Description:
Regression model with 6 QuBiLS-MIDAS descriptors used for the logarithmic values prediction of the minimum effective dose (Log(MED)) in µmol/cm2 to trigger Aedes aegypti repellency.

The training was performed with the Stacking algorithm as default in Weka 3.9.4 with 10-fold cross-validation by using Gaussian Processes algorithm (with Pearson Universal Kernel (PUK)) as meta classifier and as classifiers: SMOreg (with Pearson Universal Kernel (PUK)) and IBk (with K-nearest neighbors = 10 and True cross-validation). The 6 QuBiLS-MIDAS descriptors are namely:

GV[5]_S_Q_AB_nCi_2_M3_NS6_o_C_KA_r_MID
K_Q_AB_nCi_2_M2_SS12_n_A_KA_a_MID
CHOQUET[D;-0.75;AO1;0.2]_F_AB_nCi_2_M10_NS1_T_KA_p_MID
S_B_AB_nCi_2_M3_SS9_T_KA_r-p_MID
GV[3]_N1_F_AB_nCi_2_M1_MP1_T_KA_v_MID
VC_F_AB_nCi_2_M15_SS9_C_KA_psa_MID

Training set:
71 compounds extracted from 10.1371/journal.pone.0064547

Test set:
8 carboxamides proposed by Oliferenko et al. (10.1371/journal.pone.0064547) were used for external validation.

Performance:
For a 10-fold cross-validation, the statistical parameters (performance without applicability domain) are R = 0.8731, MAE = 0.3183, RMSE = 0.412, RAE = 50.1658 %, and RRSE = 49.2254 %.

Classification Breakpoint:
The breakpoint is -0.82 µmol/cm2. Values lower than the breakpoint will elicit a repellent response in the Aedes aegypti mosquito. Values greater than or equal to is -0.82 µmol/cm2 represent certain actions occurring, however, these are not enough to activate a repellent reaction in the mosquito.

Reference:
Oliferenko et al. Promising Aedes aegypti Repellent Chemotypes Identified through Integrated QSAR, Virtual Screening, Synthesis, and Bioassay. PLOS ONE. 2013. 8(9): e64547. DOI: 10.1371/journal.pone.0064547