidrug resistant strains among pathogens have weakened the current treatment regimen. This necessitates the development of new therapeutic interventions to prevent and control such diseases. To cater to the need, analysis of protein interaction networks (PINs) has gained importance as one of the promising strategies. The present review aims to discuss various computational approaches to analyse the PINs in context to infectious diseases. Topology and modularity analysis of the network with their biological relevance, and the scenario till date about host-pathogen and intra-pathogenic protein interaction studies were delineated. This would provide useful insights to the research community thereby enabling them to design novel biomedicine against such infectious diseases

Biochemical and structural characterization of alanine racemase from Bacillus anthracis (Ames)

<p>Abstract</p> <p>Background</p> <p><it>Bacillus anthracis </it>is the causative agent of anthrax and a potential bioterrorism threat. Here we report the biochemical and structural characterization of <it>B. anthracis </it>(Ames) alanine racemase (Alr_<it>Bax</it>), an essential enzyme in prokaryotes and a target for antimicrobial drug development. We also compare the native Alr_{<it>Bax </it>}structure to a recently reported structure of the same enzyme obtained through reductive lysine methylation.</p> <p>Results</p> <p><it>B. anthracis </it>has two open reading frames encoding for putative alanine racemases. We show that only one, <it>dal1</it>, is able to complement a D-alanine auxotrophic strain of <it>E. coli</it>. Purified Dal1, which we term Alr_<it>Bax</it>, is shown to be a dimer in solution by dynamic light scattering and has a V_maxfor racemization (L- to D-alanine) of 101 U/mg. The crystal structure of unmodified Alr_{<it>Bax </it>}is reported here to 1.95 Å resolution. Despite the overall similarity of the fold to other alanine racemases, Alr_{<it>Bax </it>}makes use of a chloride ion to position key active site residues for catalysis, a feature not yet observed for this enzyme in other species. Crystal contacts are more extensive in the methylated structure compared to the unmethylated structure.</p> <p>Conclusion</p> <p>The chloride ion in Alr_{<it>Bax </it>}is functioning effectively as a carbamylated lysine making it an integral and unique part of this structure. Despite differences in space group and crystal form, the two Alr_{<it>Bax </it>}structures are very similar, supporting the case that reductive methylation is a valid rescue strategy for proteins recalcitrant to crystallization, and does not, in this case, result in artifacts in the tertiary structure.</p