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• W2041738217 abstract "In the current report, a sequential step-wise methodology based on in silico, in vitro and in vivo experimental procedures for the prompt detection of potential trichomonacidal drugs is proposed. A combinatorial of 12 QSAR (Quantitative Structure–Activity Relationship) models based on Linear Discrimination Analysis (LDA) are suggested for the rational identification of new trichomonacidal drugs from virtual screening of in house chemical libraries and drug databases. Subsequently, compounds selected as potential anti-trichomonas are screened in vitro against Trichomonas vaginalis. Finally, molecules with specific trichomonacidal activity are evaluated in vivo. Herein, different molecules were exposed to the proposed methodology. Firstly, the agents were virtually screened and two of the eight molecules (G-1 and dimetridazole) were classified as trichomonacidals by the 12 models. Subsequently both drugs were proved in vitro and in vivo following the workflow procedure. Although a remarkable in vitro activity was observed in both cases, dimetridazole achieved higher MIC100 activity than metronidazole against the resistant isolate. Furthermore, the in vivo models showed a remarkable reduction of lesions of more than 55% in both compounds. These observations support the current flowchart screening and suggest the use of dimetridazole as a promising drug-like scaffold for novel therapeutic alternatives against T. vaginalis resistant infections." @default.
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• W2041738217 date "2014-10-01" @default.
• W2041738217 modified "2023-10-14" @default.
• W2041738217 title "A sequential procedure for rapid and accurate identification of putative trichomonacidal agents" @default.
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• W2041738217 doi "https://doi.org/10.1016/j.mimet.2014.07.031" @default.
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