Description:
Regression model with 7 QuBiLS-MIDAS descriptors used for the prediction of the Drug Potency (log(1/RD50)) in mg/cm2 to trigger repellent reaction of the mosquito Anopheles gambiae.
The training was performed with the Additive Regression meta classifier, using the IBk (with K-nearest neighbors = 10 and True cross-validation) algorithm in Weka 3.9.4 with 10-fold cross-validation. The 7 QuBiLS-MIDAS descriptors are namely:
V_F_AB_nCi_2_M5_SS1_C_KA_p_MID
TS[4]_K_Q_AB_nCi_2_M8_NS2_T_KA_e_MID
Q2_F_AB_nCi_2_M13_SS4_o_T_KA_e_MID
RA_F_AB_nCi_2_M15_MP6_T_KA_r_MID
Q2_Q_AB_nCi_2_M16_SS3_T_KA_e_MID
I50_B_AB_nCi_2_M16_SS3_T_KA_e-p_MID
CHOQUET[D;0.25;AO2;0.6]_F_AB_nCi_2_M13_SS11_T_KA_e_MID
Training set:
36 compounds extracted from Omolo et al., 2004 10.1016/j.phytochem.2004.08.035
Performance:
For a 10-fold cross-validation, the statistical parameters (performance without applicability domain) are R = 0.8196, MAE = 0.24, RMSE = 0.3381, RAE = 54.1378 %, and RRSE = 56.7436 %.
Classification Breakpoint:
The breakpoint is 3.41 mg/cm2. Values greater than the breakpoint will elicit a repellent response in mosquito Anopheles gambiae. Values lower or equal to the breakpoint represent certain actions occurring, however, these are not enough to activate a repellent reaction.
Reference:
Omolo et al. Repellency of essential oils of some Kenyan plants against Anopheles gambiae. Phytochemistry. 2004, 65(20), 2797-2802. DOI: 10.1016/j.phytochem.2004.08.035