[New Model] ESCOTT #51
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…1_Spencer_2017_positive assay
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Hi ProteinGym team!
We would like to contribute to the zero-shot substitution benchmark with our model ESCOTT, presented in PRESCOTT: a population aware, epistatic and structural model accurately predicts missense effect, an updated version of GEMME that introduces structural information in the model.
ESCOTT achieves a weighted average Spearman of 0.473 (computed with
scripts/scoring_DMS_zero_shot/performance_subsitutions.sh) and a simple average of 0.497. Results for the single assays can be found on Zenodo.Due to the many dependencies inherited by GEMME and the additional required installation of DSSP program, we provide a dedicated Docker image with the properly configured environment. It can be pulled from Docker Hub with
To reproduce the results, run
scripts/scoring_DMS_zero_shot/scoring_ESCOTT_substitutions.sh.The script executes
proteingym/baselines/ESCOTT/compute_fitness.pyinside the Docker container, with the mounted data volumes. To run the script withoutrootpermissions, the user has to be added todockergroup.Please let us know if anything is missing, and if the provided solution with Docker matches your requirements.