@article {1904, title = {In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates}, journal = {Pharmacognosy Journal}, volume = {14}, year = {2022}, month = {December 2022}, pages = {736-743}, type = {Original Article}, chapter = {736}, abstract = {

Background: One of the causes of death is diabetes. Anti-diabetic drugs currently available do not work optimally because some have been reported to have side effect and resistance. Objective: This study aimed to flavonoid compounds from Syzygium cumini var. album with the greatest anti-diabetic activity and lower toxicity than acarbose. Materials and Methods: This research is an in silico study of nine flavonoid compounds from Syzygium cumini var. album, starting with PASS online was used to predict the activity spectrum of substances, drug-likeness prediction using DruLiTo, ADMET prediction (absorption, distribution, metabolism, excretion, and toxicity) using pkCSM online. Molecular docking was carried out by the AutoDock 4.2.6 program on α-glucosidase targeting. Visualization is done with the Discovery Studio Visualizer software. Results: From the data obtained, D-(+)-Catechin has a high affinity for α-glucosidase with a free energy of binding (ΔG) -5.94 kcal/mol and an inhibition constant (Ki) of 44270 nm. Conclusion: Based on the results of the study, it can be concluded that the flavonoid compounds from Syzygium cumini var. album has the potential as a promising anti-diabetic drug candidate, where the best candidate is D- (+)-Catechin. However, further studies of flavonoid compounds from Syzygium cumini var. album are needed.

}, keywords = {Flavonoid., Molecular docking, PASS, Pharmacokinetics, α-glucosidase}, doi = {10.5530/pj.2022.14.161}, author = {Yanu Andhiarto and Suciati and Ersanda Nurma Praditapuspa and Sukardiman} } @article {1643, title = {In Silico Analysis of Pinostrobin Derivatives from Boesenbergia pandurata on ErbB4 Kinase Target and QSPR Linear Models to Predict Drug Clearance for Searching Anti-Breast Cancer Drug Candidates}, journal = {Pharmacognosy Journal}, volume = {13}, year = {2021}, month = {September 2021}, pages = {1143-1149}, type = {Original Article}, chapter = {1143}, abstract = {

Background: ErbB4 is a member of ErbB family of receptor tyrosine kinases (RTKs) and plays an important role in resistance to ErbB2 inhibitors. Objective: This study aimed to design a pinostrobin derivative with activity as an ErbB4 inhibitor and to establish a quantitative structure-property relationship (QSPR) of pinostrobin and its derivatives to predict drug clearance. Materials and Methods: In this research, an in silico study was conducted on pinostrobin and its derivatives by predicting the prediction of activity spectra for substances (PASS) with PASS online, followed by molecular docking using the AutoDockTools 4.2.6 program on ErbB4 protein kinase and visualizing the docking results using the Discovery Studio Visualizer software. While the study of QSPR pinostrobin and its derivatives was determined using physicochemical parameters with clearance (CLtot) using SPSS. Results: From the data obtained, 5-O-2- phenylacetylpinostrobin has a high affinity for ErbB4 protein with a free energy of binding (ΔG) -10.37 kcal/mol and an inhibition constant (Ki) of 26.06 nM. Conclusion: Probability {\textquotedblleft}to be active{\textquotedblright} (Pa) 5-O-2- phenylacetylpinostrobin of 0.595 for kinase inhibitors and 0.666 for apoptosis agonists, thus becoming candidates for breast cancer drugs. The QSPR model can be used to predict the properties of molecules such as CLtot, this will be useful in the drug design process. The best QSPR regression equation for pinostrobin and its derivatives is Log (1/CLtot) = 0.705 Log S + 0.035 MR + 0.375. This equation can be used as a reference in predicting CLtot.

}, keywords = {5-O-acylpinostrobin, Molecular docking, PASS, Pharmacokinetic, Physicochemical properties}, doi = {10.5530/pj.2021.13.147}, author = {Ersanda Nurma Praditapuspa and Siswandono and Tri Widiandani} }