The many faces of biology

Hej! I’m Yossa, a computational biophysicist at campus Huddinge. For this first post I will survey the vast landscape of biology and tell you a little bit about me and my field.

Biology has experienced rapid growth in the past few decades. Consider that Watson and Crick only discovered the structure of DNA in 1953 and compare it to the gene editing tools at our disposal now, a mere 63 years later. If the golden age of physics was during early 1900s during the heyday of relativity and quantum mechanics (the period is arguable, but I am very partial towards quantum mechanics), the golden age of biology is certainly upon us, here and now, we are in the middle of it.

This rapid development naturally makes biology a very diverse field. In the past, the sciences were known collectively as “natural philosophy”. The subsequent accumulation of our knowledge is such that it is more tractable to split the natural philosophy to physics, chemistry, and biology, according at the scale of magnitudes they pertain. There is only so much one can teach and learn in the 4 years of Bachelor’s, ya know? And further splitting is due. And indeed today one can readily choose to major in marine biology, nutrition, biochemistry, molecular biology, bioinformatics, and so on.

Let’s imagine the distribution of biologists along the scale of magnitude of their research subjects. It may look something like this:


What is the image that you associate with the word ‘biologist’? You might have an image of a stereotypical biologist in mind, a person in white lab coat at a spotless bench, holding a micropipette, smiling beatifically as she pipettes some mysteriously coloured liquids, and double-helices of DNA are floating gently in the background… no wait, that’s from the front cover of the catalogue from the vendor you talked to just to get a free pen.

But really now, that’s the kind of picture you get when you Google image ‘biologist’. So now I want to give you a different picture of how a biologist (namely, me) in different part of the distribution looks like. You’d probably have gathered that I don’t work at the bench, but in front of the computer, performing some kind of calculations; that explains the ‘computational’ part.

What about the ‘biophysics’ part? You are probably familiar with the biochemist, who deals with biomolecules at chemical level. She would see a protein as a chain of amino acids which various interactions between the residues. A cell biologist, operating at a higher scale of magnitude, would see a protein as a blob of certain shape, which probably would bind with other protein with fits its shape. The cell biologist would not be so much concerned with how water molecules distribute themselves along the surface of this protein, for example; that is the domain of biochemistry. Now if you go down the scale a bit from biochemistry, you are in the domain of biophysics.

The biophysicist sees a protein as a collection of atoms, governed by Newtonian mechanics like most other physical objects (and at this scale and smaller, quantum mechanics starts to get important as well). The biophysicist is interested in the various conformations a certain protein can take; which conformation is of lowest energy; if that protein is binding to another, what the free energy of binding is; whether the binding free energy is primarily enthalpic or entropic; and so on. All these interesting quantities are not always experimentally tractable and/or affordable to measure. Biophysical experiments sometimes need expensive equipments like NMR spectrometer or ultrafast laser spectrometer. Even when one can afford it, there are quantities that are impossible to be measured with the current limitations of the instruments. Computational methods, then, are meant to fill this gap.

To build the models for our simulations, first we need a set of parameters of the atoms, their connectivity, the bonds, the angles, and the dihedrals (this set of parameters is what we call a force field). We also need a software suite that calculate the potential and kinetic energies and integrate the Newton’s equation of motion to make the molecules jiggle around (or, to sample the conformational space, if you want to be fancy). Are we ready to simulate now? Not quite yet. We have the parameters and the physical laws, but we also need the 3D coordinates of the atoms. This is where high resolution structures resolved by X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy come in handy (also neutron diffraction, but they are pretty rare since one needs a nuclear reactor for neutron source). These coordinates are publicly accessible in Protein Data Bank and a few other repositories.

So this is basically what I do: I model a biomolecule, taken from existing structure or otherwise, run molecular dynamics simulation to do sample quantities of interest and then postprocess the data. The data is amenable to probability theory and other wonderful tools of statistical mechanics. Quite a different kind of biologist, isn’t it? Our field is actually unique that way, in that it is an intersection between physics, chemistry, and biology.

So that’s it from me for now. Besides my own field, the topics that interest me are structural biology, medicinal chemistry, drugs and the pharmas, (I am a chemist by training) and also history and philosophy of science, as well as science communication and education. I might have interesting things to say about those, so stay tuned for my posts if these are your cup of tea.

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