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This study aimed to propose new indole derivatives as anticancer through Quantitative Structure-Activity Relationship (QSAR) and molecular docking method. The best predicted anticancer activity of indole derivatives was recommended based on the QSAR equation. A data set consist of 18 indole derivatives from literature with anticancer activity against the A498 cell line was used to generate a QSAR model equation. The data set was divided randomly into training (14) and test (4) set compounds. The structure of indole compound was optimized first using AM1 semi-empirical methods, and the descriptors involved were analyzed using Multiple Linear Regression (MLR). The best QSAR equation obtained was Log IC 50  = 65.596 (qC2) + 366.764 (qC6)  –  92.742 (qC11) + 503.297 (HOMO)  –  492.550 (LUMO)  –  76.966. Based on the QSAR model, varying electron-withdrawing groups in C2 and C6 atom, as well as adding electron-donating groups in C11 were proposed could increase the anticancer activity of the indole derivatives. The QSAR analysis showed that compound 15 has the best predicted anticancer activity, supported by molecular docking results that showed hydrogen bond interaction with essential amino acids to build anticancer activity such as MET769, THR830, and THR766 residues.

molekul

Design of New 2,4-Substituted Furo [3,2-B] Indole Derivatives as Anticancer Compounds Using Quantitative Structure-Activity Relationship (QSAR) and Molecular Docking