Wang Linxiao, Huang Xiaoling, Xu Shidi, An Yufeng, Lv Xinya, Zhu Wufu, Xu Shan, Tu Yuanbiao, Chen Shuhui, Lv Qiaoli, Zheng Pengwu
Jiangxi Provincial Key Laboratory of Drug Design and Evaluation, School of Pharmacy, Jiangxi Science & Technology Normal University, Nanchang, 330013, China.
Cancer Research Center, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, China.
BMC Chem. 2024 Aug 27;18(1):159. doi: 10.1186/s13065-024-01279-z.
Facing the significant challenge of overcoming drug resistance in cancer treatment, particularly resistance caused by mutations in epidermal growth factor receptor (EGFR), the aim of our study was to identify potent EGFR inhibitors effective against the mutant, a key player in resistance mechanisms.
Our integrated in silico approach harnessed machine learning, virtual screening, and activity evaluation techniques to screen 5105 compounds from three libraries, aiming to find candidates capable of overcoming the resistance conferred by the T790M and C797S mutations within EGFR. This methodical process narrowed the search down to six promising compounds for further examination.
Kinase assays identified three compounds to which the T790M/C797S/L858R mutant exhibited increased sensitivity compared to the T790M/L858R mutant, highlighting the potential efficacy of these compounds against resistance mechanisms. Among them, T001-10027877 exhibited dual inhibitory effects, with IC values of 4.34 µM against EGFR and 1.27 µM against EGFR. Further investigations into the antiproliferative effects in H1975, A549, H460 and Ba/F3-EGFR cancer cells revealed that T001-10027877 was the most potent anticancer agent among the tested compounds. Additionally, the induction of H1975 cell apoptosis and cell cycle arrest by T001-10027877 were confirmed, elucidating its mechanism of action.
This study highlights the efficacy of combining computational techniques with bioactivity assessments in the quest for novel antiproliferative agents targeting complex EGFR mutations. In particular, T001-10027877 has great potential for overcoming EGFR-mediated resistance and merits further in vivo exploration. Our findings contribute valuable insights into the development of next-generation anticancer therapies, demonstrating the power of an integrated drug discovery approach.
面对癌症治疗中克服耐药性的重大挑战，尤其是由表皮生长因子受体（EGFR）突变引起的耐药性，我们研究的目的是鉴定对突变体有效的强效EGFR抑制剂，该突变体是耐药机制中的关键因素。
我们的综合计算机辅助方法利用机器学习、虚拟筛选和活性评估技术，从三个文库中筛选5105种化合物，旨在找到能够克服EGFR内T790M和C797S突变所赋予耐药性的候选化合物。这个有条不紊的过程将搜索范围缩小到六种有前景的化合物以进行进一步研究。
激酶测定确定了三种化合物，与T790M/L858R突变体相比，T790M/C797S/L858R突变体对这三种化合物表现出更高的敏感性，突出了这些化合物对抗耐药机制的潜在功效。其中，T001-10027877表现出双重抑制作用，对EGFR的IC值为4.34μM，对EGFR的IC值为1.27μM。对H1975、A549、H460和Ba/F3-EGFR癌细胞的抗增殖作用的进一步研究表明，T001-10027877是测试化合物中最有效的抗癌剂。此外，还证实了T001-10027877诱导H1975细胞凋亡和细胞周期停滞，阐明了其作用机制。
本研究强调了在寻找针对复杂EGFR突变的新型抗增殖药物时，将计算技术与生物活性评估相结合的功效。特别是，T001-10027877在克服EGFR介导的耐药性方面具有巨大潜力，值得进一步进行体内研究。我们的发现为下一代抗癌疗法的开发提供了有价值的见解，证明了综合药物发现方法的力量。
