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Updated: Jan 12, 2026

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深度学习驱动的QSAR和微规模MD模拟导向策略揭示了无毒的人类HGFR抑制剂

Muhammad Waleed Iqbal1, Muhammad Ali Raza1, Xinxiao Sun1

  • 1State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing, 100029, People's Republic of China.

Molecular diversity
|October 30, 2025
PubMed
概括

研究人员通过计算选FDA批准的药物以抑制肝细胞生长因子受体 (HGFR) 来确定潜在的新卵巢癌治疗方法. 像venetoclax这样的有希望的候选药物显示出高强度和低毒性,提供了更安全的治疗替代品.

关键词:
深度学习是一种深度学习.在HGFR的基础上,HGFR模拟MD的模拟方法卵巢癌是发生在卵巢中的癌症.

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Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
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