If MD simulations converges to Boltzmann distributions ρ∼exp(−βϵ) after sufficiently long time why do we need MD simulations, as all the macroscopic quantities can be computed from the Boltzmann distribution itself. This question I am asking for short peptides of sequences of few amino acids.(tripeptide, tetrapeptide etc).
Article The intrinsic conformational propensities of the 20 naturall...
For instance in the given above (link) paper, they are using MD to generate Ramachandran distributions of conformations of pentapeptide at a constant temperature. So this should obey statistical mechanics. If it is so, then this should satisfy Boltzman distributions.So I should be able to write down the distributions using boltzmann weight as follows,
ρ({ϕi,ψi})∼exp(−βV({ϕi,ψi}))
.Here, all set of Ramachandran angle coordinates of the pentapeptides is given by {ϕi,ψi}{ϕi,ψi}.
Why should I run MD to get the same distributions?
Maybe this article will guide you
https://www.sciencedirect.com/science/article/pii/S0006349503750905
As Behnam Farid
pointed out, you cannot know all the relationships (the functional form V({ϕi,ψi})) between the different amino acids (sterical clashes, interactions based on charges or hydrophobicity) to predict the energetically favorable combinations of phi and psi and hence need to sample them. The state distribution is affected by the amino acid sequence, may differ with the force fields and simulations methods, does depend on the solvent (ions etc.) and temperature.Have a look here to see how complex the conformational space of small peptides (13-15) can already be:
Article Replica Based Protein Structure Sampling Methods: Compromisi...
Article Replica-Based Protein Structure Sampling Methods II: Advance...
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