Driving discovery of drugs and diagnostics in infectious diseases through data integration

AGÜERO F

Sao Pedro

Conferencia; X-meeting 2017 - 13th International Conference of the AB3C; 2017

Associação Brasileira de Bioinformática e Biologia Computacional

Driving discovery of drugs and diagnostics in infectious diseases through data integrationFernán Agüero Instituto de Investigaciones Biotecnológicas ? Instituto Tecnológico de Chascomús, Universidad Nacional de San Martín (UNSAM) ? Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET)The availability of genomic and a diverse array of genome-wide functional data for pathogens that cause tropical and neglected diseases has created new opportunities for the discovery and development of new drugs and diagnostics. Also, the availability of chemical information has increased recently, with the advent of public domain chemical resources and the open release of data from high throughput screening assays. However, to fully exploit these opportunities, all data must be effectively integrated and be easy to interrogate. The goal of databases and other bioinformatics resources is to provide this much-needed data integration. In our laboratory, we have invested a significant effort to the task of data integration, which serves as the main foundation for our research. As a result, we have contributed to the development of a number of bioinformatics resources, like the TDR Targets (tdrtargets.org) [1,2] and the TcSNP (snps.tcruzi.org) [3] databases. Integrated data allows the formulation of powerful and relevant questions across whole genomes. In this presentation, I will summarize a number of strategies that were enabled by careful data integration, and how these led to the prioritization of drug targets [4,5] and the discovery of different type of diagnostic markers [6-9]. Also, I will discuss how large-scale approaches based on high-density peptide microarrays are changing the landscape of diagnostic discovery for Chagas Disease [8-9].[1] Genomic-scale prioritization of drug targets: the TDR Targets database. Agüero F et al. (2008) Nat Rev Drug Discov. 7: 900. DOI: 10.1038/nrd2684[2] TDR Targets: a chemogenomics resource for neglected diseases. Magariños MP et al. (2012) Nucleic Acids Res. 40: D1118. DOI: 10.1093/nar/gkr1053[3] TcSNP: a database of genetic variation in Trypanosoma cruzi. Ackermann AA et al. (2009) Nucleic Acids Res. 37: D544 DOI: 10.1093/nar/gkn874[4] Identification of attractive drug targets in neglected-disease pathogens using an in silico approach. Crowther GJ et al. (2010) PLOS Negl Trop Dis. 4: e804. DOI: 10.1371/journal.pntd.0000804[5] A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases. Berenstein AJ, et al. (2016) PLOS Neglected Tropical Diseases 10: e0004300.[6] Diagnostic Peptide Discovery: Prioritization of Pathogen Diagnostic Markers Using Multiple Features. Carmona SJ et al. (2012) PLOS One 7: e50748. DOI: 10.1371/journal.pone.0050748[7] A simple strain typing assay for Trypanosoma cruzi: discrimination of major evolutionary lineages from a single amplification product. Cosentino RO and Agüero F (2012) PLOS Negl Trop Dis 6: e1777. DOI:10.1371/journal.pntd.0001777[8] Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants. Carmona SJ, et al. (2015) Molecular & Cellular Proteomics 14: 1871. DOI:10.1074/mcp.M114.045906[9] Next-generation ELISA diagnostic assay for Chagas Disease based on the combination of short peptidic epitopes. Mucci JS et al (2017). PLOS Neglected Tropical Diseases: accepted, in production.