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 SMOreg (with Pearson Universal Kernel - PUK) algorithm in Weka 3.9.4 with 10-fold cross-validation. The 6 QuBiLS-MIDAS descriptors are namely:

AC[5]_S_Q_AB_nCi_2_M16_MP5_T_LGL[1-2]_c_MID
AC[2]_S_Q_AB_nCi_2_M8_SS6_o_T_LGL[1-2]_m_MID
ES_S_F_AB_nCi_2_M3_SS5_C_LGL[2-3]_c_MID
S_B_AB_nCi_2_M8_SS7_T_LGL[2-3]_m-h_MID
AC[1]_S_F_AB_nCi_2_M13_MP1_T_LGP[1]_s_MID
Q3_B_AB_nCi_2_M11_SS3_o_T_LGL[2-3]_a-s_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 = 0.8646, MAE = 0.2148, RMSE = 0.3058, RAE = 48.4503 %, and RRSE = 51.3137 %.

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