This answer is from common knowledge rather than specific infield expertise. The question could be more expertly answered by other members.

If you really want to pursue this type of calculation its possible that something like `INPS-MD` *de novo* -> protein structure stability from variants will provide an answer. Intuitively I don't think its cool, just my opinion. In my opinion an experimentally derived structure is required as the basis for your calculation, where you want to consider the impact of an amino acid mutation.

Its important to separate *de novo* prediction from variant prediction. Alphafold is *de novo* prediction. What you are looking at is structure stability from a variant (see Summary). Thats my core answer, these different calculations. To look to explain this more clearly ... 

The applications you want for variant stability calculations are DUET (2014) and [INPS-MD][1] (2016). Just to reiterate a strongly recommended starting point is an experimentally derived protein structure.

The webserves are here, 

* [http://structure.bioc.cam.ac.uk/duet][2]
* [https://inpsmd.biocomp.unibo.it/inpsSuite][3]

I personally don't know `Alphafold` but understand its predecessor's and guess they'll be lots of deep learning involved in *de novo* prediction of `Alphafold`. The basis of the predecessor's calculations firstly are *de novo* prediction and secondly can miss the impact of variants if they are not directly involved in the core-algorithm. Its about the core non-linear relationships, identifying which amino acids are interacting considering all available homologous amino acid within a database. The calculation can be predict local interactions with extreme accuracy, but its a prediction. 

In contrast DUET and INPS-MD amongst a lot of other similar programs consider the property shift of an individual amino acid in relation to its immediate local stereo-chemical environment and measured by a shift of free-energy. 

Essentially, these are two sets of very different calculations.

**Summary** The problem I intuitively see is if *de novo* prediction in any form is then used, okay they are very good, but they're just predictions. Variant structural prediction are also just predictions  which are very widely respected. Stacking *de novo* prediction onto predicting protein structure stability resulting from variants has a lot of scope error, especially if there was some hidden non-linear effect.

There could be additional issues because the *de novo* stuff I know doesn't predict the local distances, so its not really in a position to make further calculations with accuracy.

  [1]: https://academic.oup.com/bioinformatics/article/32/16/2542/1743481?login=false
  [2]: http://structure.bioc.cam.ac.uk/duet
  [3]: https://inpsmd.biocomp.unibo.it/inpsSuite