Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.

BACKGROUND: The problem of drug resistance and bacterial persistence in tuberculosis is a cause of global alarm. Although, the UN's Sustainable Development Goals for 2030 has targeted a Tb free world, the treatment gap exists and only a few new drug candidates are in the pipeline. In spite of large information from medicinal chemistry to 'omics' data, there has been a little effort from pharmaceutical companies to generate pipelines for the development of novel drug candidates against the multi drug resistant Mycobacterium tuberculosis. METHODS: In the present study, we describe an integrated methodology; utilizing systems level information to optimize ligand selection to lower the failure rates at the pre-clinical and clinical levels. In the present study, metabolic targets (Rv2763c, Rv3247c, Rv1094, Rv3607c, Rv3048c, Rv2965c, Rv2361c, Rv0865, Rv0321, Rv0098, Rv0390, Rv3588c, Rv2244, Rv2465c and Rv2607) in M. tuberculosis, identified using our previous Systems Biology and data-intensive genome level analysis, have been used to design potential lead molecules, which are likely to be non-toxic. Various in silico drug discovery tools have been utilized to generate small molecular leads for each of the 15 targets with available crystal structures. RESULTS: The present study resulted in identification of 20 novel lead molecules including 4 FDA approved drugs (droxidropa, tetroxoprim, domperidone and nemonapride) which can be further taken for drug repurposing. This comprehensive integrated methodology, with both experimental and in silico approaches, has the potential to not only tackle the MDR form of Mtb but also the most important persister population of the bacterium, with a potential to reduce the failures in the Tb drug discovery. CONCLUSION: We propose an integrated approach of systems and structural biology for identifying targets that address the high attrition rate issue in lead identification and drug development We expect that this system level analysis will be applicable for identification of drug candidates to other pathogenic organisms as well.

iCHRCloud: Web & Mobile based Child Health Imprints for Smart Healthcare.

Reducing child mortality with quality care is the prime-most concern of all nations. Thus in current IT era, our healthcare industry needs to focus on adapting information technology in healthcare services. Barring few preliminary attempts to digitalize basic hospital administrative and clinical functions, even today in India, child health and vaccination records are still maintained as paper-based records. Also, error in manually plotting the parameters in growth charts results in missed opportunities for early detection of growth disorders in children. To address these concerns, we present India's first hospital linked, affordable automated vaccination and real-time child's growth monitoring cloud based application- Integrated Child Health Record cloud (iCHRcloud). This application is based on HL7 protocol enabling integration with hospital's HIS/EMR system. It provides Java (Enterprise Service Bus and Hibernate) based web portal for doctors and mobile application for parents, enhancing doctor-parent engagement. It leverages highchart to automate chart preparation and provides access of data via Push Notification (GCM and APNS) to parents on iOS and Android mobile platforms. iCHRcloud has also been recognized as one of the best innovative solution in three nationwide challenges, 2016 in India. iCHRcloud offers a seamless, secure (256 bit HTTPS) and sustainable solution to reduce child mortality. Detail analysis on preliminary data of 16,490 child health records highlight the diversified need of various demographic regions. Thus, primary lesson would be to implement better validation strategies to fulfill the customize requisites of entire population. This paper presents first glimpse of data and power of the analytics in policy framework.

iNICU - Integrated Neonatal Care Unit: Capturing Neonatal Journey in an Intelligent Data Way.

Neonatal period represents first 28 days of life, which is the most vulnerable time for a child's survival especially for the preterm babies. High neonatal mortality is a prominent and persistent problem across the globe. Non-availability of trained staff and infrastructure are the major recognized hurdles in the quality care of these neonates. Hourly progress growth charts and reports are still maintained manually by nurses along with continuous calculation of drug dosage and nutrition as per the changing weight of the baby. iNICU (integrated Neonatology Intensive Care Unit) leverages Beaglebone and Intel Edison based IoT integration with biomedical devices in NICU i.e. monitor, ventilator and blood gas machine. iNICU is hosted on IBM Softlayer based cloud computing infrastructure and map NICU workflow in Java based responsive web application to provide translational research informatics support to the clinicians. iNICU captures real time vital parameters i.e. respiration rate, heart rate, lab data and PACS amounting for millions of data points per day per child. Stream of data is sent to Apache Kafka layer which stores the same in Apache Cassandra NoSQL. iNICU also captures clinical data like feed intake, urine output, and daily assessment of child in PostgreSQL database. It acts as first Big Data hub (of both structured and unstructured data) of neonates across India offering temporal (longitudinal) data of their stay in NICU and allow clinicians in evaluating efficacy of their interventions. iNICU leverages drools based clinical rule based engine and deep learning based big data analytical model coded in R and PMML. iNICU solution aims to improve care time, fills skill gap, enable remote monitoring of neonates in rural regions, assists in identifying the early onset of disease, and reduction in neonatal mortality.

Metformin as a potential combination therapy with existing front-line antibiotics for Tuberculosis.

Tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb) remains a global health concern. The evolution of various multi-drug resistant strains through genetic mutations or drug tolerant strains through bacterial persistence renders existing antibiotics ineffective. Hence there is need for the development of either new antibiotics or rationalizing approved drugs that can be utilized in combination with existing antibiotics as a therapeutic strategy. A comprehensive systems level mapping of metabolic complexity in Mtb revels a putative role of NDH-I in the formation of bacterial persistence under the influence of front-line antibiotics. Possibilities of targeting bacterial NDH-I with existing FDA approved drug for type-II diabetes, Metformin, along with existing front-line antibiotics is discussed and proposed as a potential combination therapy for TB.

Systems level mapping of metabolic complexity in Mycobacterium tuberculosis to identify high-value drug targets.

BACKGROUND: The effectiveness of current therapeutic regimens for Mycobacterium tuberculosis (Mtb) is diminished by the need for prolonged therapy and the rise of drug resistant/tolerant strains. This global health threat, despite decades of basic research and a wealth of legacy knowledge, is due to a lack of systems level understanding that can innovate the process of fast acting and high efficacy drug discovery. METHODS: The enhanced functional annotations of the Mtb genome, which were previously obtained through a crowd sourcing approach was used to reconstruct the metabolic network of Mtb in a bottom up manner. We represent this information by developing a novel Systems Biology Spindle Map of Metabolism (SBSM) and comprehend its static and dynamic structure using various computational approaches based on simulation and design. RESULTS: The reconstructed metabolism of Mtb encompasses 961 metabolites, involved in 1152 reactions catalyzed by 890 protein coding genes, organized into 50 pathways. By accounting for static and dynamic analysis of SBSM in Mtb we identified various critical proteins required for the growth and survival of bacteria. Further, we assessed the potential of these proteins as putative drug targets that are fast acting and less toxic. Further, we formulate a novel concept of metabolic persister genes (MPGs) and compared our predictions with published in vitro and in vivo experimental evidence. Through such analyses, we report for the first time that de novo biosynthesis of NAD may give rise to bacterial persistence in Mtb under conditions of metabolic stress induced by conventional anti-tuberculosis therapy. We propose such MPG's as potential combination of drug targets for existing antibiotics that can improve their efficacy and efficiency for drug tolerant bacteria. CONCLUSION: The systems level framework formulated by us to identify potential non-toxic drug targets and strategies to circumvent the issue of bacterial persistence can substantially aid in the process of TB drug discovery and translational research.

From diversity to delivery: the case of the Indian Genome Variation initiative.

India currently has the world's second-largest population along with a fast-growing economy and significant economic disparity. It also continues to experience a high rate of infectious disease and increasingly higher rates of chronic diseases. However, India cannot afford to import expensive technologies and therapeutics nor can it, as an emerging economy, emulate the health-delivery systems of the developed world. Instead, to address these challenges it is looking to biotechnology-based innovation in the field of genomics. The Indian Genome Variation (IGV) consortium, a government-funded collaborative network among seven local institutions, is a reflection of these efforts. The IGV has recently developed the first large-scale database of genomic diversity in the Indian population that will facilitate research on disease predisposition, adverse drug reactions and population migration.

Parkinson's disease and schizophrenia interactomes contain temporally distinct gene clusters underlying comorbid mechanisms and unique disease processes.

Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ and can incorporate their spatiotemporal specificities. Therefore, to study the linked biology of PD and SZ, we compiled PD- and SZ-associated genes from the DisGeNET database, and constructed their interactomes using BioGRID and HPRD. We examined the interactomes using clustering and enrichment analyses, in conjunction with the transcriptomic data of 26 brain regions spanning foetal stages to adulthood available in the BrainSpan Atlas. PD and SZ interactomes formed four gene clusters with distinct temporal identities (Disease Gene Networks or 'DGNs'1-4). DGN1 had unique SZ interactome genes highly expressed across developmental stages, corresponding to a neurodevelopmental SZ subtype. DGN2, containing unique SZ interactome genes expressed from early infancy to adulthood, correlated with an inflammation-driven SZ subtype and adult SZ risk. DGN3 contained unique PD interactome genes expressed in late infancy, early and late childhood, and adulthood, and involved in mitochondrial pathways. DGN4, containing prenatally-expressed genes common to both the interactomes, involved in stem cell pluripotency and overlapping with the interactome of 22q11 deletion syndrome (comorbid psychosis and Parkinsonism), potentially regulates neurodevelopmental mechanisms in PD-SZ comorbidity. Our findings suggest that disrupted neurodevelopment (regulated by DGN4) could expose risk windows in PD and SZ, later elevating disease risk through inflammation (DGN2). Alternatively, variant clustering in DGNs may produce disease subtypes, e.g., PD-SZ comorbidity with DGN4, and early/late-onset SZ with DGN1/DGN2.

Posttranscriptional regulation of interleukin-10 expression by hsa-miR-106a.

IL-10 is a key regulator of the immune system that critically determines health and disease. Its expression is finely tuned both at the transcriptional and posttranscriptional levels. Although the importance of posttranscriptional regulation of IL-10 has been previously shown, understanding the underlying mechanisms is still in its infancy. In this study, using a combination of bioinformatics and molecular approaches, we report that microRNA (hsa-miR-106a) regulates IL-10 expression. The hsa-miR-106a binding site in the 3' UTR of IL10 has been identified by site-directed mutagenesis studies. Also, the involvement of transcription factors, Sp1 and Egr1, in the regulation of hsa-miR-106a expression and concomitant decrease in the IL-10 expression, has also been demonstrated. In summary, our results showed that IL-10 expression may be regulated by miR-106a, which is in turn transcriptionally regulated by Egr1 and Sp1.

HGVbaseG2P: a central genetic association database.

The Human Genome Variation database of Genotype to Phenotype information (HGVbaseG2P) is a new central database for summary-level findings produced by human genetic association studies, both large and small. Such a database is needed so that researchers have an easy way to access all the available association study data relevant to their genes, genome regions or diseases of interest. Such a depository will allow true positive signals to be more readily distinguished from false positives (type I error) that fail to consistently replicate. In this paper we describe how HGVbaseG2P has been constructed, and how its data are gathered and organized. We present a range of user-friendly but powerful website tools for searching, browsing and visualizing G2P study findings. HGVbaseG2P is available at http://www.hgvbaseg2p.org.

dbSMR: a novel resource of genome-wide SNPs affecting microRNA mediated regulation.

BACKGROUND: MicroRNAs (miRNAs) regulate several biological processes through post-transcriptional gene silencing. The efficiency of binding of miRNAs to target transcripts depends on the sequence as well as intramolecular structure of the transcript. Single Nucleotide Polymorphisms (SNPs) can contribute to alterations in the structure of regions flanking them, thereby influencing the accessibility for miRNA binding. DESCRIPTION: The entire human genome was analyzed for SNPs in and around predicted miRNA target sites. Polymorphisms within 200 nucleotides that could alter the intramolecular structure at the target site, thereby altering regulation were annotated. Collated information was ported in a MySQL database with a user-friendly interface accessible through the URL: (http://miracle.igib.res.in/dbSMR). CONCLUSION: The database has a user-friendly interface where the information can be queried using either the gene name, microRNA name, polymorphism ID or transcript ID. Combination queries using 'AND' or 'OR' is also possible along with specifying the degree of change of intramolecular bonding with and without the polymorphism. Such a resource would enable researchers address questions like the role of regulatory SNPs in the 3' UTRs and population specific regulatory modulations in the context of microRNA targets.

Meta-analysis of genomic variants and gene expression data in schizophrenia suggests the potential need for adjunctive therapeutic interventions for neuropsychiatric disorders.

Schizophrenia (SZ) is a debilitating mental illness with a multigenic aetiology and significant heritability. Despite extensive genetic studies, the molecular aetiology has remained enigmatic. A recent systems biology study suggested a protein-protein interaction network for SZ with 504 novel interactions. The onset of psychiatric disorders is predominant during adolescence, often accompanied by subtle structural abnormalities in multiple regions of the brain. The availability of BrainSpan Atlas data allowed us to re-examine the genes present in the SZ interactome as a function of space and time. The availability of genomes of healthy centenarians and nonpsychiatric Exome Aggregation Consortium database allowed us to identify the variants of criticality. The expression of the SZ candidate genes responsible for cognition and disease onset was studied in different brain regions during particular developmental stages. A subset of novel interactors detected in the network was further validated using gene expression data of post-mortem brains of patients with psychiatric illness. We have narrowed down the list of drug targets proposed by theprevious interactome study to 10 proteins. These proteins belonging to 81 biological pathways are targeted by 34 known Food and Drug Administration-approved drugs that have distinct potential for the treatment of neuropsychiatric disorders. We also report the possibility of targeting key genes belonging to celecoxib pharmacodynamics, Gα signalling and cGMP-PKG signalling pathwaysthat are not known to be specific to SZ aetiology.

Predicting protein homocysteinylation targets based on dihedral strain energy and pKa of cysteines.

A multitude of complex diseases have been linked to elevated homocysteine levels; however, till date there is no plausible explanation for a single amino acid's involvement in so many diseases. Since homocysteine is a reactive thiol amino acid and the majority of plasma homocysteine is protein thiol bound, we hypothesized that homocysteine might bind to accessible cysteine residues in target proteins, thereby modulating its structure or function or both. The parameters that dictate homocysteine-protein interaction are not well understood, and the few known homocysteine binding proteins were identified by a candidate protein approach. In this study, we identified potential homocysteine interacting proteins based on cysteine content, solvent accessibility of cysteine residues, and dihedral strain energies and pKa of these cysteines. Pathway mapping of the cysteine-rich proteins revealed that proteins in the coagulation cascade, notch receptor-mediated signaling, LDL endocytosis, programmed cell death, and extracellular matrix proteins were significantly over-represented with cysteine-rich proteins, and we believe that homocysteine has a high probability to bind to proteins in these pathways. In fact, several clinical studies have implicated high homocysteine levels to be associated with diseases like thrombosis, neural tube defects, and so forth, which result from dysfunction of one or more of the proteins identified in our study. Further, we successfully validated our prediction parameters on the proteins that have already been experimentally shown to bind homocysteine, and our structural analysis argues a plausible explanation for these prior reported protein interactions with homocysteine that could not be previously explained.

Human cellular microRNA hsa-miR-29a interferes with viral nef protein expression and HIV-1 replication.

BACKGROUND: Cellular miRNAs play an important role in the regulation of gene expression in eukaryotes. Recently, miRNAs have also been shown to be able to target and inhibit viral gene expression. Computational predictions revealed earlier that the HIV-1 genome includes regions that may be potentially targeted by human miRNAs. Here we report the functionality of predicted miR-29a target site in the HIV-1 nef gene. RESULTS: We find that the human miRNAs hsa-miR-29a and 29b are expressed in human peripheral blood mononuclear cells. Expression of a luciferase reporter bearing the nef miR-29a target site was decreased compared to the luciferase construct without the target site. Locked nucleic acid modified anti-miRNAs targeted against hsa-miR-29a and 29b specifically reversed the inhibitory effect mediated by cellular miRNAs on the target site. Ectopic expression of the miRNA results in repression of the target Nef protein and reduction of virus levels. CONCLUSION: Our results show that the cellular miRNA hsa-miR29a downregulates the expression of Nef protein and interferes with HIV-1 replication.

Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda.

BACKGROUND: Ayurveda is an ancient system of personalized medicine documented and practiced in India since 1500 B.C. According to this system an individual's basic constitution to a large extent determines predisposition and prognosis to diseases as well as therapy and life-style regime. Ayurveda describes seven broad constitution types (Prakritis) each with a varying degree of predisposition to different diseases. Amongst these, three most contrasting types, Vata, Pitta, Kapha, are the most vulnerable to diseases. In the realm of modern predictive medicine, efforts are being directed towards capturing disease phenotypes with greater precision for successful identification of markers for prospective disease conditions. In this study, we explore whether the different constitution types as described in Ayurveda has molecular correlates. METHODS: Normal individuals of the three most contrasting constitutional types were identified following phenotyping criteria described in Ayurveda in Indian population of Indo-European origin. The peripheral blood samples of these individuals were analysed for genome wide expression levels, biochemical and hematological parameters. Gene Ontology (GO) and pathway based analysis was carried out on differentially expressed genes to explore if there were significant enrichments of functional categories among Prakriti types. RESULTS: Individuals from the three most contrasting constitutional types exhibit striking differences with respect to biochemical and hematological parameters and at genome wide expression levels. Biochemical profiles like liver function tests, lipid profiles, and hematological parameters like haemoglobin exhibited differences between Prakriti types. Functional categories of genes showing differential expression among Prakriti types were significantly enriched in core biological processes like transport, regulation of cyclin dependent protein kinase activity, immune response and regulation of blood coagulation. A significant enrichment of housekeeping, disease related and hub genes were observed in these extreme constitution types. CONCLUSION: Ayurveda based method of phenotypic classification of extreme constitutional types allows us to uncover genes that may contribute to system level differences in normal individuals which could lead to differential disease predisposition. This is a first attempt towards unraveling the clinical phenotyping principle of a traditional system of medicine in terms of modern biology. An integration of Ayurveda with genomics holds potential and promise for future predictive medicine.

Intronic miRNA mediated gene expression regulation controls protein crowding inside the cell.

Gene regulatory effects of microRNAs at a posttranscriptional level have been established over the last decade. In this study, we analyze the interaction networks of mRNA translation regulation through intronic miRNA, under various tissue-specific cellular contexts, taking into account the thermodynamic affinity, chemical kinetics, co-localization, concentration levels, network parameters and the presence of competitive interactors. This database, and analysis has been made available through an open-access web-server, miRiam, to promote further exploration. Here we report that expression of genes involved in Apoptosis Processes, Immune System Processes, Translation Regulator Activities, and Molecular Transport Activities within the cell are predominately regulated by miRNA mediation. Our findings further indicate that this regulatory effect has a profound effect in controlling protein crowding inside the cell. A miRNA mediated gene expression regulation serves as a temporal regulator, allowing the cellular machinery to temporarily 'pause' the translation of mRNA, indicating that the miRNA-mRNA interactions may be important for governing the optimal usage of cell volume.

Paradigm for disease deconvolution in rare neurodegenerative disorders in Indian population: insights from studies in cerebellar ataxias.

Cerebellar ataxias are a group of rare progressive neurodegenerative disorders with an average prevalence ranges from 4.8 to 13.8 in 100,000 individuals. The inherited disorders affect multiple members of the families, or a community that is endogamous or consanguineous. Presence of more than 3000 mutations in different genes with overlapping clinical symptoms, genetic anticipation and pleiotropy, as well as incomplete penetrance and variable expressivity due to modifiers pose challenges in genotype-phenotype correlation. Development of a diagnostic algorithm could reduce the time as well as cost in clinicogenetic diagnostics and also help in reducing the economic and social burden of the disease. In a unique research collaboration spanning over 20 years, we have been able to develop a paradigm for studying cerebellar ataxias in the Indian population which would also be relevant in other rare diseases. This has involved clinical and genetic analysis of thousands of families from diverse Indian populations. The extensive resource on ataxia has led to the development of a clinicogenetic algorithm for cost-effective screening of ataxia and a unique ataxia clinic in the tertiary referral centre in All India Institute of Medical Sciences. Utilizing a population polymorphism scanning approach, we have been able to dissect the mechanisms of repeat instability and expansion in many ataxias, and also identify founders, and trace the mutational histories in the Indian population. This provides information for genetic testing of at-risk as well as protected individuals and populations. To dissect uncharacterized cases which comprises more than 50% of the cases, we have explored the potential of next-generation sequencing technologies coupled with the extensive resource of baseline data generated in-house and other public domains. We have also developed a repository of patient-derived peripheral blood mononuclear cells, lymphoblastoid cell lines and neuronal lineages (derived from iPSCs) for ascribing functionality to novel genes/mutations. Through integrating these technologies, novel genes have been identified that has broadened the diagnostic panel, increased the diagnostic yield to over 75%, helped in ascribing pathogenicity to novel mutations and enabled understanding of disease mechanisms. It has also provided a platform for testing novel molecules for amelioration of pathophysiological phenotypes. This review through a perspective on CAs suggests a generic paradigm fromdiagnostics to therapeutic interventions for rare disorders in the context of heterogeneous Indian populations.

Abundance of dinucleotide repeats and gene expression are inversely correlated: a role for gene function in addition to intron length.

High and broad transcription of eukaryotic genes is facilitated by cost minimization, clustered localization in the genome, elevated G+C content, and low nucleosome formation potential. In this scenario, illumination of correlation between abundance of (TG/CA)(n>or=12) repeats, which are negative cis modulators of transcription, and transcriptional levels and other commonly occurring dinucleotide repeats, is required. Three independent microarray datasets were used to examine the correlation of (TG/CA)(n>or=12) and other dinucleotide repeats with gene expression. Compared with the expected equi-distribution pattern under neutral model, highly transcribed genes were poor in repeats, and conversely, weakly transcribed genes were rich in repeats. Furthermore, the inverse correlation between repeat abundance and transcriptional levels appears to be a global phenomenon encompassing all genes regardless of their breadth of transcription. This selective pattern of exclusion of (TG/CA)(n>or=12) and (AT)(n>or=12) repeats in highly transcribed genes is an additional factor along with cost minimization and elevated GC, and therefore, multiple factors govern high transcription of genes. We observed that even after controlling for the effects of GC and average intron lengths, the effect of repeats albeit somewhat weaker was persistent and definite. In the ribosomal protein coding genes, sequence analysis of orthologs suggests that negative selection for repeats perhaps occurred early in evolution. These observations suggest that negative selection of (TG/CA)(n>or=12) microsatellites in the evolution of the highly expressed genes was also controlled by gene function in addition to intron length.

Structural assessment of glycyl mutations in invariantly conserved motifs.

Motifs that are evolutionarily conserved in proteins are crucial to their structure and function. In one of our earlier studies, we demonstrated that the conserved motifs occurring invariantly across several organisms could act as structural determinants of the proteins. We observed the abundance of glycyl residues in these invariantly conserved motifs. The role of glycyl residues in highly conserved motifs has not been studied extensively. Thus, it would be interesting to examine the structural perturbations induced by mutation in these conserved glycyl sites. In this work, we selected a representative set of invariant signature (IS) peptides for which both the PDB structure and mutation information was available. We thoroughly analyzed the conformational features of the glycyl sites and their local interactions with the surrounding residues. Using Ramachandran angles, we showed that the glycyl residues occurring in these IS peptides, which have undergone mutation, occurred more often in the L-disallowed as compared with the L-allowed region of the Ramachandran plot. Short range contacts around the mutation site were analyzed to study the steric effects. With the results obtained from our analysis, we hypothesize that any change of activity arising because of such mutations must be attributed to the long-range interaction(s) of the new residue if the glycyl residue in the IS peptide occurred in the L-allowed region of the Ramachandran plot. However, the mutation of those conserved glycyl residues that occurred in the L-disallowed region of the Ramachandran plot might lead to an altered activity of the protein as a result of an altered conformation of the backbone in the immediate vicinity of the glycyl residue, in addition to long range effects arising from the long side chains of the new residue. Thus, the loss of activity because of mutation in the conserved glycyl site might either relate to long range interactions or to local perturbations around the site depending upon the conformational preference of the glycyl residue.