Literature DB >> 18632275

Synthesis, inhibitory activities, and QSAR study of xanthone derivatives as alpha-glucosidase inhibitors.

Yan Liu1, Zhuofeng Ke, Jianfang Cui, Wen-Hua Chen, Lin Ma, Bo Wang.   

Abstract

Xanthones and their derivatives have been reported to exhibit strong inhibitory activities toward alpha-glucosidase. To provide deep insight into the correlation between inhibitory activities and structures of xanthones, multiple linear regression (MLR) method was employed to establish QSAR models for 43 xanthone derivatives that have diverse structures. Among the 38 typical descriptors investigated, Hs (number of H-bond forming substituents), N(pi) (number of aromatic rings), and S (softness value) can be utilized to model the inhibitory activity. Thus, inhibitory activities of xanthone derivatives can be regulated by H-bond forming substituents, pi-stacking-forming aromatic rings and softness values on the xanthone skeleton. The accuracy and predictive power of the proposed QSAR model were verified by LOO validation, Y-randomization, and test group validation with newly synthesized xanthone derivatives.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18632275     DOI: 10.1016/j.bmc.2008.06.043

Source DB:  PubMed          Journal:  Bioorg Med Chem        ISSN: 0968-0896            Impact factor:   3.641


  4 in total

1.  Docking-assisted 3D-QSAR studies on xanthones as α-glucosidase inhibitors.

Authors:  Xuehua Zheng; Siyuan Zhou; Chen Zhang; Deyan Wu; Hai-Bin Luo; Yinuo Wu
Journal:  J Mol Model       Date:  2017-08-31       Impact factor: 1.810

2.  Anti-tumour effects of xanthone derivatives and the possible mechanisms of action.

Authors:  Quan-Guan Su; Yan Liu; Yu-Chen Cai; Yue-Li Sun; Bo Wang; Li-Jian Xian
Journal:  Invest New Drugs       Date:  2010-06-26       Impact factor: 3.850

3.  A QSAR Study of Matrix Metalloproteinases Type 2 (MMP-2) Inhibitors with Cinnamoyl Pyrrolidine Derivatives.

Authors:  Eduardo Borges de Melo
Journal:  Sci Pharm       Date:  2012-01-31

4.  A simple and robust model to predict the inhibitory activity of α-glucosidase inhibitors through combined QSAR modeling and molecular docking techniques.

Authors:  Elaheh Izadpanah; Siavash Riahi; Zeinab Abbasi-Radmoghaddam; Sajjad Gharaghani; Mohammad Mohammadi-Khanaposhtanai
Journal:  Mol Divers       Date:  2021-02-09       Impact factor: 3.364

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.