北京生物醫(yī)學(xué)工程

蛋白激酶CK2天然產(chǎn)物類抑制劑的定量構(gòu)效關(guān)系研究

Quantitative structure-activity relationship studies on natural product inhibitors of protein kinase CK2

作者：張雪文張娜李春華孫國輝趙麗嬌鐘儒剛

單位：北京工業(yè)大學(xué)環(huán)境與生命學(xué)部（北京 100124）<br />通信作者：張娜。E-mai：[email protected]

關(guān)鍵詞：蛋白激酶CK2；天然產(chǎn)物類抑制劑；定量結(jié)構(gòu)-活性關(guān)系；遺傳算法；多元線性回歸

分類號：R318.04

出版年·卷·期（頁碼）：2023·42·1（81-87）

摘要：

目的構(gòu)建CK2天然產(chǎn)物類抑制劑的定量構(gòu)效關(guān)系(quantitative structure-activity relationship, QSAR)模型，揭示影響該類抑制劑活性的結(jié)構(gòu)因素，為新型CK2抑制劑的開發(fā)提供理論基礎(chǔ)和實(shí)驗(yàn)依據(jù)。方法基于文獻(xiàn)報(bào)道的115個多骨架CK2天然產(chǎn)物類抑制劑，采用遺傳算法（genetic algorithm，GA）聯(lián)合多元線性回歸（multiple linear regression，MLR）方法，建立了基于優(yōu)選的Dragon描述符的QSAR模型，以留一法交叉驗(yàn)證系數(shù)Q2LOO以及相關(guān)系數(shù)R2作為模型內(nèi)部驗(yàn)證的評價(jià)指標(biāo)；通過Q2ext和 R2ext評估模型的外部預(yù)測能力。結(jié)果最優(yōu)2D-QSAR模型由8個描述符組成，基于訓(xùn)練集內(nèi)部驗(yàn)證的統(tǒng)計(jì)學(xué)參數(shù)為Q2Loo=0.7914、R2=0.8220；基于測試集外部驗(yàn)證的統(tǒng)計(jì)學(xué)參數(shù)為Q2ext=0.7921、R2ext=0.7998，表明該模型具有較高的可靠性和預(yù)測能力。結(jié)論該模型表明，影響CK2天然產(chǎn)物類抑制劑活性的分子描述符包括IVDE、CATS2D_08_DA、nArX、IC1、Chi_D/Dt、SdssC、F08[C-O]以及C-006，可為新型CK2抗癌抑制劑的發(fā)現(xiàn)提供實(shí)驗(yàn)指導(dǎo)。

Objective To build the quantitative structure-activityy relationship model of CK2 natural products inhibitors ，and to elucidate the underlying structural factors influencing their inhibitory activity. This study will provide the theoretical basis and experimental guidance for the development of new protein kinase CK2 inhibitors. Methods Based on 115 CK2 natural product inhibitors with diverse chemical scaffolds reported in the published literature, genetic algorithm (GA) and multiple linear regression (MLR) methods, combined with preferred molecular descriptors calculated by Dragon, were employed to build the 2D-QSAR model.. The leave-one-out cross-validation coefficient Q2LOO and the correlation coefficient R2 were used as the evaluation indicators for the internal verification of the model, and the external predictive ability of the model was evaluated through Q2ext and R2ext. Results The best model composed of 8 molecular descriptors possessed Q2Loo=0.7914、R2=0.8220 with leave one out cross-validation of training set and Q2ext=0.7921、R2ext=0.7998 of external validation, which indicated that the model had the robust reliability and high predictability. Conclusions The results clearly indicate that the anti-CK2 activity of natural product inhibitors is mainly related to the descriptors IVDE CATS2D_08_DA, nArX, IC1, Chi_D/Dt, SdssC, F08[CO] and C-006. This study can provide experimental guidance for the discovery of novel CK2 anti-cancer inhibitors

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