metadata

task_categories:
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  - tabular-classification
  - text-generation
language:
  - en
tags:
  - biology
  - proteins
  - amino-acids
size_categories:
  - 100K<1M
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Protein Data Stability - Single Mutation

This repository contains data on the change in protein stability with a single mutation.

Attribution of Data Sources

Primary Source: Tsuboyama, K., Dauparas, J., Chen, J. et al. Mega-scale experimental analysis of protein folding stability in biology and design. Nature 620, 434–444 (2023). Link to the paper
Dataset Link: Zenodo Record

As to where the dataset comes from in this broader work, the relevant dataset (#3) is shown in dataset_table.jpeg of this repository's files.

Sample Protein Stability Data

Base Amino Acid Sequence	Mutation	ddG_ML	Classification
DEIHIHFNGVTIEFRGLTEEAKKALEEAIKRGASEEELKELARRLIK	base	-0.0675543480388345	neutral
DEIHIHFNGVTIEFRGLTEEAKKALEEAIKRGASEEELKELARRLIK	D1Q	-0.0162349479755414	neutral
DEIHIHFNGVTIEFRGLTEEAKKALEEAIKRGASEEELKELARRLIK	D1E	-0.1402534094665108	neutral
DEIHIHFNGVTIEFRGLTEEAKKALEEAIKRGASEEELKELARRLIK	D1N	0.0126650189159422	neutral
DEIHIHFNGVTIEFRGLTEEAKKALEEAIKRGASEEELKELARRLIK	D1H	0.1970434798619962	neutral

Dataset Structure

The dataset focuses on the differential deltaG (mutation minus base) of various protein mutations.

Base Protein Sequence (aa_seq): A (sometimes shortened) amino acid sequence.
Mutation: Represented as a combination of amino acid and its position (e.g., F10N indicates changing the 10th amino acid (F) in a sequence for N).
delta deltaG (ddG_ML): Derived from a model that makes use of stability measurements measured by two proteases, trypsin and chymotrypsin.
Classification: Classification is done purely on the basis of ddG. The standard deviation of ddG in the dataset is measured and: -- Rows above 0.5 standard deviations are classified as 'destabilising' -- Rows below -0.5 standard deviations are classified as 'stabilising' -- Rows between -0.5 and 0.5 standard deviations are classified as 'neutral'

Understanding ΔG (delta G)

ΔG is the Gibbs free energy change of a process, dictating whether a process is thermodynamically favorable:

Negative ΔG: Indicates the process is energetically favorable. For protein folding, it implies the protein is stable in its folded form.
Positive ΔG: Indicates the process is not energetically favorable. In protein folding, it means the protein requires energy to maintain its folded state.

The delta delta G (ΔΔG) represents the deltaG of the mutation compared to the base protein:

Positive ΔΔG: Suggests the mutation decreases protein stability.
Negative ΔΔG: Suggests the mutation enhances protein stability.

Data Cleanup and Validation:

Filtering: The dataset has been curated to only include examples of single mutations.
Consistency Check: Only rows with consistent mutation indication, aligned with both the base and mutated sequences, have been retained.