Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Identification of Critical Residues of the Mycobacterial Dephosphocoenzyme A Kinase by Site-Directed Mutagenesis

Dephosphocoenzyme A kinase performs the transfer of the c-phosphate of ATP to dephosphocoenzyme A, catalyzing the last step of coenzyme A biosynthesis. This enzyme belongs to the P-loop-containing NTP hydrolase superfamily, all members of which posses a three domain topology consisting of a CoA domain that binds the acceptor substrate, the nucleotide binding domain and the lid domain. Differences in the enzymatic organization and regulation between the human and mycobacterial counterparts, have pointed out the tubercular CoaE as a high confidence drug target (HAMAP database). Unfortunately the absence of a three-dimensional crystal structure of the enzyme, either alone or complexed with either of its substrates/regulators, leaves both the reaction mechanism unidentified and the chief players involved in substrate binding, stabilization and catalysis unknown. Based on homology modeling and sequence analysis, we chose residues in the three functional domains of the enzyme to assess their contributions to ligand binding and catalysis using site-directed mutagenesis. Systematically mutating the residues from the P-loop and the nucleotide-binding site identified Lys14 and Arg140 in ATP binding and the stabilization of the phosphoryl intermediate during the phosphotransfer reaction. Mutagenesis of Asp32 and Arg140 showed catalytic efficiencies less than 5-10% of the wild type, indicating the pivotal roles played by these residues in catalysis. Non-conservative substitution of the Leu114 residue identifies this leucine as the critical residue from the hydrophobic cleft involved in leading substrate, DCoA binding. We show that the mycobacterial enzyme requires the Mg2+ for its catalytic activity. The binding energetics of the interactions of the mutant enzymes with the substrates were characterized in terms of their enthalpic and entropic contributions by ITC, providing a complete picture of the effects of the mutations on activity. The properties of mutants defective in substrate recognition were consistent with the ordered sequential mechanism of substrate addition for CoaE.

Identification of Early Biomarkers during Acetaminophen-Induced Hepatotoxicity by Fourier Transform Infrared Microspectroscopy

Acetaminophen is a widely prescribed drug used to relieve pain and fever; however, it is a leading cause of drug-induced liver injury and a burden on public healthcare. In this study, hepatotoxicity in mice post oral dosing of acetaminophen was investigated using liver and sera samples with Fourier Transform Infrared microspectroscopy. The infrared spectra of acetaminophen treated livers in BALB/ mice show decrease in glycogen, increase in amounts of cholesteryl esters and DNA respectively. Rescue experiments using L-methionine demonstrate that depletion in glycogen and increase in DNA are abrogated with pre-treatment, but not post-treatment, with L-methionine. This indicates that changes in glycogen and DNA are more sensitive to the rapid depletion of glutathione. Importantly, analysis of sera identified lowering of glycogen and increase in DNA and chlolesteryl esters earlier than increase in alanine aminotransferase, which is routinely used to diagnose liver damage. In addition, these changes are also observed in C57BL/6 and Nos2(-/-) mice. There is no difference in the kinetics of expression of these three molecules in both strains of mice, the extent of damage is similar and corroborated with ALT and histological analysis. Quantification of cytokines in sera showed increase upon APAP treatment. Although the levels of Tnf alpha and Ifn gamma in sera are not significantly affected, Nos2(-/-) mice display lower Il6 but higher Il10 levels during this acute model of hepatotoxicity. Overall, this study reinforces the growing potential of Fourier Transform Infrared microspectroscopy as a fast, highly sensitive and label-free technique for non-invasive diagnosis of liver damage. The combination of Fourier Transform Infrared microspectroscopy and cytokine analysis is a powerful tool to identify multiple biomarkers, understand differential host responses and evaluate therapeutic regimens during liver damage and, possibly, other diseases.

Network approaches to drug discovery

Introduction: Advances in genomics technologies are providing a very large amount of data on genome-wide gene expression profiles, protein molecules and their interactions with other macromolecules and metabolites. Molecular interaction networks provide a useful way to capture this complex data and comprehend it. Networks are beginning to be used in drug discovery, in many steps of the modern discovery pipeline, with large-scale molecular networks being particularly useful for the understanding of the molecular basis of the disease. Areas covered: The authors discuss network approaches used for drug target discovery and lead identification in the drug discovery pipeline. By reconstructing networks of targets, drugs and drug candidates as well as gene expression profiles under normal and disease conditions, the paper illustrates how it is possible to find relationships between different diseases, find biomarkers, explore drug repurposing and study emergence of drug resistance. Furthermore, the authors also look at networks which address particular important aspects such as off-target effects, combination-targets, mechanism of drug action and drug safety. Expert opinion: The network approach represents another paradigm shift in drug discovery science. A network approach provides a fresh perspective of understanding important proteins in the context of their cellular environments, providing a rational basis for deriving useful strategies in drug design. Besides drug target identification and inferring mechanism of action, networks enable us to address new ideas that could prove to be extremely useful for new drug discovery, such as drug repositioning, drug synergy, polypharmacology and personalized medicine.

Role of Vertex Index in Substructure Identification and Activity Prediction: A Study on Antitubercular Activity of a Series of Acid Alkyl Ester Derivatives

Tuberculosis (TB) is a life threatening disease caused due to infection from Mycobacterium tuberculosis (Mtb). That most of the TB strains have become resistant to various existing drugs, development of effective novel drug candidates to combat this disease is a need of the day. In spite of intensive research world-wide, the success rate of discovering a new anti-TB drug is very poor. Therefore, novel drug discovery methods have to be tried. We have used a rule based computational method that utilizes a vertex index, named `distance exponent index (D-x)' (taken x = -4 here) for predicting anti-TB activity of a series of acid alkyl ester derivatives. The method is meant to identify activity related substructures from a series a compounds and predict activity of a compound on that basis. The high degree of successful prediction in the present study suggests that the said method may be useful in discovering effective anti-TB compound. It is also apparent that substructural approaches may be leveraged for wide purposes in computer-aided drug design.

Recognizing drug targets using evolutionary information: implications for repurposing FDA-approved drugs against Mycobacterium tuberculosis H37Rv

Drug repurposing to explore target space has been gaining pace over the past decade with the upsurge in the use of systematic approaches for computational drug discovery. Such a cost and time-saving approach gains immense importance for pathogens of special interest, such as Mycobacterium tuberculosis H37Rv. We report a comprehensive approach to repurpose drugs, based on the exploration of evolutionary relationships inferred from the comparative sequence and structural analyses between targets of FDA-approved drugs and the proteins of M. tuberculosis. This approach has facilitated the identification of several polypharmacological drugs that could potentially target unexploited M. tuberculosis proteins. A total of 130 FDA-approved drugs, originally intended against other diseases, could be repurposed against 78 potential targets in M. tuberculosis. Additionally, we have also made an attempt to augment the chemical space by recognizing compounds structurally similar to FDA-approved drugs. For three of the attractive cases we have investigated the probable binding modes of the drugs in their corresponding M. tuberculosis targets by means of structural modelling. Such prospective targets and small molecules could be prioritized for experimental endeavours, and could significantly influence drug-discovery and drug-development programmes for tuberculosis.

Identification of actin as an estradiol 17-beta-stimulated protein in the human placenta

Addition of estradiol 17-beta to first trimester human placental minces resulted in an increased synthesis of a protein of apparent molecular weight 45 kDa. The specific involvement of estrogen in the stimulation of this protein was established by demonstrating a reduction in the level of this protein by the addition of CCS 16949 A, an inhibitor of aromatase, a key enzyme in the biosynthesis of estradiol 17-beta and ICI 182,780, an estrogen receptor antagonist. The protein was purified to homogeneity and N-terminal sequencing of two of the internal peptides obtained by enzymatic digestion of the protein, as well as the absence of a free N-terminal indicated that it could be actin. This was confirmed by Western blotting using commercially available actin antiserum. The role of estradiol 17-beta in the stimulation of actin synthesis in human placenta was also established by monitoring the quantitative inhibition of DNase I by actin.

Identification of amino groups in the carbohydrate binding activity of winged bean acidic agglutinin

Chemical modification studies reveal that the modification of amino groups in WBA II leads to a complete loss in the hemagglutinating and saccharide binding activities. Since WBA II is a dimeric molecule and contains two binding sites, one amino group in each of the binding sites is inferred to be essential for its activity. The presence of amino group which has a potential to form hydrogen bonded interactions with the ligand, substantiates our observation regarding the forces involved in WBA II-receptor and WBA II-simple sugar interactions.

Inverse Sensitivity Analysis of Singular Solutions of FRF matrix in Structural System Identification

The problem of structural damage detection based on measured frequency response functions of the structure in its damaged and undamaged states is considered. A novel procedure that is based on inverse sensitivity of the singular solutions of the system FRF matrix is proposed. The treatment of possibly ill-conditioned set of equations via regularization scheme and questions on spatial incompleteness of measurements are considered. The application of the method in dealing with systems with repeated natural frequencies and (or) packets of closely spaced modes is demonstrated. The relationship between the proposed method and the methods based on inverse sensitivity of eigensolutions and frequency response functions is noted. The numerical examples on a 5-degree of freedom system, a one span free-free beam and a spatially periodic multi-span beam demonstrate the efficacy of the proposed method and its superior performance vis-a-vis methods based on inverse eigensensitivity.

Identification of a discrete intermediate in the assembly disassembly of physalis mottle tymovirus through mutational analysis

Assembly intermediates of icosahedral viruses are usually transient and are difficult to identify. In the present investigation, site-specific and deletion mutants of the coat protein gene of physalis mottle tymovirus (PhMV) were used to delineate the role of specific amino acid residues in the assembly of the virus and to identify intermediates in this process. N-terminal 30, 34, 35 and 39 amino acid deletion and single C-terminal (N188) deletion mutant proteins of PhMV were expressed in Escherichia coli. Site-specific mutants H69A, C75A, W96A, D144N, D144N-T151A, K143E and N188A were also constructed and expressed. The mutant protein lacking 30 amino acid residues from the N terminus self-assembled to T = 3 particles in vivo while deletions of 34, 35 and 39 amino acid residues resulted in the mutant proteins that were insoluble. Interestingly, the coat protein (pR PhCP) expressed using pRSET B vector with an additional 41 amino acid residues at the N terminus also assembled into T = 3 particles that were more compact and had a smaller diameter. These results demonstrate that the amino-terminal segment is flexible and either the deletion or addition of amino acid residues at the N terminus does not affect T = 3 capsid assembly, in contrast, the deletion of even a single residue from the C terminus (PhN188 Delta 1) resulted in capsids that were unstable. These capsids disassembled to a discrete intermediate with a sedimentation coefficent of 19.4 S. However, the replacement of C-terminal asparagine 188 by alanine led to the formation of stable capsids. The C75A and D144N mutant proteins also assembled into capsids that were as stable as the pR PhCP, suggesting that C75A and D144 are not crucial for the T = 3 capsid assembly. pR PhW96A and pR PhD144N-T151A mutant proteins failed to form capsids and were present as heterogeneous aggregates. Interestingly, the pR PhK143E mutant protein behaved in a manner similar to the C-terminal deletion protein in forming unstable capsids. The intermediate with an s value of 19.4 S was the major assembly product of pR PhH69A mutant protein and could correspond to a 30mer. It is possible that the assembly or disassembly is arrested at a similar stage in pR PhN188 Delta 1, pR PhH69A and pR PhK143E mutant proteins.

Identification of the nature of platinum related midgap state in silicon by deep level transient spectroscopy

In this article, we present the detailed investigations on platinum related midgap state corresponding to E-c -0.52 eV probed by deep level transient spectroscopy. By irradiating the platinum doped samples with high-energy (1.1 MeV) gamma rays, we observed that the concentration of the midgap state increases and follows a square dependence with irradiation dose. However, the concentration of the acceptor corresponding to E-c -20.28 eV remained constant. Furthermore, from the studies on passivation by atomic hydrogen and thermal reactivation, we noticed that the E-c -0.52 eV level reappears in the samples annealed at high temperatures after hydrogenation. The interaction of platinum with various defects and the qualitative arguments based on the law of mass action suggest that the platinum related midgap defect might possibly correspond to the interstitial platinum-divacancy complex (V-Pt-V).

Identification of putative regulatory motifs in the upstream regions of co-expressed functional groups of genes in Plasmodium falciparum

Background: Regulation of gene expression in Plasmodium falciparum (Pf) remains poorly understood. While over half the genes are estimated to be regulated at the transcriptional level, few regulatory motifs and transcription regulators have been found. Results: The study seeks to identify putative regulatory motifs in the upstream regions of 13 functional groups of genes expressed in the intraerythrocytic developmental cycle of Pf. Three motif-discovery programs were used for the purpose, and motifs were searched for only on the gene coding strand. Four motifs – the 'G-rich', the 'C-rich', the 'TGTG' and the 'CACA' motifs – were identified, and zero to all four of these occur in the 13 sets of upstream regions. The 'CACA motif' was absent in functional groups expressed during the ring to early trophozoite transition. For functional groups expressed in each transition, the motifs tended to be similar. Upstream motifs in some functional groups showed 'positional conservation' by occurring at similar positions relative to the translational start site (TLS); this increases their significance as regulatory motifs. In the ribonucleotide synthesis, mitochondrial, proteasome and organellar translation machinery genes, G-rich, C-rich, CACA and TGTG motifs, respectively, occur with striking positional conservation. In the organellar translation machinery group, G-rich motifs occur close to the TLS. The same motifs were sometimes identified for multiple functional groups; differences in location and abundance of the motifs appear to ensure different modes of action. Conclusion: The identification of positionally conserved over-represented upstream motifs throws light on putative regulatory elements for transcription in Pf.