3D-PHARMACOPHORE MODELING AND MOLECULAR DOCKING TO STUDY THE POTENTIAL ANTI-CANCER AGENT FROM Ficus septica

In vitro testing showed that awar awar ( Ficus septica Burm. L ) leaf had an anticancer activity. Ethanol extract from awar-awar leaves could selectively inhibit cancer cell growth with IC 50 values, there were MCF7 breast cancer cells (48 µg/ml), HeLa cervical cancer cells (122.4 µg/mL), and WiDR cancer cells (75.9 µg/mL). However, the active compounds that play a role in inhibiting the three cancer cells are not yet found. Therefore, this research carried out to find out the active compound using in silico. 3D-pharmacophore modeling and Molecular docking were developed for finding out the potential compound that could be acted as an anti-cancer agent. Screening pharmacophore was performed using LigandScout® 4.4 software for searching the matching pharmacophore features against chemical structure databases. Docking was performed using Autodock Tools ® and visualized using Discovery Studio Visualizer® software to see the ligand interaction with the active binding site at the receptor and continue with ADMET properties to evaluating the Pharmacodynamic activities of the Hit compounds. Among 17 types of compounds tested, 11 compounds showed anticancer activity and genistin was found promising and showed potential inhibitory characteristics as an anticancer compared to other active compounds of awar-awar leaves. This study suggests that these compound could be used as a lead compound for anticancer agents.


INTRODUCTION
Cancer is one of the leading causes of death in the world. In 2018, approximately 9.6 million deaths were caused by cancer (WHO, 2019). Of the many cases of death caused by this cancer, commonly used cancer treatments such as surgery, chemotherapy, and radiation therapy emerged (National Cancer Institute, 2021). The treatment aims to destroy cancer cells. However, these methods are not optimal and even give side effects.
The results of in vitro studies that have been carried out are proven that awarawar leaves had anticancer activity.
However, the active compounds that play a role in inhibiting the three cancer cells are not certain. Therefore, further research carried out in silico to search potential compounds that can be used as lead compound. Molecular docking and 3Dpharmacophore modeling were established to search for the potential compound as an anti-cancer agent from this plant.
The biological activity of a compound can be explored with a computational approach by looking at the affinity of small molecular ligands to macromolecular receptors. It can be explored using the in silico method and compared with experimental methods. The molecular docking approach can describe the interactions that occur between small molecules (ligands) and proteins at the atomic level (Agarwal & Mehrotra, 2016), (Meng et al., 2011).

Ligan Preparation
Ligands or compounds were redrawn using the ChemDraw ® Ultra 12.0 program and the energy minimization using the Chem3D ® Pro 12.0 program and then saved in the .pdb format.
After preparation, the physicochemical properties of the compounds were determined based on Lipinski's Rule of Five.

Validation
Method validation was done to find out whether the program for molecular docking is according to the requirements or not. Validation of the molecular docking method was done by redocking between the default ligands from the target receptor using Autodock Tools ® software.
The analysis used to evaluate the results of validation is the RMSD value, the binding site found and the parameters used are considered valid if the RMSD value is ≤ 2Å.

Grid Preparation
The grid of the selected target structure was prepared by using Autodock Tools ® .

Docking
After all the docking settings are complete then running can be done using

ADMET profiling analysis
The ADMET property analysis is extremely significant for evaluating the Pharmacodynamic activities of the Hit compounds. Tests carried out include absorption and distribution as well as toxicity tests which include mutagenic and carcinogenic properties of compounds. Tests are carried out using a special program that is carried out using a special program conducted online on the site http://preadme.bmdrc.kr/.

Toxicity Prediction
Toxicity prediction is done to predict the toxicity level of a compound in the body.
Toxicity prediction was carried out using the

Drug-likeliness property analysis
A drug like features (Lipinski's rule of five) of the selected best Hits was confirmed using Drug-likeliness property analysis. A good drug contains properties such as well distribution throughout the system, absorbed in the timeline as well as shows good metabolism property (Kalyaanamoorthy & Chen, 2011). Table 3 shows The test results showed that all test compounds meet the requirements of Lipinski's rule of five.