A Semester-Long Learning Path Teaching Computational Skills via Molecular Graphics in PyMOL

Magnus Kjaergaard, Laura Skak Rasmussen, Johan Nygaard Vinther, Kasper Røjkjær Andersen, E. Andersen, E. Lorentzen, S. Thirup, D. Otzen, D. Brodersen
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Abstract

Structural biology describes biological processes at the molecular level and is an integral part of undergraduate study programs in molecular biosciences. Students are often fascinated by the visualizations created by molecular graphics software, which allow them to see the molecular world for the first time. Today, molecular visualization and structural analysis do not require expensive high-end computers but can be performed on the students' own laptops and are therefore highly suited for active learning approaches. We have designed a semester-long learning path that integrates molecular graphics and structural analysis using PyMOL into an undergraduate course in biomolecular structure and function. Compared to stand-alone PyMOL introductions, the semester-long learning path allows for an improved pedagogical design. The path progressively introduces more advanced functions in relevant scientific contexts and allows for spaced repetition. Advanced analysis functions in PyMOL are available only via the command line, so the learning path also teaches basic scripting and serves as an accessible introduction to computational thinking because a few lines of code can produce stunning results. Student surveys carried out at the end of the course suggest that the learning path supported the ability to perform structural analysis to a high degree. Moreover, a simulated exam showed that almost all students were able to carry out basic visualization tasks using PyMOL scripts, while three-quarters could undertake advanced structural analysis after following the course. In summary, integration of molecular graphics software with teaching of structural biochemistry allows a hands-on approach to analyzing molecular mechanisms and introduces biologically oriented students to computational thinking.
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在PyMOL中通过分子图形学教授计算技能的一学期学习路径
结构生物学在分子水平上描述生物过程,是分子生物科学本科学习计划的一个组成部分。学生们经常被分子图形软件创造的可视化所吸引,这让他们第一次看到分子世界。今天,分子可视化和结构分析不需要昂贵的高端计算机,而是可以在学生自己的笔记本电脑上进行,因此非常适合主动学习方法。我们设计了一个学期的学习路径,将分子图形学和PyMOL结构分析整合到生物分子结构和功能的本科课程中。与独立的PyMOL介绍相比,长达一个学期的学习路径允许改进的教学设计。这条路径在相关的科学背景下逐步引入更先进的功能,并允许间隔重复。PyMOL中的高级分析功能只能通过命令行使用,因此学习路径还教授基本的脚本编写,并作为计算思维的入门,因为几行代码可以产生惊人的结果。课程结束时进行的学生调查表明,学习路径在很大程度上支持了进行结构分析的能力。此外,模拟考试表明,几乎所有学生都能够使用PyMOL脚本执行基本的可视化任务,而四分之三的学生在学习课程后可以进行高级结构分析。总之,将分子图形软件与结构生物化学教学相结合,可以让学生通过动手的方式分析分子机制,并向生物学取向的学生介绍计算思维。
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