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Updated: Sep 17, 2025

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使用基于MPNN和LSTM的转移学习的线性激素Eg5抑制剂的De novo设计和生物活性预测

Damilola Samuel Bodun1, Isiaka O Ibrahim2, Mujeebat Bashiru3

  • 1Standard Seed Corporation, Smyrna, USA; Covenant University Bioinformatics Research (CUBRe), Covenant University, Ota, Nigeria; ChemoInformatics Academy, Lagos, Nigeria.

Computers in biology and medicine
|June 27, 2025
PubMed
概括

生成性AI设计了针对Eg5蛋白的新型乳腺癌药物. 最好的化合物显示出优越的结合亲和力,表明了新的癌症治疗的潜力.

关键词:
长时间短期记忆 (LSTM)传递信息的神经网络的神经网络.线粒体动因子Eg5 Eg5分子动力学模拟模型转移学习转移学习

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