README.md

metadata

task_categories:
  - text-generation
tags:
  - biology
  - protein
  - mutation

RipplePLM Dataset

This dataset accompanies the paper RipplePLM: Structural and Property Decoupling for Protein Mutation Effect Generation. It contains protein mutation data for training and evaluating models that generate natural-language descriptions of protein mutation effects.

Code and usage instructions are available at https://github.com/Lyu6PosHao/RipplePLM.

The dataset is organized into two splits (structural_split/ and temporal_split/), each containing train_with_label.csv, val_with_label.csv, and test_with_label.csv.

The columns include:

• entry: Protein ID and mutation, e.g. P12345-A123B; residue positions are 1-based.
• protein1: Wild-type amino acid sequence.
• protein2: Mutant sequence; reconstructed from entry if absent.
• function: Wild-type protein function used as input context.
• uniprot_description: UniProt mutation-effect description.
• GPT_description: Additional generated mutation-effect description.
• all_description: Description field used to filter samples with missing annotations.
• ephod_label: Integer class label for pH.
• pptstab_label: Integer class label for thermostability.

The reference text combines uniprot_description and GPT_description. Samples missing function or all_description are omitted.