Structure-based virtual screening on a new open-source natural products database LOTUS to discover acetylcholinesterase ınhibitors

N.A.

Makale detayları

Structure-based virtual screening on a new open-source natural products database LOTUS to discover acetylcholinesterase ınhibitors

Yazarlar:

N.A.

Yayıncı:

Marmara University

Ana Başlıklar:

Pharmaceutical Chemistry

Dergi:

Journal of Research in Pharmacy Vol.28 Issue 4, pp.1099-1106

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001347027

pISSN:

2630-6344

Anahtar kelimeler:

Özet:

 Acetylcholinesterase AChE inhibitors have been used to delay the dementia progression in Alzheimers 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.

 Acetylcholinesterase AChE inhibitors have been used to delay the dementia progression in Alzheimers 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.

 Acetylcholinesterase AChE inhibitors have been used to delay the dementia progression in Alzheimers 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.

 Acetylcholinesterase AChE inhibitors have been used to delay the dementia progression in Alzheimers 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.

Makale detayları

Structure-based virtual screening on a new open-source natural products database LOTUS to discover acetylcholinesterase ınhibitors

Yazarlar: N.A.

Yayıncı: Marmara University

Ana Başlıklar: Pharmaceutical Chemistry

Dergi: Journal of Research in Pharmacy Vol.28 Issue 4, pp.1099-1106

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001347027

pISSN: 2630-6344

Structure-based virtual screening

machine learning

acetylcholinesterase

natural products

Sayı

Yazarlar:

N.A.

Yayıncı:

Marmara University

Ana Başlıklar:

Pharmaceutical Chemistry

Dergi:

Journal of Research in Pharmacy Vol.28 Issue 4, pp.1099-1106

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001347027

pISSN:

2630-6344