What's a solvent model? Simply, it's a way we can model processes that take place in solution (we'll use water as an example since it's the most common)
Proteins (large biological molecules) are usually surrounded by water so it's really important that we model these interactions correctly.
(We'll talk a bit more about proteins today)
Explicit model: this is probably the most intuitive, we model the water molecule with 3D coordinates (two hydrogens and an oxygen). This allows us to see what part of the water molecule is interacting with the protein as well as how the water molecules behave.
Implicit model: in this case we don't have any 3D coordinates to describe water molecules. Instead the effect they have on the solute (our protein) are modelled as a continuum. As long as the model reproduces the same properties as we'd expect then we're all good!
Another way to think of it: get in your car, stick your head out of the window, and drive down a road really fast - you'd feel the wind rush past your face (explicit model)
vs
buying a (very) large fan and sticking your face in front of it (implicit model)
In both scenarios you end up with the same result (wind in your face and a questionable hair style) but how you've got there is different.
(and yes I just wanted to put a dog GIF in the previous tweet)
Hybrid model: this is, as the name suggests, a mix of the two! You model some parts of your system explicitly and others implicitly.
Jumping back to explicit (water) models, there are lots of different types to choose from (each with their pros and cons). If you're interested, wikipedia has a good page on them here: en.wikipedia.org/wiki/Water_mod…
(a questionable twitter handle from the orignal post, but we're all friends here 🐱)
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Ok so I had a rather hectic evening, but now let's talk about simulating proteins!
First of all, what's a protein?
Protein's are large biological molecules that are responsible for a myriad of different processes in living things. Feel hungry? In pain? Taste something sweet? Feeling an emotion? All of these things are controlled by a vast array of proteins!
Proteins are amazing! Each one is highly specialised to carry out a specific task, what's incredible is that all proteins are made from the same building blocks called amino acids (AAs).
In the context of QM calculations we have to assess whether the level of theory we are using is appropriate. Perhaps we could use a cheaper ab initio, semi-empirical, or DFT method. The choice depends on the question and system!
Also: basis sets
Without going into too much detail, basis sets help to describe the shape and behaviour of electrons around certain atoms. We can make them really detailed (i.e. model every electron) or just model the important ones (ones involved in bonding etc)
Now that we've (hopefully) recovered from our quick tour of quantum mechanics we'll now look at molecular dynamics (MD) 🧵
At the end of my last thread I mentioned that we often use QM methods when we want high accuracy, but these methods tend to get very computationally expensive as our system size increases.
When studying larger systems the exact QM description of a molecule often isn't necessary and how its dynamics evolve over longer time frames becomes a more relevant.
So, what is computational chemistry?! The field itself is a subfield of chemistry, incorporating aspects of theoretical chemistry / physics and computer simulations. This allows us as scientists to accurately describe (and predict) the properties of atoms and molecules.
Computational chemistry is broad and draws on many areas of science, notably quantum mechanics (QM), classical mechanics, and thermodynamics. We often draw (both directly and indirectly) on all three of these areas to answer a specific scientific question.
For example, let's say we want to describe the breaking of chemical bonds in a molecule during a chemical reaction. Here it is appropriate to use QM to accurately describe the energies involved with the exchange of electrons.
Hi everyone! I'm Will, a computational chemist working in the @choderalab. I'm looking forward to curating this account for the next week, introducing you all to my research, and answering any questions you may have along the way! 🧵
I'm currently based in the UK and (if things go to plan) flying to NYC soon to join the lab after working remotely for the last year(!).
Here's how I'm planning on tweeting this week (but this certainly isn't set in stone) ⬇️
I'll give you an introduction to my field and what areas I work in. We'll cover the broader topic of computational chemistry, some theory, and how we can apply it to biological systems 🧬
You may say that all those don't influence how I perceive food but they do!
We know that smell & taste are influential but how do the others come in?
Touch can be done by our hands if we pick up food but it also accounts for how we perceive texture in our mouth!
But touch is super important in the way we experience food, this is why small children will like to pick up and poke unfamiliar or strange-looking food before they will put it in their mouth!