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介绍 Pep McConst——一个适用于生物物理应用的用户友好型肽建模器。

Introducing Pep McConst-A user-friendly peptide modeler for biophysical applications.

机构信息

Department of Physics, Carl von Ossietzky Universät Oldenburg, Oldenburg, Germany.

Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense, Denmark.

出版信息

J Comput Chem. 2021 Mar 30;42(8):572-580. doi: 10.1002/jcc.26479. Epub 2021 Jan 10.

Abstract

We are introducing Pep McConst-a software that employs a Monte-Carlo algorithm to construct 3D structures of polypeptide chains which could subsequently be studied as stand-alone macromolecules or complement the structure of known proteins. Using an approach to avoid steric clashes, Pep McConst allows to create multiple structures for a predefined primary sequence of amino acids. These structures could then effectively be used for further structural analysis and investigations. The article introduces the algorithm and describes its user-friendly approach that was made possible through the VIKING online platform. Finally, the manuscript provides several highlight examples where Pep McConst was used to predict the structure of the C-terminal of a known protein, generate a missing bit of already crystallized protein structures and simply generate short polypeptide chains.

摘要

我们正在介绍 Pep McConst 软件,它采用了蒙特卡罗算法来构建多肽链的 3D 结构,这些结构随后可以作为独立的大分子进行研究,也可以补充已知蛋白质的结构。该软件采用了一种避免空间位阻的方法,可以为预定义的氨基酸序列创建多个结构。然后,可以有效地将这些结构用于进一步的结构分析和研究。本文介绍了该算法,并描述了通过 VIKING 在线平台实现的用户友好方法。最后,本文提供了几个亮点示例,说明了 Pep McConst 如何用于预测已知蛋白质的 C 末端结构、生成已结晶蛋白质结构的缺失部分以及简单生成短多肽链。

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