What is the significance and method behind Ramachandran plots?

Question

My PI showed a Ramachandran plot in class today with minimal explanation, but I'm interested in finding out more. I understand that the Ramachandran plot shows the relation between the omega phi and psi angleson either side of an amino acid alpha-carbon, but there are a few further points I'm confused about:

a.) What do these angles describe? Are they just dihedral angles that show translation around the bond-axis?

b.) Why are these angles important beyond the scope of identifying a secondary structure? Can they be used instead to identify the amino acid components, or only higher level structural units?

c.) What kind of instrument is used to collect the data and how are angles on either side of a single alpha-carbon correlated?

Answer 1

Ramachandran plots show the relationship between the phi and psi angles of a protein referring to dihedral angles between the N and the C-alpha and the C-alpha and the C-beta. As an aside, the omega angle between the C-beta and the N tends to be fixed due to pi-pi interactions.

Dihedral Angles

There are limits to possible distributions of phi and psi angles due to steric clashes between the side chains. Furthermore other limitations from higher order structure will result in the adoption of defined phi-psi angles. Using data from solved crystal structures, it can be seen that the dihedral angles will adopt specific conformations in a protein.

RAMACHANDRAN PLOT from Lovell et al.

Furthermore, it can be noted that some of these conformations relate to specific secondary structures. As seen above, peptides in alpha-helices and beta-sheets adopt a even more limited set of phi-psi angles. Certain amino acids like glycine and proline, which differ from from canonical amino acids have an unique Ramachandran plot.

The angles from a Ramachandran plot are useful not only for determining a amino acids' role in secondary structure but can also be used to verify the solution to a crystal structure. Furthermore, it assists with constraining structure prediction simulations and helps with defining energy functions.