目的 基于網(wǎng)絡(luò)藥理學(xué)和分子對(duì)接探討美洲大蠊CII-3治療結(jié)直腸癌的作用機(jī)制。方法 通過查閱文獻(xiàn)歸納總結(jié)篩選美洲大蠊CII-3的有效活性成分；利用PubChem數(shù)據(jù)庫(kù)、SwissADME、SwissTargetPrediction平臺(tái)進(jìn)行作用靶點(diǎn)的預(yù)測(cè)；通過DisGeNet、GeneCards、TTD、OMIM數(shù)據(jù)庫(kù)檢索、歸納、篩選結(jié)直腸癌相關(guān)靶點(diǎn)；通過Venny 2.1.0對(duì)美洲大蠊CII-3活性成分作用靶點(diǎn)與結(jié)直腸癌相關(guān)靶點(diǎn)取交集，共同靶點(diǎn)即為CII-3抗結(jié)直腸癌的潛在作用靶點(diǎn)。將潛在靶點(diǎn)導(dǎo)入STRING數(shù)據(jù)庫(kù)，構(gòu)建蛋白互作（PPI）網(wǎng)絡(luò)。通過PPI網(wǎng)絡(luò)和Cytoscape 3.10.1軟件及centiscape 2.2插件，篩選出美洲大蠊CII-3治療結(jié)直腸癌的關(guān)鍵活性成分及核心靶點(diǎn)，構(gòu)建“藥物-成分-靶點(diǎn)基因”和“疾病-通路-靶點(diǎn)-成分-藥物”網(wǎng)絡(luò)。利用DAVID數(shù)據(jù)庫(kù)對(duì)CII-3和結(jié)直腸癌潛在的作用靶點(diǎn)進(jìn)行基因本體論（GO）功能及京都基因與基因組百科全書（KEGG）通路富集分析。利用AutoDockTools 1.5.7軟件對(duì)關(guān)鍵活性成分與核心靶點(diǎn)進(jìn)行分子對(duì)接驗(yàn)證。結(jié)果 篩選匯總了24種美洲大蠊CII-3的有效成分，通過網(wǎng)絡(luò)藥理學(xué)驗(yàn)證環(huán)(脯氨酸-亮氨酸)、環(huán)(亮氨酸-丙氨酸)等為主要活性成分，通過Venny 2.1.0平臺(tái)取交集，得到150個(gè)潛在的作用靶點(diǎn)。甘油醛-3-磷酸脫氫酶（GAPDH）、蛋白激酶B1（Akt1）和表皮生長(zhǎng)因子受體（EGFR）等為主要的核心靶點(diǎn)。KEGG通路富集分析顯示主要涉及癌癥通路、磷脂酰肌醇3-激酶（PI3K）-Akt信號(hào)通路等；分子對(duì)接顯示，美洲大蠊CII-3的主要活性成分與預(yù)測(cè)的核心靶點(diǎn)對(duì)接結(jié)果均小于0 kJ/mol，結(jié)果顯示較好的結(jié)合活性。結(jié)論 美洲大蠊CII-3可能通過多成分、多靶點(diǎn)、多通路協(xié)同作用治療結(jié)直腸癌，為揭示CII-3治療結(jié)直腸癌的分子機(jī)制提供了理論基礎(chǔ)。

Objective To explore the anti-tumor mechanism of the Periplaneta americana peptide CII-3 based on literature summarization, network pharmacology, and molecular docking. Methods The effective active components of CII-3 were screened through literature summarization. The PubChem database, SwissADME, and SwissTargetPrediction platforms were utilized for target prediction. Relevant targets for colorectal cancer were retrieved, summarized, and screened via the DisGeNet, GeneCards, TTD, and OMIM databases. The Venny 2.1.0 was used to intersect the active components’ targets of CII-3 with colorectal cancer targets, identifying potential targets for CII-3’s action against colorectal cancer. These potential targets were imported into the STRING database to construct a protein-protein interaction (PPI) network. Using the PPI network, Cytoscape 3.10.1 software, and centiscape 2.2 plugin, key active components and core targets of CII-3 in treating colorectal cancer were screened, leading to the construction of the “drug-component-target gene” and “disease-pathway-target-component-drug” networks. The DAVID database was employed to perform GO function and KEGG pathway enrichment analyses on the potential targets of CII-3 and colorectal cancer. Molecular docking validation of the key active components and core targets was conducted using the AutoDockTools 1.5.7 software. Results A total of 24 effective components of CII-3 were summarized, with cyclo-(Pro-Leu), cyclo-(Leu-Ala), and others identified as main active components through network pharmacology validation. The Venny 2.1.0 platform yielded 150 potential targets. Major core targets included glyceraldehyde-3-phosphate dehydrogenase (GAPDH), protein kinase B1 (Akt1), and epidermal growth factor receptor (EGFR). KEGG pathway enrichment analysis indicated involvement in cancer pathways, the phosphatidylinositol 3-kinase (PI3K)-Akt signaling pathway, among others. Molecular docking revealed that the main active components of CII-3 had docking results with predicted core targets all below 0 kJ/mol, indicating good binding activity. Conclusion CII-3 may treat colorectal cancer through synergistic action involving multiple components, targets, and pathways, laying a theoretical foundation for elucidating the molecular mechanism of CII-3 in treating colorectal cancer.

R914

國(guó)家自然科學(xué)基金項(xiàng)目（81360319）；云南省中藥飲片產(chǎn)業(yè)發(fā)展專項(xiàng)資金（2019-YG-067）