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common_sensei t1_jbswz7i wrote

Proteins can* be very rigid, and that rigidity comes mostly from four forces:

  • hydrophobic and hydrophilic interactions (some amino acids will stay away from water and twist to the inside of the protein, others will be attracted to the water and be on the outside of the protein)

  • hydrogen bonding in the protein (some substituents make strong dipole interactions with each other, these forces also exist in the backbone of the protein, making sub-structures)

  • electrostatic interactions (parts of the protein carry positive and negative charges, which help hold the protein together)

  • disulfide bridges formed from two cysteines which are actual covalent bonds between two parts of the chain

Here's the important part: when something binds to the protein, the electrical and chemical environment around the protein changes, and the protein will* change shape. For example, if a signal peptide with a lot of charged side chains lands on the receptor site, amino acids with charged side chains in the receptor will try to twist towards or away from it. This will change the shape of the protein, potentially opening new receptor sites or setting off other signalling.

A great example is this animation of a G-protein coupled receptor. Watch it change shape as things bind and unbind to it (the good part starts at 4:15) https://youtu.be/ZmrDWIeX0Tc

*Per /u/danby, below, the hydrogen bonding network is quite flexible, so we can't really call the protein a rigid body.

*Again, per /u/danby, there are examples of binding without structural change.

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danby t1_jbtmzen wrote

I don't think we'd regard proteins as rigid bodies. Lots of what makes working with protein structure hard is that we don't have a good way of modelling the dynamics of proteins. The hydrogen bonding network is quite flexible.

Ligand induced structural change is indeed an important type of ligand binding but there are many examples of binding without structural shifts.

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CocktailChemist t1_jbts314 wrote

To add to this, there’s an iterative set of interactions where ligand binding induces conformational changes on the receptor, which induces some conformational change on the ligand, and so on. That’s why in silico docking that assumes a rigid receptor often gives spurious results that don’t line up with experimentally measured binding affinities. It’s problematic since reductions in receptor degrees of freedom can impose a significant entropic cost, which can have a major influence on the Gibb’s free energy of the binding event.

We’re getting better at modeling those interactions than we used to be, but it’s still extremely challenging. The best efforts start with a large collection of known binding affinities with different ligands, which can be used to constrain the system.

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danby t1_jbtvg22 wrote

A big issue is the lack of data. There are lots of crystal structures of proteins and lots of structures with ligands bound but very little data of the intermediary states along the way to binding.

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slashdave t1_jbvxji0 wrote

The intermediate states are irrelevant. It is only the free-energy difference of the two states (bound and unbound) that matter.

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danby t1_jbz36wk wrote

> The intermediate states are irrelevant

Irrelevant to what? They seem pretty relevant if we're studying protein dynamics.

> It is only the free-energy difference of the two states (bound and unbound) that matter.

It's the only information that matters to what? If we're studying protein dynamics can you predict if a protein undergoes a change in structure form the change in free energy alone?

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LitLitten t1_jbtpl91 wrote

Here’s hoping for further developments with cryo-electron microscopy. The largest benefit imo being it doesn’t require lengthy crystallization waiting periods.

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danby t1_jbtvjti wrote

The flash freezing certainly/hopefully offers a path to capturing many intermediate states for proteins as they Bind small molecules

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common_sensei t1_jbtr6n6 wrote

Good addition, I'll add a clarifying note to my post. I have a neuroscience background so all the receptor stuff I learned about was based on structural change.

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slashdave t1_jbvxc0t wrote

Molecular dynamics is adequate in most simple cases. You could say we are limited with what kind of computing power we can apply in complex systems.

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danby t1_jbz2kzo wrote

Why on earth would we be only interested in simple cases?

MD is fine in many cases (very, very good in some) but it is absolutely not sufficient to fully model and understand the dynamics of proteins. We know the forcefields we have are lossy and not great for many applications when it comes to proteins. Simulations of long time spans or large protein rearrangements are generally very poor.

> You could say we are limited with what kind of computing power we can apply in complex systems.

Well yeah we limited there.

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slashdave t1_jbz9uck wrote

>Why on earth would we be only interested in simple cases?

We aren't. The statement "we don't have a good way of modeling the dynamics of proteins" isn't correct. If you want to amend that to "complex systems", you might have an argument, but there are also accelerated MD methods that are quite effective.

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