@article {999, title = {Virtual Screening of Indonesian Herbal Database as Adenosine A2A Antagonist using AutoDock and AutoDock Vina}, journal = {Pharmacognosy Journal}, volume = {11}, year = {2019}, month = {October 2019}, pages = {1219-1224}, type = {Original Article}, chapter = {1219}, abstract = {

Objective: Previous research found that Adenosine A2A antagonist allows to reduce motor fluctuations, dyskinesia, protect from neurodegenerative disorder in Parkinson{\textquoteright}s disease in the human brain which is chronic progressive of losing dopaminergic neurons. The aim of this study is to explore Indonesian herbal compounds as Adenosine A2A inhibitor using virtual screening method. Methods: In this study, virtual screening of Indonesian herbal database as Adenosine A2A inhibitor was done by AutoDock and AutoDock Vina and was validated by database from A Directory of Useful Decoys: Enhanced (DUD-E). The method was validated by Enrichment Factor (EF) and Area Under Curve (AUC) of Receiver Operating Characteristics (ROC) curve Results: Based on the validation results, grid box that was used in virtual screening using AutoDock is 60 {\texttimes} 60 {\texttimes} 60 with EF1\% 16.5869 and AUC 0.8406. The two compounds Chitranone and 3-O-Methylcalopocarpin with binding energy -10.19 and -9.55 kcal/mol, respectively showing interaction with Adenosine A2A active site at residues ALA63, ILE66, ALA81, LEU85, PHE168, GLU169, MET177, TRP246, LEU249, ASN253 and ILE274. Conclusions:\ This study concludes that Chitranone and 3-O-Methylcalopocarpin could be proposed to be developed as Adenosine A2A antagonists.

}, keywords = {Adenosine A2A antagonist, AutoDock, Autodock vina, Indonesian herbal database, Parkinson{\textquoteright}s disease, Virtual Screening}, doi = {10.5530/pj.2019.11.189}, author = {Nabilah Nurtika Salamah and Widya Dwi Aryati and Arry Yanuar} } @article {998, title = {Virtual Screening of Indonesian Herbal Database as alpha-Amino-3- Hydroxy-5-Methyl-4 Isoxazolepropionic Acid (AMPA) Antagonist}, journal = {Pharmacognosy Journal}, volume = {11}, year = {2019}, month = {October 2019}, pages = {1204-1210}, type = {Original Article}, chapter = {1204}, abstract = {

Objective: Ischemic stroke is one type of circulatory disturbance caused by blood clots that block blood flow to the brain. One of the impact of ischemia is nerve cell damage due to excitotoxicity. Inhibition of the ionotropic glutamate receptor such as the AMPA receptor, becomes an essential approach to the treatment of ischemia. This study aims to explore the possibility of an Indonesian herbal compound as an AMPA receptor antagonist. Methods: In this study, virtual screening of 2233 herbal compounds was performed by docking method using AutoDock to find the antagonist candidate of AMPA receptor from Indonesian herbal database. The virtual screening method was validated by an area under curve (AUC) of the ROC curve and enrichment factor (EF). Lipinski{\textquoteright}s Rule of Five was used to filter the screening result. Results: The validation of virtual screening result showed that AUC was 0.9385 and EF 1\% was 23.5550. The screening result of Indonesian herbal database showed top five compound sanggenol O, blazeispirol X, progesterone, nimolicinol and boeravinone F (-8.51; -8.39; -8.19; -8.17; -8.08 kcal/mol, respectively) and have interaction with TYR61 and THR91 residues of AMPA receptor. Conclusion: Five compounds of the Indonesia herbal database were shown as hits of AMPA receptor antagonist based on the docking method.

}, keywords = {AMPA receptor, AutoDock, Herbal plants, Neuroprotective, Virtual Screening}, doi = {10.5530/pj.2019.11.187}, author = {Rezi Riadhi Syahdi and Chindy Dwi Martinah and Arry Yanuar} } @article {839, title = {Virtual Screening of Indonesian Herbal Database for Discovery of Procaspase-3 Activators Using Autodock and Autodock Vina}, journal = {Pharmacognosy Journal}, year = {2019}, pages = {xx-xx}, type = {Original Article}, chapter = {xx}, abstract = {

Objective: Cancer is a disease where body cell grows abnormal, spread to every part of human body. Previous studies have found excessive expression of Procaspase-3 on cancer that must be activated to Caspase-3 to induce apoptotic in cells. Methods: Virtual screening of Indonesian Herbal Database was carried out to discover Procaspase-3 activators. This study was validated using enrichment factor (EF), receiver operating characteristics (ROC) area under curve (AUC) parameters. Among 1412 compounds were screened using Autodock and Autodock Vina software. Results: The virtual screening results using Autodock obtained the best ten compounds with binding energy -8.28 ~ -9.31 kcal/mol and Autodock Vina obtained the best ten compounds with binding energy -8.1 ~ -8.8 kcal/mol. Both virtual screening software showed two compounds in common, i.e., betulinic acid and maslinic acid. Conclusion: Betulinic acid interacts with Leu136A, Lys137A, Tyr195A and Pro201 residues in Autodock and Autodock Vina. While maslinic acid interacts with Leu136A, Lys137A and Pro201 residues in Autodock and Autodock Vina

}, keywords = {Apoptotic, Cancer, Herbal, Procaspase-3 activator, Virtual Screening}, doi = {10.5530/pj.2017.4.x}, author = {Rezi Riadhi Syahdi, and Ayu Annissa and Arry Yanuar} } @article {871, title = {Virtual Screening of Indonesian Herbal Database for Discovery of Procaspase-3 Activators Using Autodock and Autodock Vina}, journal = {Pharmacognosy Journal}, volume = {xx}, year = {2019}, pages = {xx-xx}, type = {Original Article}, chapter = {xx}, abstract = {

Objective: Cancer is a disease where body cell grows abnormal, spread to every part of human body. Previous studies have found excessive expression of Procaspase-3 on cancer that must be activated to Caspase-3 to induce apoptotic in cells. Methods: Virtual screening of Indonesian Herbal Database was carried out to discover Procaspase-3 activators. This study was validated using enrichment factor (EF), receiver operating characteristics (ROC) area under curve (AUC) parameters. Among 1412 compounds were screened using Autodock and Autodock Vina software. Results: The virtual screening results using Autodock obtained the best ten compounds with binding energy -8.28 ~ -9.31 kcal/mol and Autodock Vina obtained the best ten compounds with binding energy -8.1 ~ -8.8 kcal/mol. Both virtual screening software showed two compounds in common, i.e., betulinic acid and maslinic acid. Conclusion: Betulinic acid interacts with Leu136A, Lys137A, Tyr195A and Pro201 residues in Autodock and Autodock Vina. While maslinic acid interacts with Leu136A, Lys137A and Pro201 residues in Autodock and Autodock Vina.

}, keywords = {Apoptotic, Cancer, Herbal, Procaspase-3 activator, Virtual Screening}, doi = {10.5530/pj.2019.11xx}, author = {Rezi Riadhi Syahdi and Ayu Annissa and Arry Yanuar} } @article {640, title = {Indonesian Herbal SGLT2 Inhibitor Discovery through Pharmacophore-Based Virtual Screening}, journal = {Pharmacognosy Journal}, volume = {10}, year = {2018}, month = {June 2018}, pages = {803-807}, type = {Original Article}, chapter = {803}, abstract = {

Objective: Sodium-glucose cotransporter 2 (SGLT2) inhibitor had been evaluated in clinical trials as the basic strategy of hyperglycemia handling in diabetes. However, because of SGLT2 inhibitors is the new class of oral antidiabetic, it is rare to be found in Indonesia, and it is costly. This study was intended to find compounds from Indonesian herbal database that show capability to be used as SGLT2 inhibitors through a pharmacophore-based virtual screening approach. Methods: The SGLT2 inhibitor pharmacophore models were made from 10 training sets of SGLT2 ligand inhibitors using the Ligand Scout 4.1.5. Ten pharmacophore models which had been made were validated using test set and decoy set methods to know how the performance of pharmacophore model worked. Virtual screening were then applied to the best pharmacophore model. Results: The model-1 pharmacophore was the best model, with values of 0.9080, EF1\% = 56.5, EF5\% = 56.5 and AUC100\% = 0.87 which served as model for virtual screening. Model-1 consisted of one hydrophobic interaction, one aromatic ring, four hydrogen bond donors and five hydrogen bond acceptors. Virtual screening showed three compounds (Hits) with best pharmacophore fit scores according to model-1 among 1377 compounds, they were vitexin = 113.62; cucumerin A = 112.62; and cucumerin B = 113.51. Conclusion: These results showed that vitexin, cucumerin A, and cucumerin B potentially have activity as an SGLT2 inhibitor.

}, keywords = {Diabetes, Pharmacophore, SGLT2 Inhibitor, Virtual Screening}, doi = {10.5530/pj.2018.4.136}, url = {http://fulltxt.org/article/674}, author = {Rezwendy R and Rezi Riadhi Syahdi and Arry Yanuar} } @article {738, title = {Virtual Screening of Indonesian Herbal Database as Murine Double Minute-2 (MDM2) Inhibitor}, journal = {Pharmacognosy Journal}, volume = {10}, year = {2018}, month = {August 2018}, pages = {1184-1189}, type = {Original Article}, chapter = {1184}, abstract = {

Background: Murine Double Minute-2 (MDM2) overexpression causes the p53 deficiency, so the role p53 as a cell regulator does not work in the case of cancer. Methods: In this study, virtual screening of Indonesian herbal database to discover MDM2 inhibitors was carried out. Autodock and Autodock Vina validated with Directory of Useful Decoy-Enhanced (DUD-E). Validation parameters were performed with Enrichment Factor, Receiver Operating Characteristics, and Area Under Curve. Results: The validation with the grid box 70x70x70 on Autodock resulting AUC value 0.72, while in Autodock Vina 0.43. Autodock Vina did not fulfilll the standard value but still used for comparison. Based on the virtual screening result, top ten compounds from Autodock are Nimolicinol, Jacoumaric acid, Isoarborinol, Lantic acid, Diosgenin, Theasaponin E1, Taraxasterol, Leucadenone C, Simiarenol, and Alpha-Amyrin were found to have strong interaction with MDM2, with binding energy (\ΔG) ranging from -8.83 to -9.65 kcal/mol. The Autodock Vina screening resulted in the identification of Yuehchukene, Morusin, Cyanidin, Leucadenone C, Roxburghine-B, Ocidentoside, Beta-sitosterol, Curine, Withangulatin, and Jacoumaric acid as potential inhibitors with binding energy (\ΔG) ranging from -8.7 to -9.4 kcal/mol. Conclusion: Jacoumaric acid and Leucadenone C were shown to interact with the active site in MDM2 at residues Leu54, Ile61, Met62, and Ile99.

}, keywords = {Cancer, Docking, Indonesian Herbal, Inhibitor, MDM2, Virtual Screening}, doi = {10.5530/pj.2018.6.203}, author = {Alexander Victory and Rezi Riadhi Syahdi and Arry Yanuar} }