Partial least square and k-nearest neighbor algorithms for improved 3D quantitative spectral data-activity relationship consensus modeling of acute toxicity.
A diverse set of 154 chemicals that included US Food and Drug Administration-regulated compounds tested for their aquatic toxicity in Daphnia magna were modeled by a 3-dimensional quantitative spectral data-activity relationship (3D-QSDAR). Two distinct algorithms, partial least squares (PLS) and Tanimoto similarity-based k-nearest neighbors (KNN), were used to process bin occupancy descriptor matrices obtained after tessellation of the 3D-QSDAR space into regularly sized bins. The performance of models utilizing bins ranging in size from 2 ppm × 2 ppm × 0.5 Å to 20 ppm × 20 ppm × 2.5 Å was explored. Rigorous quality-control criteria were imposed: 1) 100 randomized 20% hold-out test sets were generated and the average R(2) test of the respective models was used as a measure of their performance, and 2) a Y-scrambling procedure was used to identify chance correlations. A consensus between the best-performing composite PLS model using 0.5 Å × 14 ppm × 14 ppm bins and 10 latent variables (average R(2) test  = 0.770) and the best composite KNN model using 0.5 Å × 8 ppm × 8 ppm and 2 neighbors (average R(2) test  = 0.801) offered an improvement of about 7.5% (R(2) test consensus  = 0.845). Projection of the most frequently occurring bins on the standard coordinate space indicated that the presence of a primary or secondary amino group-substituted aromatic systems-would result in an increased toxic effect in Daphnia. The presence of a second aromatic ring with highly electronegative substituents 5 Å to 7 Å apart from the first ring would lead to a further increase in toxicity.
Division of Systems Biology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, Arizona.
Iva B
IB
Stoyanova-Slavova
Svetoslav H
SH
Slavov
Bruce
B
Pearce
Dan A
DA
Buzatu
Richard D
RD
Beger
Jon G
JG
Wilkes
D000465:Algorithms; D000818:Animals; D016000:Cluster Analysis; D032921:Consensus; D003621:Daphnia / Q000187:drug effects*; D054750:Ecotoxicology; D023381:Endpoint Determination; D004785:Environmental Pollutants / Q000737:chemistry* / Q000633:toxicity*; D016018:Least-Squares Analysis; D021281:Quantitative Structure-Activity Relationship; D014481:United States
D004785:Environmental Pollutants
3D quantitative spectral data-activity relationship (QSDAR); Aquatic toxicology; Computational toxicology; Consensus modeling; Multivariate statistic