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---
dataset_info:
features:
- name: input_id_x
sequence: int64
- name: input_id_y
sequence: int64
splits:
- name: test
num_bytes: 1087504
num_examples: 474
- name: valid
num_bytes: 1124160
num_examples: 474
- name: train
num_bytes: 65391887792
num_examples: 17070828
download_size: 810671738
dataset_size: 65394099456
license: mit
task_categories:
- text-generation
tags:
- biology
size_categories:
- 10M<n<100M
---
# Dataset Card for "ProstT5Dataset"
* **Contributors:** Michael Heinzinger and Konstantin Weissenow, Joaquin Gomez Sanchez and Adrian Henkel, Martin Steinegger and Burkhard Rost
* **Licence:** MIT
## Table of Contents
- [Overview](#overview)
- [Dataset Description](#dataset-description)
- [Data Collection and Annotation](#data-collection-and-annotation)
- [Data Splits](#data-splits)
- [Dataset Structure](#dataset-structure)
- [Data Fields](#data-fields)
- [Data Instances](#data-instances)
- [Data Considerations](#data-considerations)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Overview
The ProstT5Dataset is a curated collection of *tokenized* protein sequences and their corresponding structure sequences (3Di).
It is derived from the [AlphaFold Protein Structure Database](https://alphafold.ebi.ac.uk/) and includes various steps of clustering and quality filtering.
To capture 3D information of the sequence, the [3Di structure string representation](https://www.nature.com/articles/s41587-023-01773-0#Sec2) is leveraged. This format
captures the spatial relationship of each residue to its neighbors in 3D space, effectively translating the 3D information of the sequence.
The sequence tokens are generated using the [ProstT5 Tokenizer](https://huggingface.co/Rostlab/ProstT5).
## Data Fields
- **input_id_x** (3Di Tokens): Corresponding tokenized 3Di structure representation sequences derived from the proteins.
- **input_id_y** (Amino Acid Tokens): Tokenized amino acid sequences of proteins.
## Dataset Description
We compare basic protein properties (sequence length, amino acid composition, 3Di-distribution) between our
dataset (training, validation, test sets) and proteins obtained from the [Protein Data Bank (PDB)](https://www.rcsb.org/). Key findings include similar amino acid distributions across datasets,
an overrepresentation of certain 3Di-tokens (d, v, p) and helical structures in AlphaFold2 predictions compared to PDB, and a tendency for shorter protein
lengths in this dataset (average 206-238) relative to PDB proteins (average 255). The analysis also highlights the relationship between
3Di states and secondary structures, with a notable distinction in strand-related tokens between datasets.
## Data Collection and Annotation
The dataset began with the AlphaFold Protein Structure Database , undergoing a two-step clustering process and one step of quality filtering:
1. *First Clustering:* 214M UniprotKB protein sequences were clustered using MMseqs2, resulting in 52M clusters based on pairwise sequence identity.
2. *Second Clustering:* Foldseek further clustered these proteins into 18.8M clusters, expanded to 18.6M proteins by adding diverse members.
3. *Quality Filtering:* Removed proteins with low pLDDT scores, short lengths, and highly repetitive 3Di-strings. The final training split contains 17M proteins.
## Citation
```
@article{heinzinger2023prostt5,
title={ProstT5: Bilingual language model for protein sequence and structure},
author={Heinzinger, Michael and Weissenow, Konstantin and Sanchez, Joaquin Gomez and Henkel, Adrian and Steinegger, Martin and Rost, Burkhard},
journal={bioRxiv},
pages={2023--07},
year={2023},
publisher={Cold Spring Harbor Laboratory}
}
```
## Tokens to Character Mapping
| Amino Acid Representation | 3DI | Special Tokens |
|---------------------------|-----------|--------------------|
| 3: A | 128: a | 0: \<pad\> |
| 4: L | 129: l | 1: \</s\> |
| 5: G | 130: g | 2: \<unk\> |
| 6: V | 131: v | 148: \<fold2AA\> |
| 7: S | 132: s | 149: \<AA2fold\> |
| 8: R | 133: r | |
| 9: E | 134: e | |
| 10: D | 135: d | |
| 11: T | 136: t | |
| 12: I | 137: i | |
| 13: P | 138: p | |
| 14: K | 139: k | |
| 15: F | 140: f | |
| 16: Q | 141: q | |
| 17: N | 142: n | |
| 18: Y | 143: y | |
| 19: M | 144: m | |
| 20: H | 145: h | |
| 21: W | 146: w | |
| 22: C | 147: c | |
| 23: X | | |
| 24: B | | |
| 25: O | | |
| 26: U | | |
| 27: Z | | | |