插件
计算机科学
可视化
质量(理念)
质量评定
图形用户界面
软件工程
定量评估
数据挖掘
软件
人机交互
程序设计语言
数据可视化
人工智能
可视化程序设计语言
作者
Yifan Deng,Jinyuan Sun
标识
DOI:10.1021/acs.jcim.5c02410
摘要
Deep learning has transformed protein structure prediction, yet most state-of-the-art models remain challenging for experimental scientists to access. To address this, we present PymolFold, an open-source PyMOL plugin that seamlessly integrates cutting-edge structure predictors accessible via application programming interfaces into the molecular visualization environment. PymolFold supports both graphical and command-line interfaces for flexible usage and incorporates a structural quality assessment tool for the quantitative evaluation of predictions against reference structures. Together, these features establish a unified "predict-visualize-analyze" workflow, lowering technical barriers and broadening access to advanced structural modeling. PymolFold is available at https://github.com/jinyuansun/PymolFold.
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