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Quantitative structure–activity relationship (QSAR) analysis of plant‐derived compounds with larvicidal activity against Zika Aedes aegypti (Diptera: Culicidae) vector using freely available descriptors
Author(s) -
Saavedra Laura M,
Romanelli Gustavo P,
Duchowicz Pablo R
Publication year - 2018
Publication title -
pest management science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.296
H-Index - 125
eISSN - 1526-4998
pISSN - 1526-498X
DOI - 10.1002/ps.4850
Subject(s) - quantitative structure–activity relationship , aedes aegypti , chikungunya , loo , applicability domain , yellow fever , test set , molecular descriptor , artificial intelligence , dengue fever , computational biology , biology , machine learning , computer science , ecology , virology , virus , larva
A QSAR model for 60 larvicides against A. aegypti is established, employing the RM technique for correlating 18 326 descriptors. We provide a suitable tool for predicting LC 50 using a conformation‐independent approach.