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Letters in Drug Design & Discovery

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ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

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Research Article

Research on the Anti-tumor Activity of a Novel Aminopeptidase Inhibitor Based on 3D QSAR Model

Author(s): Liqiang Meng*, Yanhong Ou-Yang, Fuyin Lv, Jiarong Song and Jianxin Yao

Volume 19, Issue 9, 2022

Published on: 25 March, 2022

Page: [811 - 822] Pages: 12

DOI: 10.2174/1570180819666220210101641

Price: $65

Abstract

Background: Aminopeptidase N (APN) is a type II transmembrane zinc ion-dependent metalloprotease. It is closely related to many processes of tumor occurrence and development, such as the formation of new blood vessels and tumor metastasis. Recent studies have shown that APN is a member of the family of surface markers of liver cancer stem cells. Therefore, APN small molecule inhibitors may have multiple compound functions, exerting multiple anti-tumor effects at multiple stages of cancer occurrence and development.

Methods: Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) approaches were employed in the study.

Results: Both internal and external cross-validations were conducted to obtain high predictive and satisfactory CoMFA model (q2 = 0.627, r2 = 0.995, SEE = 0.043) and CoMSIA model (q2 = 0.575, r2 = 0.998, SEE = 0.031) values. The statistical results obtained from CoMFA and CoMSIA models were found to be credible and having remarkable predictive power.

Conclusion: The results of 3D-QSAR are reliable and significant with high predictive (q2) ability, and a lower value of the standard error of estimation indicates a good correlation between predicted and observed activity. All these results have revealed many useful structural insights to improve the activity of the newly designed APN small molecule inhibitors.

Keywords: 3D-QSAR, CoMFA, CoMSIA, PLS, APN, small molecule inhibitors.

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