Using Masked Marginal Score for ESM-2 as a Scoring Method about evoprotgrad

[pemami4911]

Hi, this could definitely be supported in EvoProtGrad with some minor modifications to the code in the HuggingFaceExpert class.

The masked marginal score uses the masked mutated protein sequence as input to the protein language model (PLM) and uses the (unmasked) mutations to compute the score. This could be supported by extending this __call__ function

EvoProtGrad/evo_prot_grad/experts/base_experts.py

Line 117 in fda1d39

class HuggingFaceExpert(Expert):

to support passing auxiliary information about what the mutations are at the masked locations in the input (e.g., passing the the unmasked sequence).

Allowing the HuggingFaceExpert to have its score function be selected in an argument in the constructor seems reasonable as well, that way the __call__ function can select between different score functions on the fly.

[Amelie-Schreiber]

Would you be up for working on this with me? If so, what is the best way to get in touch?

[pemami4911]

Definitely; I will be attending NeurIPS all next week so it's unlikely I'll have time to get to this until after that.
In general, I am happy to review and accept pull requests too! 🙂

Feel free to send me an email at [email protected] to get in touch offline.