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Updated: Jul 4, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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EquiPNAS:使用蛋白语言模型信息等同变量深图神经网络改进了蛋白质核酸结合部位的预测

Rahmatullah Roche1, Bernard Moussad1, Md Hossain Shuvo1

  • 1Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA.

Nucleic acids research
|January 28, 2024
PubMed
概括

EquiPNAS是一个新的框架,通过将蛋白质语言模型 (pLMs) 与E(3) 等价深图神经网络集成,提高了蛋白质-核酸结合部位的预测. 这种方法提高了准确性,并减少了对DNA和RNA结合部位识别的进化数据的依赖.

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