Careful decisions must be made about what is presented and how it is represented when visually depicting a molecular process. Which molecules are shown, and how many of each? How fast do molecules move and what is the nature of their motion? Much of the decision-making vis-à-vis representation of these features is dependent upon the communication goals and the intended target audience. In peer-to-peer communication within the scientific research community, a high level of abstraction is acceptable, particularly when communicating increasingly complex data (Johnson and Hertig, 2014). Although visualization of molecular simulation trajectories has been a powerful way for researchers to inspect dynamic data (Kozlıkova et al., 2017; Hildebrand et al., 2019), animation can also serve as a useful tool within the scientific community for guiding and refining research hypotheses (Iwasa, 2015), as well as an opportunity for data integration and knowledge synthesis (McGill, 2022). It is also worth noting however, that the perceived accuracy and usefulness of more delineative molecular animations is influenced by whether experts take them seriously as a medium with which to credibly communicate complex phenomena (Iwasa, 2015; Jantzen et al., 2015).

Beyond sharing research, biologists and educators are also tasked with communicating to more general audiences who lack the requisite background knowledge and subject matter expertise to directly interpret biomolecular data. In the context of undergraduate biology education, a number of frameworks provide specific learning objectives, many of which relate to students’ understanding of molecular structure and function. In particular, the BioCore (Brownell et al., 2014) and BioSkills (Clemmons et al., 2020) guides delineate learning goals that help to articulate the core concepts and competencies outlined in the Vision & Change report (AAAS, 2011; Branchaw et al., 2020). More recently, a set of nationally endorsed granular learning objectives that build upon the existing frameworks have also been proposed (Hennessey and Freeman, 2023). Other frameworks, like BioMolViz (Shor et al., 2021), cater specifically to instructors of biomolecular structure and dynamics. Taken together, these educational resources not only provide context for the relevance of the concepts addressed by the 12 Principles of Molecular Animation, but also help guide specific design decisions. Indeed, communicating the complexity and chaotic richness of the molecular world to students represents a significant challenge, and which information is included or abstracted away in a molecular animation primarily comes down to the learning objectives behind a communication piece.

Understandably, different visual solutions are required to communicate to novice learners. But what is the correct degree of simplification? One might assume that the best visualizations present an unadapted translation of a process, showing events exactly as they might proceed inside a cell. However, this information can be too much, too fast, and too complex, to directly visualize. In order to communicate effectively, the designer of educational visualizations must necessarily simplify, that is, use approximations and interpretive representations and abstractions since the molecular reality is too complex and ephemeral. However, as noted by Johnson and Hertig (2014), representations that are familiar to molecular biologists are only abstract shapes to most other audiences, who often assume incorrectly that such representations have some physical reality. In other words, the more novice the audience, the less one may be able to afford abstraction. When we consistently avoid complexity for the sake of clarity, misconceptions may remain in place or, even worse, may be established or reinforced.

Common misconceptions held by science students relate to the belief that molecules have agency or purpose, which manifests as ligands aiming for receptors and enzymes pursuing or vacuuming up substrate (Tibell and Rundgren, 2010; Jenkinson and McGill, 2012; Jenkinson and McGill, 2013). While most students understand molecular diffusion and Brownian motion in general terms (particularly in an ideal gas scenario), they have a hard time extending those principles to real biological events. In truth, these misconceptions persist among even more proficient learners (upper level undergraduates) and their confidence in these erroneous beliefs increases over time (Gauthier et al., 2019). These misconceptions may be compounded by the way in which molecular scale phenomena are represented.

If, for some subset of educational animations, we prioritize depicting dynamic molecular “realism,” might this influence how students conceptualize intracellular environments and events? Certainly, by devoting attention to fundamental molecular behaviors when designing visuals we may allow for a more robust understanding of the spaces in which these events take place. This is a question that, to-date, remains unanswered, but represents a burgeoning area of inquiry (Cooper et al., 2015; Jenkinson, 2018; Procko et al., 2022). Certainly, an important early step is to identify which concepts could best reflect the dynamic realism of these environments and to create example visuals to help guide animation practitioners in the development of molecular visualizations.

The “12 principles of molecular animation” (described in detail below) are partly inspired by, but also exist in contrast to a more famous set of principles, introduced by Disney animators Frank Thomas and Ollie Johnston in their book “The Illusion of Life” (1981). More recently, this list of concepts was adapted for computer animation by Lasseter (1998), the former CEO of Pixar Animation Studios. These principles are: squash and stretch, anticipation, staging, straight ahead action versus pose to pose, follow through and overlapping action, slow in and slow out, arcs, secondary action, timing, exaggeration, solid drawing, and appeal. Solid drawing does not appear in the computer animation paper, presumably because in this newer medium, visuals are generated in three-dimensional space, greatly alleviating the need for animators to predict how a volume moves through space.

The goals behind these traditional animation principles are multifactorial. They are intended to create more convincing and engaging animations, ensuring that on-screen characters have weight, volume, and inertia, and that the audience can clearly follow actions and events. In contrast, constraining molecular movements to macroscopic physics is not only factually incorrect but, more importantly, misleading to novice audiences. Principles like “slow in/slow out” and “follow through” may make computer-generated movements feel natural, however real molecular motion is far more chaotic. The principle of “arcs” reminds animators that structures such as appendages and projectiles rarely travel in straight lines. It is true that molecules don’t move in straight lines, but neither do they travel in arcs. By applying character animation principles to molecules, are they given anthropomorphic or zoomorphic properties?

The twelve principles of animation, as outlined by Thomas, Johnston, and Lasseter, should not be discarded en masse. They are very useful tools for animators and in many cases separate amateur animation from higher quality pieces. Several of these animation principles aid in guiding the audience, as discussed below. However, the molecular animator should be aware of when and how these principles can be beneficial and when they may obscure the true nature of molecular behaviors. Perhaps the inherent conflict between abstraction and realism is this: molecules do not behave the way we intuitively expect (or at least a novice learner expects), therefore depictions that make use of traditional animation principles belie reality and promote misconceptions. On the other hand, whereas realistic depictions are complex and challenging to follow, is there a balance to incorporating these opposing approaches in molecular animation?

Inspired by Disney’s twelve principles of animation, we have identified twelve concepts (Table 1) that we believe are important to consider when creating molecular animations. Many of the concepts pertain to misconceptions that have been identified in the literature relating to biology education, while others are derived from an environmental scan of commonly misrepresented features of molecular environments (particularly in relation to core concepts in biology education). Many core concepts associated with cell biology have been identified and codified in so-called concept inventories (Ellis, 2001; Garvin-Doxas and Klymkowsky, 2008; Robic, 2010; Newman et al., 2017). Subject areas of particular difficulty for students include protein conformational change and stability (Robic, 2010), diffusion and random molecular motion (Garvin-Doxas and Klymkowsky, 2008; Jenkinson and McGill, 2012; Gauthier et al., 2019), and molecular crowding (Ellis, 2001; Gauthier et al., 2019). Learners have tremendous difficulty coming to terms with the full complexity of the molecular world, given the perceived efficiency of biological systems. Through the design of these principles, we have proposed what we believe to be important considerations for the representation of these concepts.

Each principle is titled with a biological concept, includes a learning objective related to the concept (Table 1), and is illustrated by two short paired animations showing the principle in action (Figure 1). The paired animations use a simplified biological process to demonstrate the principle; one shows the process as it is typically depicted (without incorporating the principle), the other shows the same process with the principle present (links to animations are included in Table 1). As well, we have included in our website (https://sciencevis.ca/index.php/portfolio/molecular-visualization-principles/), actionable suggestions for how each principle might be applied. The aesthetic design of the animations was determined primarily to make the principles as clear as possible. We derived the models from structural data (PDB), but we also simplified the geometry representing molecular surfaces and applied bright, saturated colors. These last two decisions were made to demonstrate that not only highly detailed or “photorealistic” representations would warrant the incorporation of these principles. In each case, we were forced to ignore a subset of the other principles in a given animation on a case by case basis, again to ensure the principle being presented was demonstrated in the clearest way possible. As noted by Tibell and Rundgren (2010), no single visualization can convey all the critical aspects of knowledge, and so, we must be selective in choosing what to include in order to convey specific learning objectives. In a formal learning environment this may require using multiple representations.

We previously argued for organizing, annotating, and presenting the data sources used in creating scientific animations (Jantzen et al., 2015). The properties of elements to which data sources can be linked are structure, appearance, motion, interactions, and populations. In other words, the resources used to inform structure are often distinct from those used for motion, for example, Our principles are most closely related to motions, interactions, and populations. Developing useful resources and workflows for incorporating these kinds of data and concepts is a task both for biologists and molecular animators. To-date, data-driven structural representations are far more prevalent in molecular animation than data-driven representations of molecular motion or interactions. Although the visualization of molecular trajectories issued from simulation methods (like molecular dynamics or other coarse-grained approaches) are common in the scientific research community, these simulation trajectories are seldom used in the context of educational molecular animations.

The molecular animation principles described here are not intended to be prescriptive, but rather are presented to raise awareness for the biophysical properties of molecules, and to encourage the careful consideration of how novice audiences might respond to molecules being shown with more or less agency. When science animators are creating molecular animations, they have many choices to make, and it is our hope that these content creators will carefully examine their learning objectives and make rational choices based on these.

With the twelve principles presented here, we have merely scratched the surface of biophysical concepts that can be visualized. There are certainly other molecular principles for which different representational styles are worth considering. There are also phenomena at larger or smaller scales that are worth careful consideration, for example, the physical quality of lipid membranes at the cellular scale or the oscillations of atoms involved in covalent bonding. We eagerly anticipate dialog on whether our format of pairs of animations used to illustrate these concepts is a useful one.

There is still much to be learned about the role of animation in correcting misconceptions and deepening understanding of molecular biology. Studies undertaken to-date are promising, but there is still much to uncover before general recommendations and statements can be made that will effectively guide the design of dynamic molecular representations. Educational studies measuring the pedagogical effectiveness of molecular animations that incorporate these principles could help validate the importance of such design decisions when trying to address specific learning objectives.