Abstract
Generative topographic mapping (GTM) has been used to visualize and analyze the chemical space of antimalarial compounds as well as to build predictive models linking structure of molecules with their antimalarial activity. For this, a database, including ~3000 molecules tested in one or several of 17 anti-Plasmodium activity assessment protocols, has been compiled by assembling experimental data from in-house and ChEMBL databases. GTM classification models built on subsets corresponding to individual bioassays perform similarly to the earlier reported SVM models. Zones preferentially populated by active and inactive molecules, respectively, clearly emerge in the class landscapes supported by the GTM model. Their analysis resulted in identification of privileged structural motifs of potential antimalarial compounds. Projection of marketed antimalarial drugs on this map allowed us to delineate several areas in the chemical space corresponding to different mechanisms of antimalarial activity. This helped us to make a suggestion about the mode of action of the molecules populating these zones.
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Abbreviations
- (Q)SPR/SAR:
-
(Quantitative) structure–property/structure–activity relationships
- (P)RP:
-
Privileged responsibility patterns
- PSM:
-
Privileged structural motifs
- GTM:
-
Generative topographic map
- AD:
-
Applicability domain
- MoA:
-
Mode of action
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Acknowledgements
The Laboratory of Chemoinformatics wishes to thank the High Performance Computing centers of the University of Strasbourg, France and the Babes-Bolyai University of Cluj, Romania for supplied computer power, and assistance. P.S. thanks Program of Competitive Growth of Kazan Federal University for support. B.V. is grateful to the European Social Fund (Grant 30.1-9.1/575, mediated by Archimedes Foundation, http://www.archimedes.ee, DoRa T6 subprogram, internationalization and mobility support scheme, for the mobility stipend) and the COST Action CM1307 for three short-term scientific missions (STSM) fellowships to Strasbourg to perform data analysis, curation and database creation, as well as the cheminformatics study. B.V. and U.M. are also grateful for financial support from the Estonian Ministry of Education and Research (Grant IUT34-14). This work was partly supported by the International Center for Frontier Research in Chemistry in Strasbourg (icFRC Innovation 2015 Program, project entitled “Computer-Aided Design of Novel Antimalarial Naphthoquinones (CAD-NQ)”, A.V., E.D.-C.) and the Laboratoire d’Excellence ParaFrap (grant LabEx ParaFrap ANR-11-LABX-0024, E.D.-C.).
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Sidorov, P., Viira, B., Davioud-Charvet, E. et al. QSAR modeling and chemical space analysis of antimalarial compounds. J Comput Aided Mol Des 31, 441–451 (2017). https://doi.org/10.1007/s10822-017-0019-4
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DOI: https://doi.org/10.1007/s10822-017-0019-4