Literature DB >> 31487462

Discovery of Novel Inhibitors Targeting Human O-GlcNAcase: Docking-Based Virtual Screening, Biological Evaluation, Structural Modification, and Molecular Dynamics Simulation.

Lili Dong1, Shengqiang Shen1, Wei Chen2, Dongdong Xu1, Qing Yang2, Huizhe Lu1, Jianjun Zhang1.   

Abstract

β-N-Acetylhexosaminidases have emerged as promising targets for drug and pesticide discovery due to their critical physiological functions in various cellular processes. In particular, human O-GlcNAcase (hOGA) from the glycoside hydrolase family 84 (GH84) has gained significant attention. This enzyme was found to be linked to various diseases such as diabetes, cancer, and Alzheimer's disease (AD). In this study, to develop novel hOGA inhibitors with suitable pharmaceutical properties, virtual screening of the Drugbank database was performed using a docking-based approach targeting hOGA. Chlorhexidine (4, Ki = 4.0 μM) was identified as a potent hOGA inhibitor with excellent selectivity (Ki > 200 μM against human β-N-acetylhexosaminidase B) and subjected to structural modifications and SAR studies. Furthermore, molecular dynamics simulations as well as binding free energy and free energy decomposition calculations were carried out to investigate the basis for the efficiency of potent inhibitors against hOGA. This present work revealed the new application of the disinfectant chlorhexidine and provided useful information for the future design of hOGA inhibitors.

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Year:  2019        PMID: 31487462     DOI: 10.1021/acs.jcim.9b00479

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  2 in total

1.  Region- and voxel-based quantification in human brain of [18F]LSN3316612, a radioligand for O-GlcNAcase.

Authors:  Jae-Hoon Lee; Mattia Veronese; Jeih-San Liow; Cheryl L Morse; Jose A Montero Santamaria; Mohammad B Haskali; Sami S Zoghbi; Victor W Pike; Robert B Innis; Paolo Zanotti-Fregonara
Journal:  EJNMMI Res       Date:  2021-04-01       Impact factor: 3.138

2.  Exploration and augmentation of pharmacological space via adversarial auto-encoder model for facilitating kinase-centric drug development.

Authors:  Xinyu Bai; Yuxin Yin
Journal:  J Cheminform       Date:  2021-12-06       Impact factor: 5.514

  2 in total

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