Network Pharmacology Combined with Machine Learning to Reveal the Action Mechanism of Licochalcone Intervention in Liver Cancer

Sep 24, 2026

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Network pharmacology and machine learning are applied to uncover how licochalcones may act against liver cancer. The study targets licochalcone A through licochalcone G using computer-aided screening, machine-learning clustering, and quantitative structural similarity analyses to link small molecules with key proteins and interaction residues. Results indicate disruption of cancer signaling involving NF-κB, PD-L1/PD-1 checkpoint signaling, and related pathways, with additional candidate licorice flavonoids showing similar structures. Key amino acids are identified for flavonoid–nitric oxide synthase 2 binding, supporting drug-design ideas.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages26

Reading Time1 h 6 min

AccessFree to download

Introduction

Background and epidemiology of liver cancer

Limitations of conventional therapies

Rationale for natural compounds and integrative computational approaches

Article Network Pharmacology Combined with Machine Learning to Reveal the Action Mechanism of Licochalcone Intervention in Liver Cancer Fangfang Guo †, Xiaotang Yang †, Chengxiang Hu, Wannan Li * and Weiwei Han * Citation: Guo, F.; Yang, X.; Hu, C.; Li, W.; Han, W. Network Pharmacology Combined with Machine Learning to Reveal the Action Mechanism of Licochalcone Intervention in Liver Cancer. Int. J. Mol. Sci. 2023, 24, 15935. [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)ijms242115935 Academic Editor: Alain Couvineau Received: 22 September 2023 Revised: 30 October 2023 Accepted: 1 November 2023 Published: 3 November 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) . Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Science, Jilin University, 2699 Qianjin Street, Changchun 130012, China; [guoff15@mails.jlu.edu.cn](guoff15@mails.jlu.edu.cn) (F.G.); [yangxt22@mails.jlu.edu.cn](yangxt22@mails.jlu.edu.cn) (X.Y.); [hucx23@mails.jlu.edu.cn](hucx23@mails.jlu.edu.cn) (C.H.) * Correspondence: [liwannan@jlu.edu.cn](liwannan@jlu.edu.cn) (W.L.); [weiweihan@jlu.edu.cn](weiweihan@jlu.edu.cn) (W.H.)† These authors contributed equally to this work. Abstract: There are reports indicating that licochalcones can inhibit the proliferation, migration, and invasion of cancer cells by promoting the expression of autophagy-related proteins, inhibiting the expression of cell cycle proteins and angiogenic factors, and regulating autophagy and apoptosis. This study aims to reveal the potential mechanisms of licochalcone A (LCA), licochalcone B (LCB), licochalcone C (LCC), licochalcone D (LCD), licochalcone E (LCE), licochalcone F (LCF), and licochalcone G (LCG) inhibition in liver cancer through computer-aided screening strategies. By using machine learning clustering analysis to search for other structurally similar components in licorice, quantitative calculations were conducted to collect the structural commonalities of these components related to liver cancer and to identify key residues involved in the interactions between small molecules and key target proteins. Our research results show that the seven licochalcones molecules interfere with the cancer signaling pathway via the NF-􀀔B signaling pathway, PDL1 expression and PD1 checkpoint pathway in cancer, and others. Glypallichalcone, Echinatin, and 3,4,30,40-Tetrahydroxy-2-methoxychalcone in licorice also have similar structures to the seven licochalcones, which may indicate their similar effects. We also identiﬁed the key residues (including ASN364, GLY365, TRP366, and TYR485) involved in the interactions between ten ﬂavonoids and the key target protein (nitric oxide synthase 2) . In summary, we provide valuable insights into the molecular mechanisms of the anticancer effects of licorice ﬂavonoids, providing new ideas for the design of small molecules for liver cancer drugs. Keywords: network pharmacology; machine learning; quantitative calculation; ﬂavonoids; licorice 1. Introduction Cancer seriously affects human health and is expected to become the main cause of death in every country/region in the 21st century [1] . According to calculations for 2020, liver cancer is the sixth most common cancer and the third leading cause of cancer death [2] . Scientists from the International Agency for Research on Cancer (IARC) and its collaborating institutions have estimated the global burden of cancer in 2020 and predicted that by 2040, the number of new cases and deaths will increase by over 55% annually. The latest estimates show that in 2020, 905,700 people worldwide were diagnosed w

FAQs

What are the main licochalcones evaluated in the study for liver cancer intervention?

The study evaluates licochalcone A (LCA), licochalcone B (LCB), licochalcone C (LCC), licochalcone D (LCD), licochalcone E (LCE), licochalcone F (LCF), and licochalcone G (LCG).

How does the methodology use machine learning and network pharmacology?

The approach uses computer-aided screening strategies and machine-learning clustering analysis to find structurally similar components, then performs quantitative calculations to identify shared structural features and key residues in small molecule–target protein interactions.

Which biological pathways and targets are highlighted by the results?

The results implicate interference with cancer signaling via the NF-κB pathway and PD-L1/PD-1 checkpoint signaling. The study also identifies key residues involved in interactions between flavonoids and nitric oxide synthase 2.

Sep 24, 2026

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