Imam Siswanto, Muhammad Ikhlas Abdjan, Nanik Siti Aminah, Alfinda Novi Kristanti, Khusna Arif Rakhman, I Gusti Made Sanjaya, Muggundha Raoov Ramachandran, Yoshiaki Takaya
Computational studies were used to predict molecular interactions between active compounds and biological targets. This approach helps the pharmaceutical and food industries accelerate the drug discovery process and reduce the costs and risks of failure in clinical trials. A combination of computational chemistry techniques has been carried out, such as quantum mechanical modeling, molecular docking, quantitative structure-activity relationship-2 dimension (QSAR-2D), molecular dynamics simulations, and pharmacokinetic predictions to carry out drug designs for indole derivatives. The purpose of this study was to find indole candidates that have the potential to inhibit the indoleamine 2,3-dioxygenase-1 (IDO1) enzyme, which is responsible for the development of cancer cells. The QSAR-2D equation model shows better predictive strength through internal and external validations. Moreover, the screening results show that the proposed compounds 78 and 79 were selected by meeting the criteria for the candidate with the lowest grid score and predicted IC50. Molecular dynamics simulation was performed to refine the affinity energy calculations of the ligand-receptor. The results show free energy binding (∆Gbind) candidate (kcal/mol) < ∆Gbind reference (native ligand/XNL:-28.97 ± 0.25, C78:-32.88 ± 0.33, and C79:-35.31 ± 0.35). Furthermore, the pharmacokinetic properties of C78 and C79, such as drug-likeness, bioavailability, and ADMET (absorption, distribution, metabolism, excretion, and toxicity), showed promising results as criteria for a good drug. The results of this study are expected to provide systematic theoretical information for the efficiency of IDO1 enzyme inhibition in the future. Moreover, the efficiency and accuracy of the utilized strategy in this research make it an innovative strategy in the development of more effective, safe, and sustainable pharmaceutical and food products. ©The Author(s) 2025.
Department of Chemistry, Faculty of Science and Technology, Universitas Airlangga, Surabaya, 60286, Indonesia; Bioinformatic Laboratory, UCoE Research Center for Bio-Molecule Engineering, Universitas Airlangga, Surabaya, 60286, Indonesia; Department of Chemistry, Faculty of Mathematics and Natural Science, Universitas Negeri Surabaya, Surabaya, 60231, Indonesia; Biotechnology of Tropical Medicinal Plants Research Group, Universitas Airlangga, Surabaya, 60286, Indonesia; Department of Chemistry Education, Faculty of Teacher Training and Education, Universitas Khairun, Ternate, 55281, Indonesia; Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur, 50603, Malaysia; Department of Natural Product Chemistry, Faculty of Pharmacy, Meijo University, Nagoya, 468-8503, Japan
