Visualizing mutation

I’ve illustrated the coronavirus spike protein a lot over the last few years, including its mutations. In the process, I made many decisions about how to show mutations, and want to share my rationale. First, it’s important to review how we describe mutations – they’re identified in reference to an original, unmutated reference sequence. So, for example: This poses a challenge – do we show the structure of the mutated spike? Or the structure of the Read more…

Model of estrogen receptor binding to DNA strand inspired by AlphaFold. Disordered linkers shown between rigid estrogen receptor domains.

AlphaFold and Molecular Visualization

What is AlphaFold? Predicting protein structures based on their amino acid sequence has been a scientific dream for decades. AlphaFold, an artificial intelligence (AI) system developed by DeepMind, makes that dream a reality. It predicts a protein’s 3D structure based solely on its primary structure.  This video from one of DeepMind’s research scientists, Jonas Adler, shows visually how AlphaFold works to iteratively predict and refine a structure. Some of the graphics are really cool too. Read more…

Falconieri Visuals on the Cover of Nature Materials

Falconieri Visuals artwork of a platinum-gold catalyst studied by the Argonne National Lab’s Stamenkovic lab is on the cover of the November 2020 Nature Materials Issue. Check it out here: Platinum dissolution suppression Based on Lopes PP, Li D, Lv H, et al. Eliminating dissolution of platinum-based electrocatalysts at the atomic scale. Nat Mater. 2020;19(11):1207-1214. doi:10.1038/s41563-020-0735-3

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