@article {1764, title = {Molecular Docking, Physicochemical and Drug-likeness Properties of Isolated Compounds from Garcinia latissima Miq. on Elastase Enzyme: In Silico Analysis}, journal = {Pharmacognosy Journal}, volume = {14}, year = {2022}, month = {April 2022}, pages = {282-288}, type = {Original Article}, chapter = {282}, abstract = {

Garcinia latissima Miq. belongs to the Clusiaceae family that has been studied with activity as an antibacterial and anti-elastase in vitro. The inhibitory ability of the elastase enzyme from the G. latissima extract. This needs to be tested further by an in silico molecular docking study of the compound. Previous studies have shown that 4-oxo-β-lactam crystals are selective against the human neutrophil elastase (an enzyme protease). It has a structural relationship with its activity to become the basis for inhibiting the elastase enzyme. The purpose of this in silico study was to test whether the isolated compounds from G. latissima (including friedelin, 6-deoxyjacareubin, amentoflavone, and Robusta flavone). The in silico molecular docking method used was Autodock 4.2.6 molecular docking software. This protocol is used to test friedelin, 6-deoxyjacareubin, amentoflavone, and Robusta flavone as ligands for the elastase enzyme receptor. The protocol{\textquoteright}s output was analyzed using the Accelrys Discovery Studio Visualizer 4.0 post-docking analysis method. The results showed that isolated compounds, including amentoflavone, friedelin, and 6-deoxyjacareubin, are active ligands against porcine pancreatic elastase with the free binding energy of -10.94, -7.17, and -6.72 kcal/mol, respectively, and form hydrogen bonds, van der Walls, alkyl, electrostatic, and hydrophobic interaction. In silico physicochemical, lipophilicity, water-soluble, pharmacokinetics, and drug-likeness properties prediction showed characteristics prediction of isolated compound. This study provides an overview of the molecular interactions of isolates compounds from G. latissima against the elastase enzyme.

}, keywords = {Drug likeness, Elastase enzyme, Garcinia latissima Miq., Molecular docking study, Physicochemical properties}, doi = {10.5530/pj.2022.14.35}, author = {Neneng Siti Silfi Ambarwati and Azminah Azminah and Islamudin Ahmad} } @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} }