<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Aditya Sindu Sakti</style></author><author><style face="normal" font="default" size="100%">Agung Kristiyanto</style></author><author><style face="normal" font="default" size="100%">Riky Redmawati</style></author><author><style face="normal" font="default" size="100%">Abdul Mun’im</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effect of Gamma Irradiation on Some Pharmacological Properties and Microbial Activities of Melinjo (Gnetum gnemon Linn.) Seeds</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antioxidant</style></keyword><keyword><style  face="normal" font="default" size="100%">Dipeptidyl peptidase-4</style></keyword><keyword><style  face="normal" font="default" size="100%">Gamma irradiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Gnetum gnemon</style></keyword><keyword><style  face="normal" font="default" size="100%">HMG-CoA reductase</style></keyword><keyword><style  face="normal" font="default" size="100%">Resveratrol</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">January 2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">177-182</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt; Ionizing radiation, such as gamma irradiation, serves as a useful approach to inhibit spore germination and to control pathogens in postharvest seeds. Recently, its application on phytochemical sources and its influence on antioxidant activity of various phytochemical compounds has become an interesting topic to be explored.&lt;strong&gt; Objective:&lt;/strong&gt; The objectives of this study were to determine the effect of gamma irradiation as sterilization method on the resveratrol content and its antioxidant, HMG-CoA reductase inhibitory and dipeptidyl peptidase-4 (DPP-4) inhibitory activities of Melinjo (&lt;em&gt;Gnetum gnemon&lt;/em&gt;) seeds. &lt;strong&gt;Methods:&lt;/strong&gt; In this research, melinjo seeds were irradiated by 0.0; 2.5; 5.0; 7.5; and 10.0 kGy with gamma irradiation and then extracted with ethanol. The extracts were tested for resveratrol content with HPLC, antioxidant activities by DPPH assay, HMG-CoA inhibitory activity using HMG-CoA reductase assay kit and DPP-4 inhibitory activity using DPP-4 Inhibitor Screening Assay Kit. Gamma irradiation has effect on resveratrol content, antioxidant activity, HMG-CoA reductase inhibition and DPP-4 inhibitory activity. &lt;strong&gt;Results:&lt;/strong&gt; From the research, the highest value of resveratrol content is 0.18±0.004 mg/g seeds powder found in 5.0 kGy gamma irradiation treatment with IC50 94.64±0.236 μg/mL, while the highest HMG-CoA reductase inhibition is shown in 2.5 kGy irradiation dose. Melinjo seeds irradiated by 2.5 kGy gamma irradiation also shown a significant increase of DPP-4 inhibition activity. &lt;strong&gt;Conclusion:&lt;/strong&gt; This study suggests that 2.5-5 kGy radiation is the effective gamma irradiation dose to improve the quality of melinjo seeds.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">177</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p&gt;&lt;strong&gt;Rezi Riadhi Syahdi&lt;sup&gt;1&lt;/sup&gt;, Aditya Sindu Sakti&lt;sup&gt;2&lt;/sup&gt;, Agung Kristiyanto&lt;sup&gt;2&lt;/sup&gt;, Riky Redmawati&lt;sup&gt;2&lt;/sup&gt;, Abdul Mun’im&lt;sup&gt;3 &lt;/sup&gt;&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt;Departement of Medicinal Chemistry, Analysis and Biomedics Laboratory, Faculty of Pharmacy, Universitas INDONESIA.&lt;/p&gt;

&lt;p&gt;&lt;sup&gt;2&lt;/sup&gt;Drug Development Laboratory, Faculty of Pharmacy, Universitas INDONESIA.&lt;/p&gt;

&lt;p&gt;&lt;sup&gt;3&lt;/sup&gt;Departement of Pharmacognosy-Phytochemistry, Universitas INDONESIA.&lt;/p&gt;
</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Retno Prihatiningtyas</style></author><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Masteria Yunovilsa Putra</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Establishment of a 3D-structure Database for Chemical Compounds in Indonesian Sponges</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">2D-and 3D-chemical structures</style></keyword><keyword><style  face="normal" font="default" size="100%">3D-database of chemical structures</style></keyword><keyword><style  face="normal" font="default" size="100%">Evaluation of software packages</style></keyword><keyword><style  face="normal" font="default" size="100%">Indonesian sponges</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October 2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">1211-1218</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Nowadays, There hasn’t any three-dimensional (3D) chemical structure database yet for biologically active compound in sponges from Indonesian origin. Therefore, this study aimed to create &lt;em&gt;in silico&lt;/em&gt; a 3D-structure database of such compound and to evaluate the preferred software for this purpose. &lt;strong&gt;Methods:&lt;/strong&gt; 2D- structure of selected compounds was established using MarvinSketch software. Conversion from 2D- into 3D-structures was evaluated by comparing MarvinSketch, OpenBabel and VegaZZ software packages. Visualization of the respective 3D-structures was perfomed by using PyMOL software. From 68 scientific articles, 212 chemical compounds were selected from 53 Indonesian sponge species. &lt;strong&gt;Results: &lt;/strong&gt;The conversion of 2D-structures of the selected 212 chemical compound into 3D-structures lead to 7118 files, respectively consisting of 2508 files from the MarvinSketch, 1672 files from the OpenBabel and 1051 files from the VegaZZ software. The results based on the extention files were 1043 SDF, 1258 MOL and 2930 PDB format files of the three-dimensional structure. The valid and correct three-dimensional structure of chemical compound were 914 .sdf format files, 916 format .mol files and 72 .pdb format files. From the three-dimensional structures visualization, the database prefers established by using MarvinSketch with SDF or MOL format files since the results is consistent to literature and contain less number of errors.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">1211</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Retno Prihatiningtyas&lt;sup&gt;1&lt;/sup&gt;, Rezi Riadhi Syahdi&lt;sup&gt;1&lt;/sup&gt;, Masteria Yunovilsa Putra&lt;sup&gt;2&lt;/sup&gt;, Arry Yanuar&lt;sup&gt;1&lt;/sup&gt;,* &lt;/strong&gt;&lt;/p&gt;

&lt;p class=&quot;rtejustify&quot;&gt;&lt;sup&gt;1&lt;/sup&gt;Biomedical Computation and Drug Design Laboratory, Faculty of Pharmacy, Universitas Indonesia, Depok 16424, INDONESIA&lt;/p&gt;

&lt;p class=&quot;rtejustify&quot;&gt;&lt;sup&gt;2&lt;/sup&gt;Research Center for Oceanography, Indonesian Institute of Sciences, Jl. Pasir Putih I, Ancol Timur, Jakarta 14430, INDONESIA.&lt;/p&gt;
</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Jasmine Tiara Iqbal</style></author><author><style face="normal" font="default" size="100%">Abdul Munim</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">HerbalDB 2.0: Optimization of Construction of Three-Dimensional Chemical Compound Structures to Update Indonesian Medicinal Plant Database</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Herbal database</style></keyword><keyword><style  face="normal" font="default" size="100%">MarvinSketch</style></keyword><keyword><style  face="normal" font="default" size="100%">Three-dimensional structure</style></keyword><keyword><style  face="normal" font="default" size="100%">VegaZZ</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October 2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">1189-1194</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Development of novel drugs is an important challenge in the pharmaceutical world and industry. &lt;em&gt;In-silico &lt;/em&gt;methods are often considered in refinement / correction processes of drug design because they may lower the costs. The &lt;em&gt;in-silico&lt;/em&gt; drug discovery process requires a three- Dimensional Structure (3DS) of the chemical compounds as input. Computational 3DSs often exhibit structural mismatches thus affecting the validity of the &lt;em&gt;in-silico&lt;/em&gt; drug design process. In a previous study, a 3DS database with 1405 of Indonesian herbal compounds was developed, named HerbalDB. In this database, various structural mismatches were identified in some of the 3DSs. Our study aimed to identify and correct the structural mismatches in the herbalDB and to determine the best method in creating correct 3DS of chemical compounds. &lt;strong&gt;Methods: &lt;/strong&gt;Structural mismatches in the herbal database were identified by molecular visualization. &lt;strong&gt;Results:&lt;/strong&gt; The identification process yielded 170 compounds with structural mismatches that were corrected with 10 different parameters using the MarvinSketch and VegaZZ software, evaluated by molecular visualization. &lt;strong&gt;Conclusions:&lt;/strong&gt; based on 3DS of chemical compound visualization, *.mol and *.sdf file format created using Dreiding force fields of MarvinSketch are the best method to construct the proper structure of Indonesian medicinal plant’s chemical compound database compared with MMFF94, AMBER and CHARMM forcefields.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">1189</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Rezi Riadhi Syahdi&lt;sup&gt;1&lt;/sup&gt;, Jasmine Tiara Iqbal&lt;sup&gt;1&lt;/sup&gt;, Abdul Munim&lt;sup&gt;1&lt;/sup&gt;, Arry Yanuar&lt;sup&gt;1&lt;/sup&gt;*&lt;/strong&gt;&lt;/p&gt;

&lt;p class=&quot;rtejustify&quot;&gt;&lt;sup&gt;1&lt;/sup&gt;Faculty of Pharmacy, Universitas Indonesia, Depok, 16424 West Java, INDONESIA.&lt;/p&gt;
</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stefandi J Wijaya</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author><author><style face="normal" font="default" size="100%">Rosita Handayani</style></author><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">In silico Analysis of Flavonoid Glycosides and its Aglycones as Reverse Transcriptase Inhibitor</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Flavonoid</style></keyword><keyword><style  face="normal" font="default" size="100%">Glycosides</style></keyword><keyword><style  face="normal" font="default" size="100%">HIV</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular docking</style></keyword><keyword><style  face="normal" font="default" size="100%">Reverse transcriptase</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October 2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">1252-1255</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Background:&lt;/strong&gt; HIV continues to be a major global public health issue, having claimed more than 35 million lives so far. In 2016, 1 million people died from HIV-related causes globally. HIV-1 reverse transcriptase is one of HIV’s vital enzymes for virus reproduction. If the enzyme is inhibited, the virus multiplication could be significantly decreased. There are currently many treatments for HIV, but more effective treatment is always needed because of the possibility of drug resistance and side effects for long-term use. Based on the previous study, there are some natural compounds with high affinity to the HIV-1 reverse transcriptase enzyme. Some of these compounds are flavonoid glycosides. &lt;strong&gt;Aims and Method:&lt;/strong&gt; This study was aimed to learn more about &lt;em&gt;in silico&lt;/em&gt; HIV-1 reverse transcriptase inhibitory activities of flavonoid glycosides using docking method. &lt;strong&gt;Results:&lt;/strong&gt; The results showed that the most recommended flavonoid glycosides are those with the lowest binding energy, which were kaempferol-3-O-rhamnoside, myricetin-3-O-rhamnoside and quercetin-3-O-rhamnoside. This was due to the interactions of all three flavonoid rings and sugar moiety with key amino acid residues, which were Leu100, Lys101, Glu138, Tyr181, His235 and Tyr318. &lt;strong&gt;Conclusion: &lt;/strong&gt;Flavonoid glycosides with rhamnose as glycone showed lower binding energy on HIV-1 reverse transcriptase.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">1252</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Stefandi J Wijaya, Arry Yanuar, Rosita Handayani, Rezi Riadhi Syahdi* &lt;/strong&gt;&lt;/p&gt;

&lt;p class=&quot;rtejustify&quot;&gt;Faculty of Pharmacy, Universitas Indonesia, Depok, 16424, INDONESIA.&lt;/p&gt;
</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Chindy Dwi Martinah</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Screening of Indonesian Herbal Database as alpha-Amino-3- Hydroxy-5-Methyl-4 Isoxazolepropionic Acid (AMPA) Antagonist</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">AMPA receptor</style></keyword><keyword><style  face="normal" font="default" size="100%">AutoDock</style></keyword><keyword><style  face="normal" font="default" size="100%">Herbal plants</style></keyword><keyword><style  face="normal" font="default" size="100%">Neuroprotective</style></keyword><keyword><style  face="normal" font="default" size="100%">Virtual Screening</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October 2019</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">1204-1210</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Objective:&lt;/strong&gt; 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. &lt;strong&gt;Methods:&lt;/strong&gt; 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’s Rule of Five was used to filter the screening result. &lt;strong&gt;Results:&lt;/strong&gt; 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. &lt;strong&gt;Conclusion:&lt;/strong&gt; Five compounds of the Indonesia herbal database were shown as hits of AMPA receptor antagonist based on the docking method.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">1204</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Rezi Riadhi Syahdi, Chindy Dwi Martinah, Arry Yanuar* &lt;/strong&gt;&lt;/p&gt;

&lt;p class=&quot;rtejustify&quot;&gt;Biomedical Computation and Drug Design Laboratory, Faculty of Pharmacy, Universitas Indonesia, Depok, INDONESIA.&lt;/p&gt;
</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Ayu Annissa</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Screening of Indonesian Herbal Database for Discovery of Procaspase-3 Activators Using Autodock and Autodock Vina</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Apoptotic</style></keyword><keyword><style  face="normal" font="default" size="100%">Cancer</style></keyword><keyword><style  face="normal" font="default" size="100%">Herbal</style></keyword><keyword><style  face="normal" font="default" size="100%">Procaspase-3 activator</style></keyword><keyword><style  face="normal" font="default" size="100%">Virtual Screening</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">xx</style></volume><pages><style face="normal" font="default" size="100%">xx-xx</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;&lt;strong&gt;Objective:&lt;/strong&gt; 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. &lt;strong&gt;Methods:&lt;/strong&gt; 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. &lt;strong&gt;Results:&lt;/strong&gt; 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.&lt;strong&gt; Conclusion:&lt;/strong&gt; 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.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">xx</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">xx</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p&gt;&lt;strong&gt;Rezi Riadhi Syahdi, Ayu Annissa, Arry Yanuar&lt;sup&gt;* &lt;/sup&gt;&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;Faculty of Pharmacy, Universitas Indonesia, Depok 16424, West Java, INDONESIA.&lt;/p&gt;
</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rezwendy R</style></author><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Indonesian Herbal SGLT2 Inhibitor Discovery through Pharmacophore-Based Virtual Screening</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Diabetes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pharmacophore</style></keyword><keyword><style  face="normal" font="default" size="100%">SGLT2 Inhibitor</style></keyword><keyword><style  face="normal" font="default" size="100%">Virtual Screening</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June 2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://fulltxt.org/article/674</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">803-807</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align: justify;&quot;&gt;&lt;strong&gt;Objective:&lt;/strong&gt; 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. &lt;strong&gt;Methods:&lt;/strong&gt; 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. &lt;strong&gt;Results:&lt;/strong&gt; 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. &lt;strong&gt;Conclusion:&lt;/strong&gt; These results showed that vitexin, cucumerin A, and cucumerin B potentially have activity as an SGLT2 inhibitor.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">803</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align: justify;&quot;&gt;&lt;strong&gt;Rezwendy, Rezi Riadhi Syahdi, Arry Yanuar* &lt;/strong&gt;&lt;/p&gt;
&lt;p style=&quot;text-align: justify;&quot;&gt;Faculty of Pharmacy, Universitas Indonesia, Kampus UI, Depok, 16424, INDONESIA.&lt;/p&gt;</style></auth-address></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alexander Victory</style></author><author><style face="normal" font="default" size="100%">Rezi Riadhi Syahdi</style></author><author><style face="normal" font="default" size="100%">Arry Yanuar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Virtual Screening of Indonesian Herbal Database as Murine Double Minute-2 (MDM2) Inhibitor</style></title><secondary-title><style face="normal" font="default" size="100%">Pharmacognosy Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cancer</style></keyword><keyword><style  face="normal" font="default" size="100%">Docking</style></keyword><keyword><style  face="normal" font="default" size="100%">Indonesian Herbal</style></keyword><keyword><style  face="normal" font="default" size="100%">Inhibitor</style></keyword><keyword><style  face="normal" font="default" size="100%">MDM2</style></keyword><keyword><style  face="normal" font="default" size="100%">Virtual Screening</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August 2018</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">1184-1189</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align: justify;&quot;&gt;&lt;strong&gt;Background:&lt;/strong&gt; 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. &lt;strong&gt;Methods:&lt;/strong&gt; 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. &lt;strong&gt;Results:&lt;/strong&gt; 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 (&amp;Delta;G) 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 (&amp;Delta;G) ranging from -8.7 to -9.4 kcal/mol. &lt;strong&gt;Conclusion:&lt;/strong&gt; Jacoumaric acid and Leucadenone C were shown to interact with the active site in MDM2 at residues Leu54, Ile61, Met62, and Ile99.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Original Article</style></work-type><section><style face="normal" font="default" size="100%">1184</style></section><auth-address><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align: justify;&quot;&gt;&lt;strong&gt;Alexander Victory, Rezi Riadhi Syahdi, Arry Yanuar*&lt;/strong&gt;&lt;/p&gt;
&lt;p style=&quot;text-align: justify;&quot;&gt;Faculty of Pharmacy, Universitas Indonesia, 16424, Depok, INDONESIA.&lt;/p&gt;</style></auth-address></record></records></xml>