Consider, for instance, ribonuclease A, an enzyme that voraciously chops up RNA molecules. In the mid twentieth century scientists figured out how to determine the structure of such proteins using X-rays, and then later using other techniques as well. A protein sample is carefully crystallized and then exposed to an X-ray beam. The X-rays diffract as they pass through the sample and create a complex pattern which indicates the positions of the various atoms in the protein. Here is what the 124 amino acid ribonuclease A protein structure looks like when its many atoms are rendered in a three-dimensional graph:
As you can see, a graph of a protein’s individual atoms doesn’t tell you very much. It looks like, well, a bunch of atoms. But if we step back and consider the protein’s amino acids we see something very different. In a protein, the amino acids are sometimes wound tightly in a helix. Or they can be stretched out into a strand. These two patterns can be detected from the atomic locations and graphed. Here is the ribonuclease A structure again, but this time with these amino acid patterns rendered and their individual atoms left off the graph:
Suddenly a coherent structure is apparent.
Because ribonuclease A is such a voracious eater it sometimes needs to be turned off. Enter the ribonuclease inhibitor. Here are some different renderings of this beautiful horse-shoe shaped protein:
The ribonuclease inhibitor is shaped to dock with ribonuclease A and bring it to a halt. Here are renderings of the two proteins docked together:
Such renderings provide an immediate peek at the phenomena at work. They provide higher level information than do mere measurements. And it is interesting that these renderings were made with graphing tools that know nothing of ribonuclease A or ribonuclease inhibitors, in particular. Computer scientists have developed these powerful rendering tools based on general principles of protein structure. But these tools do nothing without the structural data provided by measurement techniques, such as X-ray diffraction.
So as with electron microscopes and astronomical observatories, these molecular tools create impressive, beautiful and meaningful renderings that are completely dependent on the measurements. The computer scientist creates the tool, but has no idea what rendering might emerge after the raw data are input.
A recent example of the power of rendering, and the importance of stepping back and choosing the right perspective, is the frog embryo’s electric face. If that sounds strange read on, for as one researcher said, “electric face” is the perfect description.
The body electric
Electricity is not just for engineers, it is crucial in biology as well. For instance, a cell contains various ionic compounds which give the cell interior a net charge. And the difference between the intracellular charge and that of the the external environment causes a voltage across the cell membrane. This membrane voltage is crucial in cellular biology. For instance, a wide variety of membrane proteins, such as channels that allow chemical in and out of the cell, are controlled by the membrane voltage. Change the voltage and you suddenly change the state of those proteins and their various actions.
Yes electricity is important in biology, but when Dany Adams left her digital camera and microscope apparatus running overnight, she had no idea what stunning electrical patterns would emerge on the frog embryo she was studying. Watch this video to learn more:
Here is a shorter video of just the embryo:
The video suggests that bioelectric signals presage the morphological development of the face. It also, in an instant, gives a peak at the phenomenal processes at work in biology. As the lead researcher said, “It’s a jaw dropper.”
The frog’s electric face is one of those renderings worth a thousand words. We could make detailed protein measurements showing that evolution cannot even explain how a single protein could have arisen. In fact there are 27 orders of magnitude between evolution’s expectations and reality. And that is going by the evolutionist’s own reckoning (in reality it is 100+ orders of magnitude). Or we could make detailed measurements of mutations and show that unicellular organisms are not likely to evolve spontaneously into elephants.
But the frog’s electric face, in an instant, reminds one of the utter absurdity of evolution. Religion drives science, and it matters.
* Hat tip to bornagain77