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cgbind: A Python Module and Web App for Automated Metallocage Construction and Host-Guest Characterization.
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2020-06-24 , DOI: 10.1021/acs.jcim.0c00519
Tom A Young 1 , Razvan Gheorghe 1 , Fernanda Duarte 1
Affiliation  

Metallocages offer a diverse and underexplored region of chemical space in which to search for novel catalysts and substrate hosts. However, the ability to tailor such structures toward applications in binding and catalysis is a challenging task. Here, we present an open-source computational toolkit, cgbind, that facilitates the construction, characterization, and prediction of functional metallocages. It employs known structural scaffolds as starting points and computationally efficient approaches for property evaluation. We demonstrate the ability of cgbind to construct libraries of cages with varied topologies and linker functionalities, generate accurate geometries (RMSD < 1.5 Å to crystal structures), and predict substrate binding with accuracy on par with semiempirical QM, all in seconds. The cgbind code presented here is freely available at github.com/duartegroup/cgbind and also via a web-based graphical user interface at cgbind.chem.ox.ac.uk. The protocol described here paves the way for high-throughput virtual screening of potential supramolecular structures, accelerating the search for new hosts and catalysts.

中文翻译:

cgbind:一个用于自动进行金属定位和表征主机的Python模块和Web应用程序。

Metallocages提供了一个多样的,尚未充分开发的化学空间区域,可在其中寻找新型催化剂和底物主体。然而,使这种结构适应结合和催化应用的能力是一项艰巨的任务。在这里,我们提出了一个开放源代码的计算工具包cgbind,它可以简化功能性金属定位的构建,表征和预测。它采用已知的结构支架作为起点,并采用计算有效的方法进行属性评估。我们展示了cgbind的能力可以构建具有多种拓扑结构和接头功能的笼子库,生成精确的几何形状(相对于晶体结构的RMSD <1.5Å),并能在几秒钟内准确地预测与半经验QM相同的底物结合。此处提供的cgbind代码可在github.com/duartegroup/cgbind上免费获得,也可以通过cgbind.chem.ox.ac.uk上基于Web的图形用户界面免费获得。此处描述的协议为潜在的超分子结构的高通量虚拟筛选铺平了道路,从而加速了对新宿主和催化剂的搜索。
更新日期:2020-07-27
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