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Updated: May 17, 2025

Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation
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Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

Published on: May 20, 2020

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对多代EGFR抑制剂的结构-活性关系的建模和解释性研究

Zhiqi Sun1, Donghui Huo1, Jiangyu Guo1

  • 1State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, Beijing University of Chemical Technology, P.O. Box 53, 15 BeiSanHuan East Road, Beijing 100029, China.

ACS omega
|March 31, 2025
PubMed
概括

开发新的表皮生长因子受体 (EGFR) 抑制剂至关重要. 一个多任务深度神经网络 (MT-DNN) 模型有效地预测了多代EGFR抑制剂的生物活性,优于单任务模型,并提供了克服抵抗突变的结构洞察力.

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