Hi everyone! Marco here, again.
What I will to talk about today is less practical than what others showed in their science course. As I said in the online science exhibition, the topic of this post is biomolecular visualization. If you are not interested in reading, just go there for some more nice pictures!
This will not be an exhaustive lecture on the field, but I will try my best to give a short introduction.
We have been talking about DNA, proteins, origami, sequencing: but how do we see all this? This is a problem as old as the field of molecular biology itself, probably: Watson and Crick used a famous physical model, trying to understand the structure of DNA (Figure 1).
Credit: User: Alkivar, Public domain, via Wikimedia Commons
In general, we can find three essential functions for visualization:
- Synthesis: a model is often created to embody or to integrate experimental observations or an hypothesis
- Analysis: visualization of data or models allows the examination and exploration of them, in order to explain observed phenomena, derive new hypothesis, or to suggest new experiments
- Communication: visualization is often fundamental for the sharing of information and knowledge, both to experts and non-experts
These points are valid for any kind of visualization. As we have seen before, physical models were the first 3D molecular visualization tools (Figure 2). They were difficult and cumbersome to design and produce, but at the same time they were fundamental for discoveries in the ‘50s and 60s. Another important tool for research and education is 2D illustrations, that used to be made by hand (figure 2).
Right: Ribbon schematic of Triosephosphate isomerase, hand-drawn by Jane Richardson. Credits: Jane Richardson, CC BY 3.0 ,via Wikimedia Commons
Today, the field of biomolecular visualization is quite different. Technological advances in computer graphics make it easier and simpler to have better representations of the great amount of data that are produced every day. The field of biomolecular visualization had a lot of influence from graphic design and the field has now a distinguished and common vocabulary. Different representations, with different levels of details, enable researchers to be able to better highlight and describe their data in different context: more detailed visualization for scientific papers, and less detailed for educational purposes, for example (Figure 3).
credits: Tokenzero, CC BY-SA 4.0, via Wikimedia Commons.
While before the only alternative was to manually design or draw molecules and complexes, nowadays even not expert users can easily render a publication-level picture from data. The alternatives one can use are many, all of them pretty good. Some examples are software specifically designed for molecular visualization: VMD, Chimera, PyMol, PMV, etc. (Figure 4). Other software are available as extensions of high-end graphic software: plugins of this kind are available, for example, for Autodesk Maya, Cinema4D, 3DStudioMax, Blender. Other examples are browser-based software, such Illustrate, CellPAINT, oxView.
The giant amount of data that are being generated by techniques like cryo-EM makes it possible to move from the level of single molecules to more complex meso-scales pictures. At this level of detail, it is necessary to use more “artistic licenses”: maybe this is why it is easier turned into art. An example is the work of prof. David Goodsell. He is focused on representing the cellular mesoscale, and he does so using oil painting (Figure 5). His pieces of art are both very enjoyable and scientifically accurate, although something is sacrificed in the name of clarity.
I want to finish this very small lecture talking about the future of biomolecular visualization. The field made giant leaps in the latest years, especially thanks to the availability of a great number of structures, mainly through the Protein Data Bank (PDB). This is a database where data about molecular structures are updated when published: especially thanks to the cryo-EM revolution, the number of structures exploded. These data also became bigger and bigger: this required more and more power for the visualization of structures. Technical improvements are already showing their importance: augmented reality and new ways of looking at and interacting with molecules are probably the future of this field. For now though, we have to be satisfied with looking at beautiful things on a screen (or maybe 3D printed?).
References and further readings:
[1]. Olson, A. J., Perspectives on Structural Molecular Biology Visualization: From Past to Present, JMB, 2018.
[2]. Goodsell, D. S., Franzen, M. A., Herman, T., From Atoms to Cells: Using Mesoscale Landscapes to Construct Visual Narratives, JMB, 2018.
[3]. Goodsell, D.S., Jenkinson, J., Molecular Illustration in Research and Education: Past, Present, and Future, JMB, 2018.
[4]. Cohen, J., Meet the scientist painter who turns deadly viruses into beautiful works of art, Science, 2019.
[5]. Goodsell, D.S., Olson, A.J., Forli, S., Art and Science of the Cellular Mesoscale, Trends in Biochemical Sciences, 2020
[6]. Goddard et al., UCSF ChimeraX: Meeting modern challenges in visualization and analysis, Proeitn Science, 2017
DNA-Robotics 