Computational biologist working at the intersection of structure-based drug discovery, machine learning, and multi-omics. MSc in Biochemistry (University of Sistan and Baluchestan, 2022 — ranked 2nd of 10, A-grade thesis defense). Co-author of three peer-reviewed journal articles; first author of a conference paper on NMDA-receptor virtual screening. Earlier background: wet-lab cell & gene therapy (hWJMSC culture, lentiviral vector production).

Structure-based drug discovery (docking, MD, τRAMD, MM-PBSA) · QSAR machine learning · transcriptomic/proteomic network analysis · reproducible pipeline engineering (Python, R, Nextflow, Docker, FastAPI)

• proteomics-de-pipeline — differential protein abundance & enrichment in AD hippocampus (PXD034525; 369 significant proteins; STRING hub analysis)
• AChE-QSAR-Machine-Learning — pIC50 prediction from Morgan fingerprints; Random Forest (R² = 0.722) vs. PyTorch NN (R² = 0.710) on 8,790 ChEMBL compounds
• alphafold-cadd-workflow — automated AlphaFold → Vina docking → Lipinski pipeline (Nextflow DSL2), TREM2 target
• cadd-fastapi-service — containerized REST API for descriptor retrieval and Lipinski screening (FastAPI, Docker, RDKit)
• pubchem-metabolite-descriptor-fetcher — batch PubChem PUG REST pipeline with rate limiting, retry/backoff, and R visualization
• vina-docking-pipeline — Vina output parsing, RoF filtering, affinity ranking

1. Khakpour A., Ahmadi Shadmehri N., Sedaghati A., et al. (2025). Computational screening of walnut (Juglans regia) husk metabolites reveals Aesculin as a potential inhibitor of pectate lyase Pel3: Insights from molecular dynamics and τRAMD. Biochemistry and Biophysics Reports, 43, 102171. doi:10.1016/j.bbrep.2025.102171
2. Alami F., Teymourzadeh M., Sedaghati A., et al. (2026). Network-based transcriptomics identifies key hippocampal targets in Alzheimer's disease and their modulation by Apigenin, Luteolin, and Berberine. Scientific African, 33, e03564. doi:10.1016/j.sciaf.2026.e03564
3. Estiri M., Estiri B., Fallah A., Aghazadeh M., Sedaqati A., et al. (2022). Therapeutic effects of mesenchymal stem cells expressing erythropoietin on cancer-related anemia in mice model. Current Gene Therapy, 22(5), 406–416. doi:10.2174/1566523222666220405134136

Conference proceedings paper (Persian-language):

4. Sedaghati A., Lagzian M., Mohammadi M., Ghahghaei A. (2022). Identification of the most effective compounds binding to the NMDA receptor, a key factor in Alzheimer's disease, using virtual screening of Traditional Chinese Medicine database compounds (English translation of the Persian title). 5th National Conference on the Development of Emerging Sciences and Technologies in Medicinal Plants, Chemistry and Biology of Iran. Civilica-indexed: civilica.com/doc/1560361.

ORCID: 0009-0002-6445-0329 · Google Scholar · LinkedIn · Email: aamirsedaghati@gmail.com