| Autor: |
Octa RISWANTO, Florentinus Dika, Wira WASKITHA, Stephanus Satria, Surya YANUAR, Michael Resta, ISTYASTONO, Enade Perdana |
| Předmět: |
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| Zdroj: |
Journal of Research in Pharmacy; 2024, Vol. 28 Issue 4, p1099-1106, 8p |
| Abstrakt: |
Acetylcholinesterase (AChE) inhibitors have been used to delay the dementia progression in Alzheimer’s Disease (AD). In 2017, a structure-based virtual screening (SBVS) protocol was made publicly available and successfully employed to discover chalcone derivatives and short peptides as AChE inhibitors. During the upgrading process of the SBVS protocol, an optimized version of the enhanced directory of useful decoys (DUDE) was released. This optimized DUDE was named DUDE-Z. In this article, the re-optimization of the upgraded SBVS protocol is presented. The optimization process made use of a machine learning package and library called recursive partitioning and regression tree (RPART) in R statistical computing software environment. The optimized SBVS protocol has the F-measure value of 0.322 against the DUDE-Z. The protocol was subsequently analyzed to efficiently screen on a newly released open-accessed natural products database LOTUS (https://lotus.naturalproducts.net/) to discover bioactive natural products as AChE inhibitors. The SBVS campaigns on 276,518 natural products identified 867 compounds as virtual hits, thirty-seven of which were identified as compounds found in the species from Kingdom Plantae. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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