Resistance related metabolic pathways for drug target identification in Mycobacterium tuberculosis.

BACKGROUND: Increasing resistance to anti-tuberculosis drugs has driven the need for developing new drugs. Resources such as the tropical disease research (TDR) target database and AssessDrugTarget can help to prioritize putative drug targets. Hower, these resources do not necessarily map to metabolic pathways and the targets are not involved in dormancy. In this study, we specifically identify drug resistance pathways to allow known drug resistant mutations in one target to be offset by inhibiting another enzyme of the same metabolic pathway. One of the putative targets, Rv1712, was analysed by modelling its three dimensional structure and docking potential inhibitors. RESULTS: We mapped 18 TB drug resistance gene products to 15 metabolic pathways critical for mycobacterial growth and latent TB by screening publicly available microarray data. Nine putative targets, Rv1712, Rv2984, Rv2194, Rv1311, Rv1305, Rv2195, Rv1622c, Rv1456c and Rv2421c, were found to be essential, to lack a close human homolog, and to share >67 % sequence identity and >87 % query coverage with mycobacterial orthologs. A structural model was generated for Rv1712, subjected to molecular dynamic simulation, and identified 10 compounds with affinities better than that for the ligand cytidine-5'-monophosphate (C5P). Each compound formed more interactions with the protein than C5P. CONCLUSIONS: We focused on metabolic pathways associated with bacterial drug resistance and proteins unique to pathogenic bacteria to identify novel putative drug targets. The ten compounds identified in this study should be considered for experimental studies to validate their potential as inhibitors of Rv1712.

DDPC: Dragon Database of Genes associated with Prostate Cancer.

Prostate cancer (PC) is one of the most commonly diagnosed cancers in men. PC is relatively difficult to diagnose due to a lack of clear early symptoms. Extensive research of PC has led to the availability of a large amount of data on PC. Several hundred genes are implicated in different stages of PC, which may help in developing diagnostic methods or even cures. In spite of this accumulated information, effective diagnostics and treatments remain evasive. We have developed Dragon Database of Genes associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise require tedious computational analyses, (ii) it integrates data on molecular interactions, pathways, gene ontologies, gene regulation at molecular level, predicted transcription factor binding sites on promoters of PC implicated genes and transcription factors that correspond to these binding sites and (iii) it contains DrugBank data on drugs associated with PC. We believe this resource will serve as a source of useful information for research on PC. DDPC is freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/ddpc/ and http://cbrc.kaust.edu.sa/ddpc/.

Identification of Parkinson's disease candidate genes using CAESAR and screening of MAPT and SNCAIP in South African Parkinson's disease patients.

Assuming that a significant cause of Parkinson's disease (PD) is genetic, genetic factors have been shown to account for <10% of all PD cases to date, and it is therefore necessary to identify novel genes. The aim of the present study was to identify PD candidate genes using a bioinformatic approach and to screen them for possible PD-causing mutations. The CAESAR (CAndidatE Search And Rank) program was used in the present study to identify and prioritize PD candidate genes. CAESAR ranks annotated human genes as candidates by using ontologies to semantically map natural language descriptions of the trait under investigation to gene-centric databases. Two of the candidates were selected and screened for mutations in 202 South African PD patients using the High-Resolution Melt (HRM) method. Samples exhibiting altered HRM profiles were sequenced. CAESAR generated a prioritized list of candidates including both known and novel PD genes. The MAPT and SNCAIP genes were selected for mutation screening from the list of ten highest scoring genes. Two novel missense (A91V and V635I), four synonymous and three intronic sequence variants were identified in MAPT. For SNCAIP, three novel missense (T383N, R606Q, N906H), one known (E709Q), four synonymous and one intronic sequence variant were found. A bioinformatic approach was used to aid in the identification and selection of PD candidate genes in a group of South African patients. Mutation screening of MAPT and SNCAIP identified novel sequence variants in both genes and further studies are necessary to determine their possible functional consequences.

Arrhythmogenic right ventricular cardiomyopathy type 6 (ARVC6): support for the locus assignment, narrowing of the critical region and mutation screening of three candidate genes.

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a heritable disorder characterized by progressive degeneration of right ventricular myocardium, arrhythmias and an increased risk of sudden death at a young age. By linkage analysis, ARVC type 6 was previously mapped to a 10.6 cM region on chromosome 10p12-p14 in a large North American kindred. To date, the genetic defect that causes ARVC6 has not been identified. METHODS: We identified a South African family of 13 members with ARVC segregating as an autosomal dominant disorder. The diagnosis of ARVC was based on international diagnostic criteria. All available family members were genotyped with microsatellite markers at six known ARVC loci, and positional candidate gene screening was performed. RESULTS: Genetic linkage and haplotype analysis provided lod scores that are highly suggestive of linkage to the ARVC6 locus on chromosome 10p12-p14, and the narrowing of the critical region to approximately 2.9 Mb. Two positional candidate genes (ITG8 and FRMD4A) were screened in which defects could possibly disrupt cell-cell adhesion. A non-positional candidate gene with apoptosis inducing properties, LAMR1P6 (laminin receptor 1 pseudogene 6) was also screened. Direct sequencing of DNA from affected individuals failed to detect disease-causing mutations in the exonic sequences of the three genes investigated. CONCLUSION: The narrowing of the ARVC6 critical region may facilitate progress towards the identification of the gene that is involved in ARVC. Identification of the causative genes for ARVC will contribute to the understanding of the pathogenesis and management of this poorly understood condition.

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds.

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferator-activator receptor (PPAR) α response in rat and human.

Apoptosis-inducing signal sequence mutation in carbonic anhydrase IV identified in patients with the RP17 form of retinitis pigmentosa.

Genetic and physical mapping of the RP17 locus on 17q identified a 3.6-megabase candidate region that includes the gene encoding carbonic anhydrase IV (CA4), a glycosylphosphatidylinositol-anchored protein that is highly expressed in the choriocapillaris of the human eye. By sequencing candidate genes in this region, we identified a mutation that causes replacement of an arginine with a tryptophan (R14W) in the signal sequence of the CA4 gene at position -5 relative to the signal sequence cleavage site. This mutation was found to cosegregate with the disease phenotype in two large families and was not found in 36 unaffected family members or 100 controls. Expression of the mutant cDNA in COS-7 cells produced several findings, suggesting a mechanism by which the mutation can explain the autosomal dominant disease. In transfected COS-7 cells, the R14W mutation (i) reduced the steady-state level of carbonic anhydrase IV activity expressed by 28% due to a combination of decreased synthesis and accelerated turnover; (ii) led to up-regulation of immunoglobulin-binding protein, double-stranded RNA-regulated protein kinase-like ER kinase, and CCAAT/enhancer-binding protein homologous protein, markers of the unfolded protein response and endoplasmic reticulum stress; and (iii) induced apoptosis, as evidenced by annexin V binding and terminal deoxynucleotidyltransferase-mediated dUTP nick end labeling staining, in most cells expressing the mutant, but not the WT, protein. We suggest that a high level of expression of the mutant allele in the endothelial cells of the choriocapillaris leads to apoptosis, leading in turn to ischemia in the overlying retina and producing autosomal dominant retinitis pigmentosa.