Using augmented reality in molecular case studies to enhance biomolecular structure-function explorations in undergraduate classrooms.

Molecular case studies (MCSs) are open educational resources that use a storytelling approach to engage students in biomolecular structure-function explorations, at the interface of biology and chemistry. Although MCSs are developed for a particular target audience with specific learning goals, they are suitable for implementation in multiple disciplinary course contexts. Detailed teaching notes included in the case study help instructors plan and prepare for their implementation in diverse contexts. A newly developed MCS was simultaneously implemented in a biochemistry and a molecular parasitology course at two different institutions. Instructors participating in this cross-institutional and multidisciplinary implementation collaboratively identified the need for quick and effective ways to bridge the gap between the MCS authors' vision and the implementing instructor's interpretation of the case-related molecular structure-function discussions. Augmented reality (AR) is an interactive and engaging experience that has been used effectively in teaching molecular sciences. Its accessibility and ease-of-use with smart devices (e.g., phones and tablets) make it an attractive option for expediting and improving both instructor preparation and classroom implementation of MCSs. In this work, we report the incorporation of ready-to-use AR objects as checkpoints in the MCS. Interacting with these AR objects facilitated instructor preparation, reduced students' cognitive load, and provided clear expectations for their learning. Based on our classroom observations, we propose that the incorporation of AR in MCSs can facilitate its successful implementation, improve the classroom experience for educators and students, and make MCSs more broadly accessible in diverse curricular settings.

A Concise Review of Biomolecule Visualization.

The structural characteristics of biomolecules are a major focus in the field of structural biology. Molecular visualization plays a crucial role in displaying structural information in an intuitive manner, aiding in the understanding of molecular properties. This paper provides a comprehensive overview of core concepts, key techniques, and tools in molecular visualization. Additionally, it presents the latest research findings to uncover emerging trends and highlights the challenges and potential directions for the development of the field.

TensorView for MATLAB: Visualizing tensors with Euler angle decoding.

TensorView for MATLAB is a GUI-based visualization tool for depicting second-rank Cartesian tensors as surfaces on three-dimensional molecular models. Both ellipsoid and ovaloid tensor display formats are supported, and the software allows for easy conversion of Euler angles from common rotation schemes (active, passive, ZXZ, and ZYZ conventions) with visual feedback. In addition, the software displays all four orientation-equivalent Euler angle solutions for the placement of a single tensor in the molecular frame and can report relative orientations of two tensors with all 16 orientation-equivalent Euler angle sets that relate them. The salient relations are derived and illustrated through several examples. TensorView for MATLAB expands and complements the earlier implementation of TensorView within the Mathematica programming environment and can be run without a MATLAB license. TensorView for MATLAB is available through github at https://github.com/LeoSvenningsson/TensorViewforMatlab, and can also be accessed directly via the NMRbox resource.

Integrative visualization of the molecular structure of a cellular microdomain.

An integrative approach to visualization is used to create a visual snapshot of the structural biology of the polar microdomain of Caulobacter crescentus. The visualization is based on the current state of molecular and cellular knowledge of the microdomain and its cellular context. The collaborative process of researching and executing the visualization has identified aspects that are well determined and areas that require further study. The visualization is useful for dissemination, education, and outreach, and the study lays the groundwork for future 3D modeling and simulation of this well-studied example of a cellular condensate.

PacDOCK: A Web Server for Positional Distance-Based and Interaction-Based Analysis of Docking Results.

Molecular docking is a key method for structure-based drug design used to predict the conformations assumed by small drug-like ligands when bound to their target. However, the evaluation of molecular docking studies can be hampered by the lack of a free and easy to use platform for the complete analysis of results obtained by the principal docking programs. To this aim, we developed PacDOCK, a freely available and user-friendly web server that comprises a collection of tools for positional distance-based and interaction-based analysis of docking results, which can be provided in several file formats. PacDOCK allows a complete analysis of molecular docking results through root mean square deviation (RMSD) calculation, molecular visualization, and cluster analysis of docked poses. The RMSD calculation compares docked structures with a reference structure, also when atoms are randomly labelled, and their conformational and positional differences can be visualised. In addition, it is possible to visualise a ligand into the target binding pocket and investigate the key receptor-ligand interactions. Moreover, PacDOCK enables the clustering of docking results by identifying a restrained number of clusters from many docked poses. We believe that PacDOCK will contribute to facilitating the analysis of docking results to improve the efficiency of computer-aided drug design.

Prot2Prot: a deep learning model for rapid, photorealistic macromolecular visualization.

Molecular visualization is a cornerstone of structural biology, providing insights into the form and function of biomolecules that are difficult to achieve any other way. Scientific analysis, publication, education, and outreach often benefit from photorealistic molecular depictions rendered using advanced computer-graphics programs such as Maya, 3ds Max, and Blender. However, setting up molecular scenes in these programs is laborious even for expert users, and rendering often requires substantial time and computer resources. We have created a deep-learning model called Prot2Prot that quickly imitates photorealistic visualization styles, given a much simpler, easy-to-generate molecular representation. The resulting images are often indistinguishable from images rendered using industry-standard 3D graphics programs, but they can be created in a fraction of the time, even when running in a web browser. To the best of our knowledge, Prot2Prot is the first example of image-to-image translation applied to macromolecular visualization. Prot2Prot is available free of charge, released under the terms of the Apache License, Version 2.0. Users can access a Prot2Prot-powered web app without registration at http://durrantlab.com/prot2prot .

Protein structural bioinformatics: An overview.

Proteins play a crucial role in organisms in nature. They are able to perform structural, catalytic, transport and defense functions in cells, among others. We understand that a variety of resources do exist to work with protein structural bioinformatics, which perform tasks such as protein modeling, protein docking, protein molecular dynamics, protein interaction, active and binding site prediction and mutation analysis. Nonetheless, they are generally spread all over different online repositories. For the students or professionals interested in working with protein structural bioinformatics, it may not be trivial to know what resources he/she should learn/use or where these could be accessed. Here, the main subareas in the field of protein structural bioinformatics are introduced with a brief description, and we point to and discuss several online resources, such as methods, databases and tools, in order to give an overview of this research field. Furthermore, we developed Protein Structural bioinformatics Overview (PreStO), a web tool available at http://bioinfo.dcc.ufmg.br/presto/, to organize and make it possible to retrieve these online resources based on a search term. We believe that this paper can be a starting point for potential bioinformaticians to trace a path that can be followed to build competencies and achieve knowledge milestones in the context of protein structural bioinformatics.

Considering best practices in color palettes for molecular visualizations.

Biomedical illustration and visualization techniques provide a window into complex molecular worlds that are difficult to capture through experimental means alone. Biomedical illustrators frequently employ color to help tell a molecular story, e.g., to identify key molecules in a signaling pathway. Currently, color use for molecules is largely arbitrary and often chosen based on the client, cultural factors, or personal taste. The study of molecular dynamics is relatively young, and some stakeholders argue that color use guidelines would throttle the growth of the field. Instead, content authors have ample creative freedom to choose an aesthetic that, e.g., supports the story they want to tell. However, such creative freedom comes at a price. The color design process is challenging, particularly for those without a background in color theory. The result is a semantically inconsistent color space that reduces the interpretability and effectiveness of molecular visualizations as a whole. Our contribution in this paper is threefold. We first discuss some of the factors that contribute to this array of color palettes. Second, we provide a brief sampling of color palettes used in both industry and research sectors. Lastly, we suggest considerations for developing best practices around color palettes applied to molecular visualization.

Aiming for the Bullseye: Targeted activities decrease misconceptions related to enzyme function for undergraduate biochemistry students.

Biochemistry curricula present a particular challenge to undergraduate students with abstract concepts which can lead to misconceptions that impede learning. In particular, these students have difficulty understanding enzyme structure and function concepts. Targeted learning activities and three-dimensional (3D) physical models are proposed to help students challenge these misconceptions and increase conceptual understanding. Here we assessed such pedagogical tools using the Enzyme-Substrate Interactions Concept Inventory (ESICI) to measure (mis)conceptual changes from Pre- to Post- time points in a single semester undergraduate biochemistry course. A Control group of students engaged with the active learning activities without the 3D physical models and students in the Intervention group utilized these activities with the 3D physical models. At the Post- time point both groups had higher, yet similar ESICI scores of the same magnitude as the highest scoring group from the national sample. Concomitantly, many misconception markers decreased compared to the national sample, although some of these differed between the Control and Intervention groups. Based on this assessment, both pedagogical approaches successfully increased conceptual understanding and targeted many of the misconceptions measured by the ESICI, however, several misconceptions persisted. Surprisingly, the students who used the 3D physical models did not demonstrate a further decrease in the misconception markers. Additionally, psychometric evaluation of the ESICI with our sample recommends the revision of several questions to improve the validity of this assessment. We also offer suggestions to improve instruction and pedagogical tools with further avenues for research on learning.

UnityMol prototype for FAIR sharing of molecular-visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments.

Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.

A practical guide to teaching with Proteopedia.

Proteopedia (proteopedia.org) is an open resource to explore the structure-function relationship of proteins and other biomolecules. This guide provides practical advice on how to incorporate Proteopedia into teaching the structure and function of proteins and other biomolecules. For 11 activities, we discuss desired outcomes, setting expectations, preparing students for the tasks, using resources within Proteopedia, and evaluating student work. We point out features of Proteopedia that make it especially suitable for teaching and give examples of how to avoid common pitfalls.

Meeting report: BioMolViz workshops for developing assessments of biomolecular visual literacy.

While molecular visualization has been recognized as a threshold concept in biology education, the explicit assessment of students' visual literacy skills is rare. To facilitate the evaluation of this fundamental ability, a series of NSF-IUSE-sponsored workshops brought together a community of faculty engaged in creating instruments to assess students' biomolecular visualization skills. These efforts expanded our earlier work in which we created a rubric describing overarching themes, learning goals, and learning objectives that address student progress toward biomolecular visual literacy. Here, the BioMolViz Steering Committee (BioMolViz.org) documents the results of those workshops and uses social network analysis to examine the growth of a community of practice. We also share many of the lessons we learned as our workshops evolved, as they may be instructive to other members of the scientific community as they organize workshops of their own.

SARS-CoV-2 virtual biochemistry labs on bioinformatics and drug design.

Colleges and universities are learning to provide relevant virtual lab experiences for students due to the COVID-19 pandemic. Even schools attempting in-person instruction often need to utilize virtual experiences for students absent due to quarantine or illness. Much of biochemistry is amenable to molecular visualization and/or computational study; however, many faculty face learning how to utilize new computational and molecular visualization software. We present a set of virtual lab exercises with detailed instructions to engage students in the discovery of novel antiviral compounds against the SARS-CoV-2 main protease.

Templates for writing PyMOL scripts.

PyMOL commands are used to exert exquisite control over the appearance of a molecular model. This control has made PyMOL popular for making images of protein structures for publications and presentations. However, many users have poor recall of the commands due to infrequent use of PyMOL. This poor recall hinders the writing of new code in scripts. One solution is to build the new script by using code fragments as templates for modular parts of the task at hand. The code fragments can be accessed from a library while writing the code from inside a text editor (e.g., Visual Studio Code, Vim, and Emacs). We developed a library of PyMOL code templates or snippets called pymolsnips to ease the writing of PyMOL code in scripts. We made pymolsnips available on GitHub in formats for 18 popular text editors. Most of the supported text editors are available for Mac, Windows, and Linux operating systems. The GitHub site includes animations that complement the instructions for installing the library for each text editor. We expect that the library will help many PyMOL users to be more productive when writing PyMOL script files.

Rapid deployment of smartphone-based augmented reality tools for field and online education in structural biology.

Structural biology education commonly employs molecular visualization software, such as PyMol, RasMol, and VMD, to allow students to appreciate structure-function relationships in biomolecules. In on-ground, classroom-based education, these programs are commonly used on University-owned devices with software preinstalled. Remote education typically involves the use of student-owned devices, which complicates the use of such software, owing to the fact that (a) student devices have differing configurations (e.g., Windows vs MacOS) and processing power, and (b) not all student devices are suitable for use with such software. Smartphones are near-ubiquitous devices, with smartphone ownership exceeding personal computer ownership, according to a recent survey. Here, we show the use of a smartphone-based augmented reality app, Augment, in a structural biology classroom exercise, which students installed independently without IT support. Post-lab attitudinal survey results indicate positive student experiences with this app. Based on our experiences, we suggest that smartphone-based molecular visualization software, such as that used in this exercise, is a powerful educational tool that is particularly well-suited for use in remote education.

Interactive learning modules with 3D printed models improve student understanding of protein structure-function relationships.

Ensuring undergraduate students become proficient in relating protein structure to biological function has important implications. With current two-dimensional (2D) methods of teaching, students frequently develop misconceptions, including that proteins contain a lot of empty space, that bond angles for different amino acids can rotate equally, and that product inhibition is equivalent to allostery. To help students translate 2D images to 3D molecules and assign biochemical meaning to physical structures, we designed three 3D learning modules consisting of interactive activities with 3D printed models for amino acids, proteins, and allosteric regulation with coordinating pre- and post-assessments. Module implementation resulted in normalized learning gains on module-based assessments of 30% compared to 17% in a no-module course and normalized learning gains on a comprehensive assessment of 19% compared to 3% in a no-module course. This suggests that interacting with these modules helps students develop an improved ability to visualize and retain molecular structure and function.

Something old, something new: Teaching the BMB lab.

Lab courses are a significant component of biochemistry and molecular biology (BMB) education. In teaching the labs, we combine established techniques with novel approaches. Lab formats have also moved from traditional cookbook style labs to guided inquiry to course-based undergraduate research experiences (CUREs), where faculty bring their own research interests into the course setting with a larger number of students in a much more restricted time frame. This presentation is designed to explore some of these ideas and challenge the reader to introduce research opportunities to all students, not just the smaller group of students in their research labs.

An idea to explore: Use of augmented reality for teaching three-dimensional biomolecular structures.

Biology and biochemistry students must learn to visualize and comprehend the complex three-dimensional (3D) structures of macromolecules such as proteins or DNA. However, most tools available for teaching biomolecular structures typically operate in two dimensions. Here, we present protocols and pedagogical approaches for using immersive augmented reality (AR) visors, specifically the Microsoft HoloLens, to reinforce learning with large scale 3D holographic structures. We developed a novel workflow to render vividly colored custom biomolecules in AR visors. In addition, we developed AR exercises to review concepts relevant to protein or DNA structure and then implemented the exercises in four different biology and biochemistry courses. Surveys showed that students reported greater interest in biomolecular structures after the exercise. We also highlight some of the advantages and disadvantages of the software and hardware of this upcoming technology.

Developing and applying computational resources for biochemistry education.

Biochemistry is about structure and function, but it is also about data and this is where computers come in. From my time as a graduate student and post doc, whenever I encountered data I thought, "I can work this up by hand, but I think a computer could do a better job." Since that time, I have been working at the interface of biochemistry and computers, by attracting talented students and collaborating with colleagues with complementary skills. This has resulted in several exciting projects: a simulation of 2D electrophoresis and tandem mass spectrometry, the human visualization project, and two different programs that enable biochemists to search protein structures for enzyme active sites: ProMOL (promol.org) and Moltimate (moltimate.appspot.com). The human side of software development for education involved finding the right students and colleagues, communicating effectively across disciplines, building and managing effective teams and the importance of serendipity throughout the process.