Description:
Regression model with 6 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 6 QuBiLS-MIDAS descriptors are namely:

IB_S_Q_AB_nCi_2_M1_SS1_o_T_LGL[1-2]_m_MID
S_B_AB_nCi_2_M8_SS7_T_LGL[2-3]_m-h_MID
AC[2]_S_Q_AB_nCi_2_M8_SS6_o_T_LGL[1-2]_m_MID
I50_B_AB_nCi_2_M16_SS3_T_KA_e-p_MID
V_F_AB_nCi_2_M5_SS1_C_KA_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 = 0.8608, MAE = 0.2116, RMSE = 0.2993, RAE = 47.7345 %, and RRSE = 50.2343 %.

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