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--- |
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task_categories: |
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- question-answering |
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- tabular-classification |
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- text-generation |
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language: |
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- en |
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tags: |
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- biology |
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- proteins |
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- amino-acids |
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size_categories: |
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- 100K<1M |
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--- |
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# Protein Data Stability - Single Mutation |
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This repository contains data on the change in protein stability with a single mutation. |
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## Attribution of Data Sources |
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- **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](https://www.nature.com/articles/s41586-023-06328-6) |
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- **Dataset Link**: [Zenodo Record](https://zenodo.org/record/7992926) |
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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. |
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## Sample Protein Stability Data [subset of 4 columns] |
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| Base Protein Sequence | Mutation | ΔΔG_ML | Classification | |
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|-------------------------------------------------------------|----------|--------------------|-----------------| |
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| FDIYVVTADYLPLGAEQDAITLREGQYVEVLDAAHPLRWLVRTKPTKSSPSRQGWVSPAYLDRRL | R63W | -0.2010871345320799 | neutral | |
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| FDIYVVTADYLPLGAEQDAITLREGQYVEVLDAAHPLRWLVRTKPTKSSPSRQGWVSPAYLDRRL | R63Y | 0.0194756159891467 | neutral | |
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| FDIYVVTADYLPLGAEQDAITLREGQYVEVLDAAHPLRWLVRTKPTKSSPSRQGWVSPAYLDRRL | R63F | 0.7231614929744659 | stabilising | |
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| FDIYVVTADYLPLGAEQDAITLREGQYVEVLDAAHPLRWLVRTKPTKSSPSRQGWVSPAYLDRRL | R63P | -0.3668887752897785 | neutral | |
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| FDIYVVTADYLPLGAEQDAITLREGQYVEVLDAAHPLRWLVRTKPTKSSPSRQGWVSPAYLDRRL | R63C | -0.5317304030261774 | destabilising | |
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## Dataset Structure |
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This dataset focuses on the differential deltaG of *unfolding* (mutation minus base) of various protein mutations and is derived from stability measurements (free energy of unfolding) measured by two proteases, trypsin and chymotrypsin. |
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### Columns (Trypsin): |
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- **name**: The name of the protein variant. |
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- **dna_seq**: The DNA sequence encoding the protein variant. |
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- **log10_K50_t**: The log10 of the K50 value measured with trypsin (a measure of stability). |
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- **log10_K50_t_95CI_high**: The upper bound of the 95% confidence interval for log10_K50_t. |
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- **log10_K50_t_95CI_low**: The lower bound of the 95% confidence interval for log10_K50_t. |
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- **log10_K50_t_95CI**: The width of the 95% confidence interval for log10_K50_t. |
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- **fitting_error_t**: A measure of error between the model and data for trypsin. |
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- **log10_K50unfolded_t**: The predicted log10 K50 value for the unfolded state with trypsin. |
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- **deltaG_t**: The ΔG stability calculated from the trypsin data. |
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- **deltaG_t_95CI_high**: The upper bound of the ΔG confidence interval from trypsin. |
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- **deltaG_t_95CI_low**: The lower bound of the ΔG confidence interval from trypsin. |
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- **deltaG_t_95CI**: The width of the ΔG confidence interval from trypsin. |
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### Columns (Chymotrypsin): |
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- **log10_K50_c**: Analogous to `log10_K50_t`, but for chymotrypsin. |
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- **log10_K50_c_95CI_high**: Upper bound of the 95% CI for `log10_K50_c`. |
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- **log10_K50_c_95CI_low**: Lower bound of the 95% CI for `log10_K50_c`. |
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- **log10_K50_c_95CI**: Width of the 95% CI for `log10_K50_c`. |
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- **fitting_error_c**: A measure of error between the model and data for chymotrypsin. |
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- **log10_K50unfolded_c**: Predicted log10 K50 value for the unfolded state with chymotrypsin. |
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- **deltaG_c**: ΔG stability calculated from the chymotrypsin data. |
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- **deltaG_c_95CI_high**: Upper bound of the ΔG CI from chymotrypsin. |
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- **deltaG_c_95CI_low**: Lower bound of the ΔG CI from chymotrypsin. |
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- **deltaG_c_95CI**: Width of the ΔG CI from chymotrypsin. |
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### Combined Data: |
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- **deltaG**: The combined ΔG estimate from both trypsin and chymotrypsin. |
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- **deltaG_95CI_high**: Upper bound of the combined ΔG confidence interval. |
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- **deltaG_95CI_low**: Lower bound of the combined ΔG confidence interval. |
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- **deltaG_95CI**: Width of the combined ΔG confidence interval. |
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### Protein Sequencing Data: |
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- **aa_seq_full**: The full amino acid sequence. |
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- **aa_seq**: A (sometimes shortened) amino acid sequence representing the protein. |
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- **mut_type**: The type of mutation introduced to the protein. |
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- **WT_name**: Name of the wild type variant. |
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- **WT_cluster**: Cluster classification for the wild type variant. |
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- **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). |
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- **base_aa_seq**: The base sequence of the protein before the mutation. |
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### Derived Data: |
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- **log10_K50_trypsin_ML**: Log10 value of K50 derived from a machine learning model using trypsin data. |
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- **log10_K50_chymotrypsin_ML**: Log10 value of K50 derived from a machine learning model using chymotrypsin data. |
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- **dG_ML**: ΔG derived from a machine learning model that makes use of stability measurements from both proteases. |
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- **ddG_ML**: Differential ΔG (mutation minus base) derived from a machine learning model. |
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### Classification: |
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- **Stabilizing_mut**: Indicates whether the mutation is stabilizing or not. |
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- **pair_name**: Name representation combining the wild type and mutation. |
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- **classification**: Classification based on `ddG_ML`: |
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- Rows below -0.5 standard deviations are classified as 'destabilising'. |
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- Rows above +0.5 standard deviations are classified as 'stabilising'. |
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- Rows between -0.5 and 0.5 standard deviations are classified as 'neutral'. |
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This dataset offers a comprehensive view of protein mutations, their effects, and how they relate to the stability measurements made with trypsin and chymotrypsin. |
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### Understanding ΔG (delta G) |
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ΔG is the Gibbs free energy change of a process, dictating whether a process is thermodynamically favorable: |
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- **Negative ΔG**: Indicates the process is energetically favorable. For protein unfolding, it implies the protein is more stable in its unfolded form. |
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- **Positive ΔG**: Indicates the process is not energetically favorable. In protein unfolding, it means the protein requires energy to maintain its unfolded state, i.e. it is stable in folded form. |
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The **delta delta G** (ΔΔG) represents the deltaG of the mutation compared to the base protein: |
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- **Positive ΔΔG**: Suggests the mutation enhances protein stability. |
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- **Negative ΔΔG**: Suggests the mutation decreases protein stability. |
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### Data Cleanup and Validation: |
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1. Filtering: The dataset has been curated to only include examples of single mutations. |
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2. Sequence mutations were extracted from the row names. Base mutations are labelled as 'base'. |
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3. Consistency Check: Only rows with a consistent 'mutation', aligned with both the base and mutated sequences from the raw data, have been retained. |