In silico analysis of phytochemical compounds in ethyl acetate fraction of semanggi (Marsilea crenata Presl.) leaves as neuroprotective agent

2020 ◽  
Vol 13 (8) ◽  
pp. 3745
Author(s):  
Mangestuti Agil ◽  
Hening Laswati ◽  
Hadi Kuncoro ◽  
Burhan Ma'arif
Author(s):  
Diniatik Diniatik ◽  
Suwijiyo Pramono ◽  
Sugeng Riyanto

Objective: The research was conducted by in silico analysis of xanthine oxidase inhibitors of volatile compounds from ethyl acetate fraction of ethanolic extract of Stelechocarpus burahol (Bl.) Hook f. and Th. leaves. The objective of the research was to determine the active compounds as a potential inhibitor of xanthine oxidase by using in silico screening method.Methods: The research was conducted using volatile compounds that were obtained by using gas chromatography of ethyl acetate fraction of ethanolic extract of S. burahol leaves and models of xanthine oxidase inhibitor downloaded via Protein Data Bank (PDB) with code 3BDJ, then performed docking process using the PyRx program, and then evaluated of the free energy (ΔG) as docking process results.Results: Volatile compounds in the ethyl acetate fraction of ethanolic extract were 3 heptene, 2,2,4,6,6-pentamethyl (2.15%),  methyl hexadecanoate (4.16%), ethyl tridecanoate (34.63%), methyl octadecanoate (7.26%), ethyl hexadecanoate (51.8%). The result showed that three of the chemical compounds have the lower free energy value as xanthine oxidase inhibitors than oxypurinol.Conclusion: They were ethyl tridecanoate, methyl octadecanoate, ethyl hexadecanoate with free energy (ΔG) -10.7, -7.6, -7.1 kcal / mol.Keywords: Stelechocarpus burahol (Bl.) Hook f. and Th., xanthine oxsidase, in silico analysis.


2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.


2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas

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