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Updated: Jul 19, 2025

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
05:08

Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins

Published on: July 8, 2025

96

可靠的蛋白质-蛋白质对接与AlphaFold,Rosetta和复制品交换

Ameya Harmalkar1, Sergey Lyskov1, Jeffrey J Gray1,2

  • 1Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.

bioRxiv : the preprint server for biology
|August 7, 2023
PubMed
概括

AlphaRED将AlphaFold与基于物理的对接集成,以改善蛋白质复杂结构预测,特别是在具有构造变化的情况下. 这种新方法提高了对具有挑战性的目标的准确性,优于现有的工具.

关键词:
形状的变化 形状的变化机器学习是机器学习.蛋白质对接的对接方式结构预测 结构预测

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