swiss model, protein sequence, mutation function

Question

[Rob]

hello friends I created a swiss model and compared my model to a sequence and found out the mutations in my model(or FASTA file). now I have some questions:

1. how do I know if the changes increase, decrease, or have no impact on the related function? Is it possible by looking at the model or color of the sequence? 3D structure? how?

2. how we would know the most functionally significant mutation?

Answer 1

[Mensur Dlakic]

Presumably you didn't find the mutation, but you introduced it. Swiss-Model doesn't model proteins randomly, but rather based on a user-provided sequence. So if you changed residue 234 into something different from the original PDB file, that is where the mutation is going to be.

Generally speaking, the effect of a mutation can be measured by calculating the energy of the new structure, and comparing it to the native energy. If you are talking about colors used by Swiss-Model, orange and red patches in mutated regions usually mean higher energy, or worse model.

Don't know exactly what you are asking in your last question. Predicting the effects of all the mutations at all possible residues, or even some residues, is very difficult to do accurately. An experiment is usually needed that measures changes in biological function upon mutations, for example something that can detect lower binding affinity.

[Rob]

thanks for responding. I don't have access to energy level. I need to know the mutation effect by looking at and comparing my model and the reference sequence. in Q1. I want to know if any of the changes (compared to reference sequence) predicted to impact ACE2 binding (this virus has binding preference for the amino acids in blue color; the yellow regions are necessary for binding, and the larger the blue letters means the higher affinity for binding) this is the model: https://ibb.co/HCTyP6S and this is the reference sequence: https://ibb.co/N7QmQHX

in Q2, I want to have structural model with the most functionally significant RBD mutation highlighted (most significant mutations in the blue amino acids).