4.6 Article

Circular dichroism for secondary structure determination of proteins with unfolded domains using a self-organising map algorithm SOMSpec

期刊

RSC ADVANCES
卷 11, 期 39, 页码 23985-23991

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/d1ra02898g

关键词

-

向作者/读者索取更多资源

This method utilizes the neural network approach SOMSpec to determine the secondary structure of proteins with significant unfolded domains. By derandomizing spectra and regenerating alpha-helical and beta-sheet contents, it has shown promising results in determining protein structures with unfolded domains.
Many proteins and peptides are increasingly being recognised to contain unfolded domains or populations that are key to their function, whether it is in ligand binding or material assembly. We report an approach to determine the secondary structure for proteins with suspected significant unfolded domains or populations using our neural network approach SOMSpec. We proceed by derandomizing spectra by removing fractions of random coil (RC) spectra prior to secondary structure fitting and then regenerating alpha-helical and beta-sheet contents for the experimental proteins. Application to bovine serum albumin spectra as a function of temperature proved to be straightforward, whereas lysozyme and insulin have hidden challenges. The importance of being able to interrogate the SOMSpec output to understand the best matching units used in the predictions is illustrated with lysozyme and insulin whose partially melted proteins proved to have significant beta(II) content and their CD spectrum looks the same as that for a random coil.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据