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DATASET-CAPE-RhlA-seqlabel

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train · 1.59k rows

protein stringlengths 6 6	label float64 0.02 3.35
RAQLSQ	1
AAQLSQ	3.228
CAQLSQ	2.17
DAQLSQ	1.759
EAQLSQ	1.531
FAQLSQ	1.524
GAQLSQ	1.05
HAQLSQ	0.939
IAQLSQ	0.984
KAQLSQ	2.541
LAQLSQ	3.351
MAQLSQ	1.45
NAQLSQ	2.417
PAQLSQ	2.451
QAQLSQ	0.67
SAQLSQ	1.439
TAQLSQ	2.533
VAQLSQ	0.327
WAQLSQ	1.241
YAQLSQ	1.627
RFQLSQ	0.533
RGQLSQ	0.038
RLQLSQ	0.11
RMQLSQ	0.751
RNQLSQ	0.034
RPQLSQ	0.283
RRQLSQ	0.081
RSQLSQ	0.425
RTQLSQ	0.534
RVQLSQ	0.467
RYQLSQ	0.072
RAALSQ	1.508
RACLSQ	1.224
RADLSQ	0.476
RAELSQ	0.693
RAFLSQ	0.506
RAGLSQ	0.609
RAHLSQ	0.765
RALLSQ	1.33
RANLSQ	0.059
RAPLSQ	0.074
RARLSQ	1.595
RASLSQ	0.13
RATLSQ	1.752
RAVLSQ	1.558
RAWLSQ	0.534
RAYLSQ	1.74
RAQASQ	3.068
RAQCSQ	2.773
RAQDSQ	2.385
RAQESQ	2.346
RAQFSQ	1.549
RAQGSQ	0.803
RAQHSQ	1.629
RAQISQ	3.24
RAQKSQ	2.792
RAQNSQ	0.578
RAQPSQ	0.168
RAQQSQ	2.375
RAQRSQ	1.386
RAQTSQ	3.035
RAQVSQ	2.606
RAQWSQ	1.206
RAQYSQ	1.307
RAQLAQ	2.679
RAQLCQ	2.421
RAQLDQ	0.07
RAQLEQ	0.114
RAQLFQ	1.152
RAQLGQ	0.832
RAQLHQ	1.006
RAQLKQ	2.78
RAQLLQ	1.842
RAQLMQ	0.053
RAQLNQ	0.693
RAQLPQ	0.158
RAQLQQ	1.323
RAQLRQ	1.619
RAQLTQ	1.8
RAQLVQ	1.676
RAQLWQ	0.166
RAQLYQ	0.588
RAQLSA	3.072
RAQLSC	1.114
RAQLSD	1.391
RAQLSE	0.745
RAQLSF	0.712
RAQLSG	1.097
RAQLSH	0.981
RAQLSI	1.08
RAQLSK	2.435
RAQLSL	1.59
RAQLSM	0.089
RAQLSN	2.122
RAQLSP	0.726
RAQLSR	1.786
RAQLSS	1.655
RAQLST	1.191
RAQLSV	0.146
RAQLSW	0.599

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CAPE Dataset: RhlA Enzyme Mutations（https://github.com/KRATSZ/CAPE-2023/tree/main）

Dataset Introduction and Usage 😋

RhlA (Uniprot ID: Q51559, PDB ID: 8IK2) is a key enzyme involved in synthesizing the hydrophobic component of rhamnolipids. The enzyme determines the length and unsaturation of the fatty acid chains, which ultimately influences the physicochemical properties and bioactivity of rhamnolipids.

Why Modify RhlA?

Modifying RhlA allows better control over the structure of the fatty acid chains, leading to an improved yield of rhamnolipids and enhanced potential for industrial and pharmaceutical applications.

Dataset Description 📑

Training Dataset: `Saprot_CAPE_dataset_train.csv`

File Format: CSV
Number of Sequences: 1,593
Columns:
- protein: Represents the combination of mutations at 6 critical amino acid positions (positions 74, 101, 143, 148, 173, and 176).
- label: The enzyme functional evaluation metric, representing the overall activity yield.

Testing Dataset: `Saprot_CAPE_dataset_test.csv`

Number of Sequences: 925
Description: Contains sequence information only. You need to predict the activity of these sequences for model evaluation. Submit the predictions to Kaggle to receive performance feedback.