Literature DB >> 24516878

Structural bioinformatics-based identification of EGFR inhibitor gefitinib as a putative lead compound for BACE.

Mingshan Niu, Jin Hu, Sijin Wu, Zhang Xiaoe, Huaxi Xu, Yunwu Zhang, Jie Zhang, Yongliang Yang.   

Abstract

β-secretase (BACE-1) is a potential target for the treatment of Alzheimer's disease (AD). Despite its potential, only few compounds targeting BACE have entered the clinical trials. Herein, we describe the identification of Gefitinib as a potential lead compound for BACE through an integrated approach of structural bioinformatics analysis, experimental assessment and computational analysis. In particular, we performed ELISA and western analysis to assess the effect of Gefitinib using N2a human APP695 cells. In addition, we investigated the binding mechanism of Gefitinib with BACE through molecular docking coupled with molecular dynamics simulations. The computational analyses revealed that hydrophobic contact is a major contributing factor to the binding of Gefitinib with BACE. The results obtained in the study have rendered Gefitinib as a putative lead compound for BACE. Further optimization studies are warranted to improve its potency and pharmacological properties against BACE for potential AD treatment.

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Year:  2014        PMID: 24516878     DOI: 10.1111/cbdd.12200

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  3 in total

1.  A benchmark driven guide to binding site comparison: An exhaustive evaluation using tailor-made data sets (ProSPECCTs).

Authors:  Christiane Ehrt; Tobias Brinkjost; Oliver Koch
Journal:  PLoS Comput Biol       Date:  2018-11-08       Impact factor: 4.475

2.  Therapeutic Targeting of Repurposed Anticancer Drugs in Alzheimer's Disease: Using the Multiomics Approach.

Authors:  Dia Advani; Pravir Kumar
Journal:  ACS Omega       Date:  2021-05-19

3.  Comparison of effectiveness and adverse effects of gefitinib, erlotinib and icotinib among patients with non-small cell lung cancer: A network meta-analysis.

Authors:  Yuanyuan Liu; Yu Zhang; Gangling Feng; Qiang Niu; Shangzhi Xu; Yizhong Yan; Shugang Li; Mingxia Jing
Journal:  Exp Ther Med       Date:  2017-09-01       Impact factor: 2.447

  3 in total

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