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Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
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基于图形神经网络和分子静电潜能表面的尼菲迪平的晶预测

Yuting Wang1, Yanling Jiang1, Yu Zhou1

  • 1Chongqing Key Laboratory of Digitalization of Pharmaceutical Processes and Equipment, College of Chemistry and Chemical Engineering, Chongqing University of Science and Technology, No. 20, University City East Road, Chongqing, 401331, China.

AAPS PharmSciTech
|June 11, 2024
PubMed
概括

研究人员开发了一个图形神经网络模型 (CocrystalGNN) 来预测尼菲迪平 (NIF) 协同晶体. 这种方法成功地确定了具有更好的溶解性和溶解性的新型共晶体,从而增强了药物.

关键词:
同晶体预测预测电静电潜在的表面电静电潜力.图形神经网络的神经网络尼菲迪平因 (nifedipine) 是一种尼菲迪平因 (nifedipine) 的一种药物.虚拟选 虚拟选 虚拟选

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