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DC Field | Value | Language |
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dc.contributor.author | Pirzada, Rameez Hassan | - |
dc.contributor.author | Yasmeen, Farzana | - |
dc.contributor.author | Haseeb, Muhammad | - |
dc.contributor.author | Javaid, Nasir | - |
dc.contributor.author | Kim, Eunha | - |
dc.contributor.author | Choi, Sangdun | - |
dc.date.issued | 2024-12-01 | - |
dc.identifier.issn | 1879-0003 | - |
dc.identifier.uri | https://aurora.ajou.ac.kr/handle/2018.oak/34590 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85208680306&origin=inward | - |
dc.description.abstract | The human interleukin-1 receptor I (IL-1R1) is a cytokine receptor recognized by interleukin 1β (IL-1β), among other cytokines. Over activation of IL-1R1 has been implicated in various inflammatory conditions. This research aims to identify small-molecule inhibitors targeting the hIL1R1/IL1β interaction, employing a multi-task transfer learning approach for quantitative structure-activity relationship (QSAR) modelling. A comprehensive bioactivity dataset from functionally related proteins was utilised to build a robust ensemble machine learning model for predicting IC50 values against the target protein. Despite the availability of antibody-based therapies, the absence of orally available small-molecule inhibitors necessitates their development. By combining model predictions with docking and simulation approaches, the interleukin-1 receptor inhibitor (IRI-1) emerged as a lead compound. It potently inhibited human IL1-R1 with micromolar activity in THP-1 and Saos-2 cells and demonstrated good biocompatibility. Western blot analysis revealed that IRI-1 inhibits IL-1β-mediated phosphorylation of IL1-R1, JNK, IRAK-4, and ERK in THP-1 cells. Furthermore, molecular dynamics simulations confirmed the structural stability of the protein-ligand complexes. This study highlights the effectiveness of multi-task transfer learning approaches for building robust QSAR models against novel proteins or those with limited bioactivity data, such as hIL-1β/IL-1R1 protein. | - |
dc.description.sponsorship | This study was supported by the National Research Foundation of Korea under the grants NRF- 2022M3A9G1014520 , 2023R1A2C2003034 , 2019M3D1A1078940 , and 2019R1A6A1A11051471 . | - |
dc.language.iso | eng | - |
dc.publisher | Elsevier B.V. | - |
dc.subject.mesh | Dynamics simulation | - |
dc.subject.mesh | Interleukin-1 receptor | - |
dc.subject.mesh | Interleukin1 | - |
dc.subject.mesh | Molecular dynamic simulation | - |
dc.subject.mesh | Multi tasks | - |
dc.subject.mesh | Multi-task transfer learning | - |
dc.subject.mesh | Quantitative structure activity relationship | - |
dc.subject.mesh | Small-molecule inhibitors | - |
dc.subject.mesh | Task transfer | - |
dc.subject.mesh | Transfer learning | - |
dc.subject.mesh | Humans | - |
dc.subject.mesh | Interleukin-1beta | - |
dc.subject.mesh | Machine Learning | - |
dc.subject.mesh | Molecular Docking Simulation | - |
dc.subject.mesh | Molecular Dynamics Simulation | - |
dc.subject.mesh | Protein Binding | - |
dc.subject.mesh | Quantitative Structure-Activity Relationship | - |
dc.subject.mesh | Receptors, Interleukin-1 Type I | - |
dc.subject.mesh | Small Molecule Libraries | - |
dc.title | Small molecule inhibitors of IL-1R1/IL-1β interaction identified via transfer machine learning QSAR modelling | - |
dc.type | Article | - |
dc.citation.title | International Journal of Biological Macromolecules | - |
dc.citation.volume | 282 | - |
dc.identifier.bibliographicCitation | International Journal of Biological Macromolecules, Vol.282 | - |
dc.identifier.doi | 10.1016/j.ijbiomac.2024.137295 | - |
dc.identifier.pmid | 39515709 | - |
dc.identifier.scopusid | 2-s2.0-85208680306 | - |
dc.identifier.url | https://www.sciencedirect.com/science/journal/01418130 | - |
dc.subject.keyword | Interleukin-1 receptor | - |
dc.subject.keyword | Molecular dynamics simulation | - |
dc.subject.keyword | Multi-task transfer learning | - |
dc.subject.keyword | Quantitative structure-activity relationship | - |
dc.type.other | Article | - |
dc.identifier.pissn | 0141-8130 | - |
dc.description.isoa | false | - |
dc.subject.subarea | Structural Biology | - |
dc.subject.subarea | Biochemistry | - |
dc.subject.subarea | Molecular Biology | - |
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