Published on 10 September 2024

Mitigating activity cliff-induced discrepancies by structure-free compound-protein interaction and integrated bioactivity learning

View Dataset
Gu, Yaowen

Description

CPI2M data for "Complex structure-free compound-protein interaction prediction for mitigating activity cliff-induced discrepancies and integrated bioactivity learning".ki.csv: Bioactivity data with pKi activity type.kd.csv: Bioactivity data with pKd activity type.ec50.csv: Bioactivity data with pEC50 activity type.ic50.csv: Bioactivity data with pIC50 activity type.Protein_pretrained_feat.zip: pre-calculated protein feature files with UniProt ID naming. Should be unzipped before start model training with CPI2M data. For each .csv data, columns include "smiles" (ligand SMILES), "exp_mean" (nM bioactivity), "y" (neg.log nM, final label), "cliff_mol" (whether activity cliff or not), "split" (splitting label by activity cliff), "Uniprot_id" (UniProt ID for protein), "Sequence" (wildtype sequence for protein). Please find the project code at https://github.com/gu-yaowen/GGAP-CPI

Citations (1)

Mentions (0)

Metrics

Dataset Index

1.3

FAIR Score

81%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Molecular Biology

Field

Biochemistry, Genetics and Molecular Biology

Domain

Life Sciences

Confidence Score

53%

Source

Scholar Data Model

Normalization Factors

FT

30.77

CTw

1.00

MTw

1.00