您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
Andreas Evers1, Shipra Malhotra2, Wolf-Guido Bolick3
1Computational Chemistry & Biologics (CCB), Merck Healthcare KGaA, Darmstadt, Germany. Andreas.Evers@merckgroup.com.
这项研究引入了一种in silico方法,用于评估抗体和VHH序列的开发能力风险,超出结合亲和力. 该方法有助于通过预测特性和确定优化起点来选择治疗开发的最佳候选者.
06:50Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
05:08Application 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
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
结论: