0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Short-course combination treatment for experimental chronic Chagas disease

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, affects millions of people in the Americas and across the world leading to considerable morbidity and mortality. Current treatment options, benznidazole (BNZ) and nifurtimox, offer limited efficacy and often lead to adverse side effects due to long treatment durations. Better treatment options are therefore urgently required. Here we describe a pyrrolopyrimidine series, identified through phenotypic screening, that offers a clear opportunity to improve on current treatments. In vitro cell-based washout assays demonstrate that compounds in the series are incapable of killing all parasites, however, combining these pyrrolopyrimidines with a sub-efficacious dose of BNZ can clear all parasites in vitro after five days. Importantly, these findings were replicated in a clinically predictive in vivo model of chronic Chagas disease, where five days treatment with the combination was sufficient to prevent parasite relapse. Comprehensive mechanism of action studies, supported by ligand-structure modelling, show that compounds from this pyrrolopyrimidine series inhibit the Q i active site of T. cruzi cytochrome b, part of the cytochrome bc1 complex of the electron transport chain. Knowledge of the molecular target enabled a cascade of assays to be assembled to evaluate selectivity over the human cytochrome b homologue. As a result, a highly selective and efficacious lead compound was identified. The combination of our lead compound with BNZ rapidly clears T. cruzi parasites, both in vitro and in vivo, and shows great potential to overcome key issues associated with currently available treatments.

          Related collections

          Most cited references82

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.

              Heng Li (2011)
              Most existing methods for DNA sequence analysis rely on accurate sequences or genotypes. However, in applications of the next-generation sequencing (NGS), accurate genotypes may not be easily obtained (e.g. multi-sample low-coverage sequencing or somatic mutation discovery). These applications press for the development of new methods for analyzing sequence data with uncertainty. We present a statistical framework for calling SNPs, discovering somatic mutations, inferring population genetical parameters and performing association tests directly based on sequencing data without explicit genotyping or linkage-based imputation. On real data, we demonstrate that our method achieves comparable accuracy to alternative methods for estimating site allele count, for inferring allele frequency spectrum and for association mapping. We also highlight the necessity of using symmetric datasets for finding somatic mutations and confirm that for discovering rare events, mismapping is frequently the leading source of errors. http://samtools.sourceforge.net. hengli@broadinstitute.org.
                Bookmark

                Author and article information

                Journal
                101505086
                Sci Transl Med
                Sci Transl Med
                Science translational medicine
                1946-6234
                1946-6242
                13 December 2023
                13 December 2023
                20 February 2024
                29 February 2024
                : 15
                : 726
                : eadg8105
                Affiliations
                [1 ]Global Health Medicines R&D, GSK, Tres Cantos, Madrid, Spain
                [2 ]Global Investigative Safety, GSK, Ware, UK
                [3 ]Discovery DMPK, GSK Tres Cantos, Madrid, Spain
                [4 ]London School for Hygiene and Tropical Medicine, London, UK
                [5 ]Wellcome Centre for Anti-Infectives Research, University of Dundee, Dundee, UK
                [6 ]DNDi, Geneva, Switzerland
                [7 ]Epichem, Bentley, Australia
                Author notes
                [* ]corresponding authors Susan Wyllie: s.wyllie@ 123456dundee.ac.uk Tim Miles: tim.j.miles@ 123456gsk.com Manu De Rycker: m.derycker@ 123456dundee.ac.uk
                [#]

                Present affiliation: Department of Infection Biology, London School for Hygiene and Tropical Medicine, London, UK

                [ǂ]

                Present affiliation: Development Global Clinical Operations, GSK, Rueil Malmaison, France

                [ǁ]

                Present affiliation: Evoenzyme, Madrid, Spain

                [˭]

                Present affiliation: SYNthesis Research Pty Ltd, Melbourne, Australia

                [˺]

                Present affiliation: BASF, Ludwigshafen, Rhineland-Palatinate, Germany

                [˜]

                Present affiliation: Vertex Pharmaceuticals, UK

                Article
                EMS194243
                10.1126/scitranslmed.adg8105
                7615676
                38091410
                24c272ed-8111-455d-a354-2f99f866c8e6

                This work is licensed under a BY 4.0 International license.

                History
                Categories
                Article

                Comments

                Comment on this article