IC50 assay data again the sEH protein target using prediction from Machine Learning Applied to Affinity Screening Data - Abstract and dataset

Aug 3, 2026

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Machine learning models were developed from affinity screening data and used to virtually screen a large set of commercially available compounds for soluble epoxide hydrolase (sEH) inhibition. Selected top-ranked virtual hits were tested experimentally using dose-response assays to measure inhibitory potency, producing a dataset of measured IC50 values. The dataset includes two groups: 2002 compounds evaluated after ML-based selection and 62 cherry-picked compounds retested at higher concentration to refine potency estimates.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages691

Reading Time29 h 1 min

AccessFree to download

Abstract

Experimental Design and Target

UniProt Target Information

Dataset Contents

IC50 Measurements for Selected Compounds

Retest Set at Higher Concentration

Data Table Fields

Technical Disclosure Commons Defensive Publications Series October 2023 IC50 assay data again the sEH protein target using prediction from Machine Learning Applied to Affinity Screening Data Jin Xu Follow this and additional works at: [https://www.tdcommons.org/dpubs_series](https://www.tdcommons.org/dpubs_series) Recommended Citation Xu, Jin, "IC50 assay data again the sEH protein target using prediction from Machine Learning Applied to Affinity Screening Data", Technical Disclosure Commons,(October 05, 2023) [https://www.tdcommons.org/dpubs_series/6300](https://www.tdcommons.org/dpubs_series/6300) This work is licensed under a Creative Commons Attribution 4.0 License. This Article is brought to you for free and open access by Technical Disclosure Commons. It has been accepted for inclusion in Defensive Publications Series by an authorized administrator of Technical Disclosure Commons. IC50 assay data against the sEH protein target using prediction from Machine Learning Applied to Affinity Screening Data Anonymous October 2023 Abstract Machine learning models were developed using affinity screening data and applied to virtually screen commercially available compounds. The top-ranked compounds from this virtual screening were then tested experimentally to determine their inhibitory potency against the soluble epoxide hydrolase (sEH) target. This dataset provides (1) the measured IC50 values for 2002 compounds evaluated in dose-response assays with sEH after selection through the machine learning models. (2) cherry-picked 62 compounds to re-test using higher concentration. 1 2002 compounds tested against sEH The UniProtKB entry of sEH is Q6VAM8 . In the table, higher pIC50 values indicate higher potency inhibition. | Chemical Structure | SMILES | Compound ID | pIC50 | | --- | --- | --- | --- | | | CC1CCC(NC(=O)CN2CCN( C(=O)NCCc3ccccc3C(F)
(F)F)CC2)CC1 | MCULE- 9260300032 | 6.338241523 | 1 Published by Technical Disclosure Commons, 2023 2 | Chemical Structure | SMILES | Compound ID | pIC50 | | --- | --- | --- | --- | | | CC[C@H]1CC[C@H](C(=O )NC[C@H]2CC[C@H](CNC (=O)C3CCOC3)CC2)CC1 | MCULE- 2948378156 | 6.569025929 | | | CC1CCC(NC(=O)NC2CCC( C3CCC3)CC2)C(C)C1 | MCULE- 2408890678 | 8.66894843 | | | Cc1ccc(CN2CCN(C(=S)NCC(=O)NC3CCCCCCC3)CC 23CCCCC3)cc1 | MCULE- 2499395204 | 7.001175512 | 2 [https://www.tdcommons.org/dpubs_series/6300](https://www.tdcommons.org/dpubs_series/6300) 3 | Chemical Structure | SMILES | Compound ID | pIC50 | | --- | --- | --- | --- | | | N\#CC1CN(C(=O)NCC2(c3 cccc(OC(F)(F)F)c3)CCC2)CCO1 | MCULE- 9759014052 | 5 | | | CC(C)[C@@H]1C[C@@H]( CNC(=O)NC2CCC3CNCC3C 2)c2ccccc21 | MCULE- 9821320097 | 7.081483709 | | | O=C(NCCC(=O)N1CCc2sc cc2C1)NC1CCCCCCC1 | MCULE- 4480828382 | 6.608076815 | 3 Published by Technical Disclosure Commons, 2023 4 | Chemical Structure | SMILES | Compound ID | pIC50 | | --- | --- | --- | --- | | | S=C(NC1CCCCCCC1)NC1CC2CCC1C2 | MCULE- 9543299376 | 6.97069948 | | | CCO[C@@H]1CN(C(=O)NCC2CCC3(CC2)CC3)C[C@H ]1CN | MCULE- 3358297101 | 5.926135598 | | | NCC1CCC(NC(=O)NC[C@@ H]2C[C@H]2C2CCC2)C1 | MCULE- 4229224592 | 7.670946101 | 4 [https://www.tdcommons.org/dpubs_series/6300](https://www.tdcommons.org/dpubs_series/6300) 5 | Chemical Structure | SMILES | Compound ID | pIC50 | | --- | --- | --- | --- | | | O=C(NCCc1ccc(Cl)cc1) NCC12CC3CC(CC(C3)C1) C2 | MCULE- 7153430405 | 7.636097043 | | | CC1CC(C)(C)CCC1NC(=O )NCc1cccc(NC(=O)C2CCC2)c1 | MCULE- 4741004818 | 6.401424214 | | | CCS(=O)(=O)N1CCC(CNC (=O)NCC2(c3ccccc3Br) CCC2)CC1 | MCULE- 6173635103 | 6.64261177 | 5 Published by Technical Disclosure Commons, 2023 6 | Chemical Structure | SMILES | Compound ID | pIC50 | | --- | --- | --- | --- | | | O=C(CC12CC3CC(CC(C3) C1)C2)NCC(=O)N1CCC(C (=O)Nc2ccc(F)c(Cl)c2)CC1 | MCULE- 3727836555 | 8.067726343 | | | CNC(=O)NCC1CN(C(=O)NCc2ccc(F)cc2C(F)(F)F )CCO1 | MCULE- 1862827056 | 6.295542658 | | | CCC1CCCCC1NC(=O)NCc1 ccc(C2CC

FAQs

How were the sEH inhibitory compounds selected before IC50 measurement?

Compounds were first screened virtually using machine learning models trained on affinity screening data, and the top-ranked predictions were advanced for experimental testing against the sEH target.

What does the dataset contain in terms of measured endpoints?

The dataset provides measured IC50 values from dose-response assays for 2002 selected compounds, and it also includes a retest set of 62 cherry-picked compounds using higher concentration.

What does pIC50 mean in the dataset tables?

In the provided tables, higher pIC50 values correspond to higher inhibitory potency against the soluble epoxide hydrolase (sEH) target.

Aug 3, 2026

Upload by Finn