Computational study on new natural compound inhibitors of indoleamine 2,3-dioxygenase 1

Abstract

Indoleamine 2,3-Dioxygenase (IDO), is a speed limiting enzyme that catalyzes the decomposition and metabolism of Tryptophan along Tryptophan-IDO-Kynurenine pathway [1]. Tryptophan is a necessary amino acid for activating cell growth and metabolism. Additionally, the insufficiency of Tryptophan can lead to immune system dysfunction. Raising the level of Indoleamine 2,3-Dioxygenase protein can promote stagnation and apoptosis of effector T cells [2]. In contrast, the decline in the number of effect T cells naturally protects cancer cells from attack. Therefore, Indoleamine 2,3-Dioxygenase is a potential target for tumour immunotherapy, such as melanoma, ovarian cancer, lung cancer, leukaemia, and so on, especially in solid tumours [3]. In the study, we have done sets of virtual screening aided by computer techniques in order to find potentially effective inhibitors of Indoleamine 2,3-Dioxygenase. Firstly, screening based on structure was carried out by Libdock. Then, ADME (adsorption, distribution, metabolism, excretion) and toxicity prediction were also analyzed. Molecular docking and 3D-QSAR pharmacophore generation were used to study the mechanism of these compounds and Indoleamine 2,3-Dioxygenase's binding. A molecular dynamic analysis was carried out to assess if these potential compound's binding is stable enough. According to the results of the analysis above, two potential compounds (ZINC000012495022 and ZINC000003791817) from the ZINC database were discovered to interact with Indoleamine 2,3-Dioxygenase with appropriate energy and proved to be none toxic. The study offered valuable information of Indoleamine 2,3-Dioxygenase inhibitor-based drug discovery in cancer therapy by increasing the activity of T cells and releasing immunity suppression [4, 5].

Identification of novel natural inhibitors targeting AKT Serine/Threonine Kinase 1 (AKT1) by computational study

“…To perform virtual screening, LibDock docked all the prepared ligands at the defined active site which was generated by using the ligands of AKT1 binding position. All candidate compounds were ranked according to the LibDock score [ 31–33 ].

Figure 1.

…”

Functionalized non-woven surfaces for combating the spread of the COVID-19 pandemic

“…Computational assessment of two separate formulations A and B (details given in §7.2) of phytochemicals to counter the bacterial and viral protein structures was performed using docking score-functioned LibDock algorithm [ 58 , 59 ]. The algorithm was functioned for docking ligands at active receptor location, supporting ligand configurations to polar and non-polar receptor interactions.…”

Computational study on new natural compound agonists of dopamine receptor

“…25932 molecules that are natural and purchasable were downloaded for free from the ZINC database. The database is established by Irwin and Shoichet Laboratories in the Department of Pharmaceutical Chemistry at the University of California, San Francisco [18]. Additionally, the 3D structure of DAR was regarded as target in this study.…”

“…The process was carried out on an NPT (atmospheric pressure and temperature) system. And temperature was set at a constant temperature of 300 K. We also used the PME (particle grid Ewald) algorithm to analyze remote static electricity, and adjusted the LINCS (Linear Constraint Solver) algorithm accordingly to make all hydrogen-related bonds fixed [18]. With reference to the initial settings, we performed the trajectory protocol steps in DS 4.5 to analyze the structural performance, RMSD and potential energy, and drew trajectory [18].…”

“…Finally, a Cell Counting Kit 8 (CCK8) assay and ELISA were performed to verify the effect of potential compounds. This study provided potential inhibitor's pharmacological properties, which will significantly promote the development of DAR agonistdrugs [18,19].…”