Single-Cell Transcriptomic Identification of Drug Repurposing Candidates for Ankylosing Spondylitis via PBMC scRNA-seq and ChEMBL Target Screening
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2026
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| _version_ | 1866901761313210368 |
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| author | Ritschel, Glen Charles Claude |
| author_facet | Ritschel, Glen Charles Claude |
| contents | <p>Companion preprint to USPTO provisional patent application by Ritschel Research. We applied a standardized computational drug repurposing pipeline to single-cell RNA sequencing data from peripheral blood mononuclear cells of 10 ankylosing spondylitis (AS) patients and 29 healthy controls (GEO: GSE194315; 79,733 cells after quality control across 39 donors). scVI-based batch correction and Leiden clustering identified 15 clusters spanning 10 immune cell types including CD4+ T cells, CD8+ T cells, NK cells, B cells, CD14+ monocytes, CD16+ monocytes, dendritic cells, Tregs, ILC/Th17 cells, and platelets. Wilcoxon differential expression analysis identified 3,611 AS-upregulated genes including mitochondrial-encoded transcripts reflecting metabolic reprogramming (MTRNR2L12, MT-ND3, MT-CO2), ribosomal protein genes indicating translational activation, and the phospholipase signaling mediator PLCG2. Systematic ChEMBL screening nominated 2,000 NOVEL_ALL repurposing candidates led by CHEMBL5653589 (score=219.63, N_targets=21, max_pChEMBL=9.63), which independently ranked first in our companion psoriatic arthritis pipeline, establishing a pan-spondyloarthritis cross-disease signal. The p38 MAPK inhibitors DORAMAPIMOD and NEFLAMAPIMOD also emerged as biologically coherent candidates. Authors: Glen Charles Ritschel¹ and Claude²; ¹Ritschel Research, Tega Cay SC; ²Anthropic, San Francisco CA.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19392339 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
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| spellingShingle | Single-Cell Transcriptomic Identification of Drug Repurposing Candidates for Ankylosing Spondylitis via PBMC scRNA-seq and ChEMBL Target Screening Ritschel, Glen Charles Claude ankylosing spondylitis axial spondyloarthritis scRNA-seq drug repurposing PBMC CHEMBL5653589 p38 MAPK DORAMAPIMOD NEFLAMAPIMOD spondyloarthritis scVI Leiden clustering ChEMBL PubChem single-cell transcriptomics computational pharmacology GSE194315 <p>Companion preprint to USPTO provisional patent application by Ritschel Research. We applied a standardized computational drug repurposing pipeline to single-cell RNA sequencing data from peripheral blood mononuclear cells of 10 ankylosing spondylitis (AS) patients and 29 healthy controls (GEO: GSE194315; 79,733 cells after quality control across 39 donors). scVI-based batch correction and Leiden clustering identified 15 clusters spanning 10 immune cell types including CD4+ T cells, CD8+ T cells, NK cells, B cells, CD14+ monocytes, CD16+ monocytes, dendritic cells, Tregs, ILC/Th17 cells, and platelets. Wilcoxon differential expression analysis identified 3,611 AS-upregulated genes including mitochondrial-encoded transcripts reflecting metabolic reprogramming (MTRNR2L12, MT-ND3, MT-CO2), ribosomal protein genes indicating translational activation, and the phospholipase signaling mediator PLCG2. Systematic ChEMBL screening nominated 2,000 NOVEL_ALL repurposing candidates led by CHEMBL5653589 (score=219.63, N_targets=21, max_pChEMBL=9.63), which independently ranked first in our companion psoriatic arthritis pipeline, establishing a pan-spondyloarthritis cross-disease signal. The p38 MAPK inhibitors DORAMAPIMOD and NEFLAMAPIMOD also emerged as biologically coherent candidates. Authors: Glen Charles Ritschel¹ and Claude²; ¹Ritschel Research, Tega Cay SC; ²Anthropic, San Francisco CA.</p> |
| title | Single-Cell Transcriptomic Identification of Drug Repurposing Candidates for Ankylosing Spondylitis via PBMC scRNA-seq and ChEMBL Target Screening |
| topic | ankylosing spondylitis axial spondyloarthritis scRNA-seq drug repurposing PBMC CHEMBL5653589 p38 MAPK DORAMAPIMOD NEFLAMAPIMOD spondyloarthritis scVI Leiden clustering ChEMBL PubChem single-cell transcriptomics computational pharmacology GSE194315 |
| url | https://doi.org/10.5281/zenodo.19392339 |