Ligand-based discovery of new potential acetylcholinesterase inhibitors for Alzheimer's disease treatment

被引:5
作者
Canizares-Carmenate, Y. [1 ]
Nam, N-H [2 ]
Diaz-Amador, R. [3 ]
Thuan, N. T. [2 ]
Dung, P. T. P. [2 ]
Torrens, F. [4 ]
Pham-The, H. [2 ]
Perez-Gimenez, F. [5 ]
Castillo-Garit, J. A. [5 ,6 ]
机构
[1] Univ Cent Marta Abreu Las Villas, Fac Quim Farm, Unit Comp Aided Mol Biosil Discovery & Bioinforma, Santa Clara, Cuba
[2] Hanoi Univ Pharm, Dept Pharmaceut Chem, Hanoi, Vietnam
[3] Univ Cent Marta Abreu Las Villas, Dept Comp Sci, Santa Clara, Cuba
[4] Univ Valencia, Inst Univ Ciencia Mol, Edifici Inst Paterna, Valencia, Spain
[5] Univ Valencia, Fac Farm, Dept Quim Fis, Unidad Invest Diseno Farmacos & Conectividad Mol, Valencia, Spain
[6] Univ Ciencias Med Villa Clara, Unidad Toxicol Expt, Santa Clara, Cuba
关键词
Acetylcholinesterase inhibitor; Alzheimer's disease; benzothiadiazine; 1; 1-dioxide; quinazolinones; support vector machine; DRUG DESIGN; CLASSIFICATION;
D O I
10.1080/1062936X.2022.2025615
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The enzyme acetylcholinesterase (AChE) is currently a therapeutic target for the treatment of neurodegenerative diseases. These diseases have highly variable causes but irreversible evolutions. Although the treatments are palliative, they help relieve symptoms and allow a better quality of life, so the search for new therapeutic alternatives is the focus of many scientists worldwide. In this study, a QSAR-SVM classification model was developed by using the MATLAB numerical computation system and the molecular descriptors implemented in the Dragon software. The obtained parameters are adequate with accuracy of 88.63% for training set, 81.13% for cross-validation experiment and 81.15% for prediction set. In addition, its application domain was determined to guarantee the reliability of the predictions. Finally, the model was used to predict AChE inhibition by a group of quinazolinones and benzothiadiazine 1,1-dioxides obtained by chemical synthesis, resulting in 14 drug candidates with in silico activity comparable to acetylcholine.
引用
收藏
页码:49 / 61
页数:13
相关论文
共 28 条
[1]   The present and future of pharmacotherapy of Alzheimer's disease: A comprehensive review [J].
Anand, Abhinav ;
Patience, Albert Anosi ;
Sharma, Neha ;
Khurana, Navneet .
EUROPEAN JOURNAL OF PHARMACOLOGY, 2017, 815 :364-375
[2]  
[Anonymous], 2016, DEM FACT SHEET
[3]  
[Anonymous], 2001, STATISTICA DAT AN SO
[4]   Assessing the accuracy of prediction algorithms for classification: an overview [J].
Baldi, P ;
Brunak, S ;
Chauvin, Y ;
Andersen, CAF ;
Nielsen, H .
BIOINFORMATICS, 2000, 16 (05) :412-424
[5]   In vitro evaluation and in silico screening of synthetic acetylcholinesterase inhibitors bearing functionalized piperidine pharmacophores [J].
Brahmachari, Goutam ;
Choo, CheeYan ;
Ambure, Pravin ;
Roy, Kunal .
BIOORGANIC & MEDICINAL CHEMISTRY, 2015, 23 (15) :4567-4575
[6]   Explorative and targeted neuroproteomics in Alzheimer's disease [J].
Brinkmalm, Ann ;
Portelius, Erik ;
Ohrfelt, Annika ;
Brinkmalm, Gunnar ;
Andreasson, Ulf ;
Gobom, Johan ;
Blennow, Kaj ;
Zetterberg, Henrik .
BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS, 2015, 1854 (07) :769-778
[7]   Comparative study to predict toxic modes of action of phenols from molecular structures [J].
Brito-Sanchez, Y. ;
Castillo-Garit, J. A. ;
Le-Thi-Thu, H. ;
Gonzalez-Madariaga, Y. ;
Torrens, F. ;
Marrero-Ponce, Y. ;
Rodriguez-Borges, J. E. .
SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2013, 24 (03) :235-251
[8]   Machine learning approach to discovery of small molecules with potential inhibitory action against vasoactive metalloproteases [J].
Canizares-Carmenate, Yudith ;
Mena-Ulecia, Karel ;
MacLeod Carey, Desmond ;
Perera-Sardina, Yunier ;
Hernandez-Rodriguez, Erix W. ;
Marrero-Ponce, Yovani ;
Torrens, Francisco ;
Castillo-Garit, Juan A. .
MOLECULAR DIVERSITY, 2022, 26 (03) :1383-1397
[9]   Computational approach to the discovery of potential neprilysin inhibitors compounds for cardiovascular diseases treatment [J].
Canizares-Carmenate, Yudith ;
Alcantara Cardenas, Adriana ;
Roche Llerena, Viviana ;
Torrens, Francisco ;
Castillo-Garit, Juan A. .
MEDICINAL CHEMISTRY RESEARCH, 2020, 29 (05) :897-909
[10]   A Simple Method to Predict Blood-Brain Barrier Permeability of Drug-Like Compounds Using Classification Trees [J].
Castillo-Garit, Juan A. ;
Casanola-Martin, Gerardo M. ;
Huong Le-Thi-Thu ;
Hai Pham-The ;
Barigye, Stephen J. .
MEDICINAL CHEMISTRY, 2017, 13 (07) :664-669