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      Discovery of New Inhibitors of Toxoplasma gondii via the Pathogen Box

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          ABSTRACT

          Toxoplasma gondii is a cosmopolitan protozoan parasite which affects approximately 30% of the population worldwide. The drugs currently used against toxoplasmosis are few in number and show several limitations, such as drug intolerance, poor bioavailability, or drug resistance mechanism developed by the parasite. Thus, it is important to find new compounds able to inhibit parasite invasion or proliferation. In this study, the 400 compounds of the open-access Pathogen Box, provided by the Medicines for Malaria Venture (MMV) foundation, were screened for their anti- Toxoplasma gondii activity. A preliminary in vitro screening performed over 72 h by an enzyme-linked immunosorbent assay (ELISA) revealed 15 interesting compounds that were effective against T. gondii at 1 μM. Their cytotoxicity was estimated on Vero cells, and their 50% inhibitory concentrations (IC 50) were further calculated. As a result, eight anti- Toxoplasma gondii compounds with an IC 50 of less than 2 μM and a selectivity index (SI) value of greater than 4 were identified. The most active was MMV675968, showing an IC 50 of 0.02 μM and a selectivity index value equal to 275. Two other compounds, MMV689480 and MMV687807, also showed a good activity against T. gondii, with IC 50s of 0.10 μM (SI of 86.6) and 0.15 μM (SI of 11.3), respectively. Structure-activity relationships for the eight selected compounds also were discussed on the basis of fingerprinting similarity measurements using the Tanimoto method. The anti- Toxoplasma gondii compounds highlighted here represent potential candidates for the development of new drugs that could be used against toxoplasmosis.

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          Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?

          Background Cheminformaticians are equipped with a very rich toolbox when carrying out molecular similarity calculations. A large number of molecular representations exist, and there are several methods (similarity and distance metrics) to quantify the similarity of molecular representations. In this work, eight well-known similarity/distance metrics are compared on a large dataset of molecular fingerprints with sum of ranking differences (SRD) and ANOVA analysis. The effects of molecular size, selection methods and data pretreatment methods on the outcome of the comparison are also assessed. Results A supplier database (https://mcule.com/) was used as the source of compounds for the similarity calculations in this study. A large number of datasets, each consisting of one hundred compounds, were compiled, molecular fingerprints were generated and similarity values between a randomly chosen reference compound and the rest were calculated for each dataset. Similarity metrics were compared based on their ranking of the compounds within one experiment (one dataset) using sum of ranking differences (SRD), while the results of the entire set of experiments were summarized on box and whisker plots. Finally, the effects of various factors (data pretreatment, molecule size, selection method) were evaluated with analysis of variance (ANOVA). Conclusions This study complements previous efforts to examine and rank various metrics for molecular similarity calculations. Here, however, an entirely general approach was taken to neglect any a priori knowledge on the compounds involved, as well as any bias introduced by examining only one or a few specific scenarios. The Tanimoto index, Dice index, Cosine coefficient and Soergel distance were identified to be the best (and in some sense equivalent) metrics for similarity calculations, i.e. these metrics could produce the rankings closest to the composite (average) ranking of the eight metrics. The similarity metrics derived from Euclidean and Manhattan distances are not recommended on their own, although their variability and diversity from other similarity metrics might be advantageous in certain cases (e.g. for data fusion). Conclusions are also drawn regarding the effects of molecule size, selection method and data pretreatment on the ranking behavior of the studied metrics. Graphical Abstract A visual summary of the comparison of similarity metrics with sum of ranking differences (SRD). Electronic supplementary material The online version of this article (doi:10.1186/s13321-015-0069-3) contains supplementary material, which is available to authorized users.
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            Intercontinental spread of pyrimethamine-resistant malaria.

            Here we present molecular evidence demonstrating that malaria parasites bearing high-level pyrimethamine resistance originally arrived in Africa from southeast Asia. The resistance alleles carried by these migrants are now spreading across Africa at an alarming rate, signaling the end of affordable malaria treatment and presenting sub-Saharan Africa with a public health crisis.
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              Atom pairs as molecular features in structure-activity studies: definition and applications

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                Author and article information

                Journal
                Antimicrob Agents Chemother
                Antimicrob. Agents Chemother
                aac
                aac
                AAC
                Antimicrobial Agents and Chemotherapy
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0066-4804
                1098-6596
                13 November 2017
                25 January 2018
                February 2018
                25 January 2018
                : 62
                : 2
                : e01640-17
                Affiliations
                [a ]Laboratoire de Parasitologie–Mycologie, EA 3800, SFR CAP-Santé FED 4231, Centre Hospitalier de Reims et Université de Reims Champagne-Ardenne, Reims Cedex, France
                [b ]UMR CNRS 7312, Université de Reims Champagne-Ardenne, Reims Cedex 2, France
                [c ]Biomatériaux et Inflammation en site Osseux, EA 4691, Université de Reims Champagne-Ardenne, Reims Cedex, France
                [d ]Centre National de Référence de la Toxoplasmose, Centre de Ressources Biologiques Toxoplasma, EA 3800, SFR CAP-Santé FED 4231, Centre Hospitalier de Reims et Université de Reims Champagne-Ardenne, Reims Cedex, France
                Author notes
                Address correspondence to Isabelle Villena, ivillena@ 123456chu-reims.fr .
                [*]

                Present address: Simon Duchateau, Université de Lille-1 - Sciences et Technologies, Cité Scientifique, Villeneuve d'Ascq Cedex, France.

                Citation Spalenka J, Escotte-Binet S, Bakiri A, Hubert J, Renault J-H, Velard F, Duchateau S, Aubert D, Huguenin A, Villena I. 2018. Discovery of new inhibitors of Toxoplasma gondii via the pathogen box. Antimicrob Agents Chemother 62:e01640-17. https://doi.org/10.1128/AAC.01640-17.

                Article
                01640-17
                10.1128/AAC.01640-17
                5786798
                29133550
                1b98a57f-2602-45ac-ac11-f2e3b75a6df8
                Copyright © 2018 Spalenka et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 10 August 2017
                : 2 October 2017
                : 29 October 2017
                Page count
                Figures: 4, Tables: 2, Equations: 0, References: 39, Pages: 10, Words: 5908
                Categories
                Pharmacology
                Custom metadata
                February 2018

                Infectious disease & Microbiology
                toxoplasma gondii,drug screening,antitoxoplasmic compound,pathogen box,antitoxoplasmic activity

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