• LassoESM

  • LassoESM_pretraining.py: Pretraining Lasso Peptide-Specific Language Model
  • get_embeddings_LassoESM: extract embeddings for peptide variants in training set from LassoESM/PeptideESM/VanillaESM, then feed them into various downstream classification models

• Downstream task 1: substrate_tolerance_prediction

  • hyperparameter_optimization_ML_FusA.py: grid-search for hyperparameters of downstream classification models
  • downstream_models_performance_diff_3embs.py: compare downstream model performance with different embeddings (VanillaESM, PeptideESM, LassoESM)
  • diff_training_size.py: evaulate downstream model performance using different training size
  • cal_uncertainty.py: explore uncertainty of classification model output

• Downstream task 2: cycalse_peptide_pair_prediction

  • generate_negative_cyclase_peptide_pairs.py: generate the synthetic cyclase-peptide pairs (negative samples)
  • predict_cyclase_peptide_pairs: a general model (MLP) to predict cyclase(embedded by VanillaESM)-peptide(embedded by LassoESM) pairs
  • predict_cyclase_peptide_pairs_with_CrossAttention: add a cross-attention layer, where lasso peptide embeddings reweight its corresponding cyclase embeddings
  • predict_non_natural_cyclase_peptide_pairs.py: use the trained cyclase-peptide pair prediction model to assess the compatibility of FusC with other predicted naturally occuring lasso peptides

• Downstream task 3: antimicrobial_activity_prediction

  • get_embeddings_for_Ubonodin.py: extracting embeddings for Ubonodin variant sequences from LassoESM/PeptideESM/VanillaESM models
  • antimicrobial_activity_prediction_for_Ubonodin.py: predict the antimicrobial activity of Ubonodin variant sequences
  • get_embeddings_for_Klebsidin.py: extracting embeddings for Klebsidin variant sequences from LassoESM/PeptideESM/VanillaESM models
  • antimicrobial_activity_prediction_for_Klebsidin.py: predict the antimicrobial activity of Klebsidin variant sequences

To set up the environment for this project, use the provided environment.yml file. This file contains all necessary dependencies.

• Xuenan Mi - xmi4@illinois.edu