Basically, you see these 3D representations of specific proteins as a crumple of ribbons-- literally like someone ran multi-colored ribbons though scissors to make curls and dumped it on the floor (like a grade school craft project).
So... I understand that proteins are huge organic molecules composed of thousands of atoms, right? Their special capabilities arise from their structure/shape. So basically the molecule contorts itself to a low energy state which could be very complex but which enables it to "bind?" to other molecules expressly because of this special shape and do the special things that proteins do-- that form the basis of living things. Hence the efforts, like Alphafold, to compute what these shapes are for any given protein molecule.
But what does one "do" with such 3D shapes?
They seem intractably complex. Are people just browsing these shapes and seeing patterns in them? What do the "ribbons" signify? Are they just some specific arrangement of C,H,O? Why are some ribbons different colors? Why are there also thread-like things instead of all ribbons?
Also, is that what proteins would really look like if you could see at sub-optical wavelength resolutions? Are they really like that? I recall from school the equipartition theorem-- 1/2 KT of kinetic energy for each degree of freedom. These things obviously have many degrees of freedom. So wouldn't they be "thrashing around" like rag doll in a blender at room temperature? It seems strange to me that something like that could be so central to life, but it is.
Just trying to get myself a cartoonish mental model of how these shapes are used! Anyone?
The atoms do wiggle around a bit at room temperature (and even more at body temperature), which means that simulating them usefully typically requires sampling from a probability distribution defined by the protein structure and some prior knowledge about how atoms move (often a potential energy surface fitted to match quantum mechanics).
There are many applications of these simulations. One of the most important is drug design: knowing the structure of the protein, you can zoom in on a binding pocket and design a set of drug molecules which might disable it. Within the computer simulation, you can mutate a known molecule into each of your test molecules and measure the change in binding affinity, which tells you pretty accurately which ones will work. Each of these simulations requires tens of millions of samples from the atomic probability distribution, which typically takes a few hours on a GPU given a good molecular dynamics program.