8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Discovery of Leishmania Druggable Serine Proteases by Activity-Based Protein Profiling

      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

          Leishmaniasis are a group of diseases caused by parasitic protozoa of the genus Leishmania. Current treatments are limited by difficult administration, high cost, poor efficacy, toxicity, and growing resistance. New agents, with new mechanisms of action, are urgently needed to treat the disease. Although extensively studied in other organisms, serine proteases (SPs) have not been widely explored as antileishmanial drug targets. Herein, we report for the first time an activity-based protein profiling (ABPP) strategy to investigate new therapeutic targets within the SPs of the Leishmania parasites. Active-site directed fluorophosphonate probes (rhodamine and biotin-conjugated) were used for the detection and identification of active Leishmania serine hydrolases (SHs). Significant differences were observed in the SHs expression levels throughout the Leishmania life cycle and between different Leishmania species. Using iTRAQ-labelling-based quantitative proteomic mass spectrometry, we identified two targetable SPs in Leishmania mexicana: carboxypeptidase LmxM.18.0450 and prolyl oligopeptidase LmxM.36.6750. Druggability was ascertained by selective inhibition using the commercial serine protease inhibitors chymostatin, lactacystin and ZPP, which represent templates for future anti-leishmanial drug discovery programs. Collectively, the use of ABPP method complements existing genetic methods for target identification and validation in Leishmania.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: found
          • Article: not found

          MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

          Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            UniProt: the universal protein knowledgebase in 2021

            Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The Perseus computational platform for comprehensive analysis of (prote)omics data.

              A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                15 July 2022
                2022
                : 13
                : 929493
                Affiliations
                [1] 1 Department of Chemistry , Durham University , Durham, United Kingdom
                [2] 2 School of Health and Life Sciences , Teesside University , Middlesbrough, United Kingdom
                [3] 3 National Horizons Centre , Darlington, United Kingdom
                Author notes

                Edited by: Hendrik W. Van Veen, University of Cambridge, United Kingdom

                Reviewed by: Mick Urbaniak, Lancaster University, United Kingdom

                Reik Löser, Helmholtz Association of German Research Centres (HZ), Germany

                *Correspondence: Exequiel O. J. Porta, exequiel.o.porta@ 123456durham.ac.uk ; Patrick G. Steel, p.g.steel@ 123456durham.ac.uk

                This article was submitted to Pharmacology of Infectious Diseases, a section of the journal Frontiers in Pharmacology

                Article
                929493
                10.3389/fphar.2022.929493
                9335491
                35910377
                05dffdab-cd39-48bc-a469-943a5237b1b5
                Copyright © 2022 Porta, Isern, Kalesh and Steel.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 26 April 2022
                : 21 June 2022
                Funding
                Funded by: Global Challenges Research Fund , doi 10.13039/100016270;
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                abpp,fluorophosphonate,leishmania,proteomics,serine proteases,serine protease inhibitors. discovery of leishmania druggable serine proteases

                Comments

                Comment on this article