Thomas Seidel

Thomas Seidel studied Technical Chemistry at the Vienna University of Technology where he received a PhD in Synthetic Organic Chemistry in 2003. From 2004 until 2005 he worked as a postdoctoral research assistant in the group of Prof. Johann Gasteiger at the Computer Chemistry Center/University of Erlangen-Nuremberg. The main focus of his research was the development of methods and algorithms to assess the synthetic accessibility of compounds generated by de novo design. After his postdoctoral stay he returned to Vienna for a position at the company InteLigand GmbH where he developed cheminformatics software for pharmacophore modeling and virtual screening. Since 2014 Thomas Seidel is a senior PostDoc at the Department of Pharmaceutical Chemistry/University of Vienna where he leads the chemoinformatics research group. The main topics of his research are the development and implementation of novel algorithms for pharmacophore-based drug development, the advancement of the pharmacophore concept and the application of molecular dynamics simulations and machine learning methods in the context of molecular design.

Contact
E-Mail: thomas.seidel@univie.ac.at
Tel: +43-1-4277-55051
Room: 2E 354
Publications: u:cris

Permann C, Seidel T , Langer T. Greedy 3-point search (G3ps)—a novel algorithm for pharmacophore alignment. Molecules. 2021 Nov 27;26(23):7201. doi: 10.3390/molecules26237201

Wieder O, Kuenemann M, Wieder M, Seidel T, Meyer C, Bryant SD et al. Improved lipophilicity and aqueous solubility prediction with composite graph neural networks. Molecules. 2021 Oct 1;26(20):6185. doi: 10.3390/molecules26206185

Kohlbacher SM, Langer T , Seidel T. QPHAR: quantitative pharmacophore activity relationship: method and validation. Journal of Cheminformatics. 2021 Aug 9;13(1):57. doi: 10.1186/s13321-021-00537-9

Vittorio S, Seidel T, Garon A, Gitto R, Langer T, De Luca L. In Silico Identification of Potential Druggable Binding Sites on CIN85 SH3 Domain. International Journal of Molecular Sciences. 2021 Jan;22(2):1-14. 534. doi: 10.3390/ijms22020534

Garon A, Wieder O, Bareis K, Seidel T, Ibis G, Bryant S et al. Hierarchical Graph Representation of Pharmacophore Models. Frontiers in Molecular Biosciences. 2020 Dec 14;7:599059. doi: 10.3389/fmolb.2020.599059, 10.3389/fmolb.2020.599059

Wieder O, Kohlbacher S, Kuenemann M, Garon A, Ducrot P, Seidel T et al. A compact review of molecular property prediction with graph neural networks. Drug Discovery Today: Technologies. 2020 Dec;37:1-12. doi: 10.1016/j.ddtec.2020.11.009

Seidel T , Wieder O, Garon A, Langer T. Applications of the Pharmacophore Concept in Natural Product inspired Drug Design. Molecular Informatics. 2020 Nov 1;39(11):2000059. doi: 10.1002/minf.202000059

Battisti V , Wieder O, Garon A, Seidel T , Urban E , Langer T. A Computational Approach to Identify Potential Novel Inhibitors against the Coronavirus SARS-CoV-2. Molecular Informatics. 2020 Oct;39(10):2000090. doi: 10.1002/minf.202000090

Vittorio S, Seidel T, Germano MP, Gitto R, Ielo L, Garon A et al. A Combination of Pharmacophore and Docking‐based Virtual Screening to Discover new Tyrosinase Inhibitors. Molecular Informatics. 2020 Mar;39(3):1900054. Epub 2019 Sept 11. doi: 10.1002/minf.201900054

Stadler M, Monticelli S, Seidel T, Luger D, Salzer I, Boehm S et al. Design, Synthesis, and Pharmacological Evaluation of Novel β2/3 Subunit-Selective γ-Aminobutyric Acid Type A (GABA _A ) Receptor Modulators. Journal of Medicinal Chemistry. 2019 Oct 1;62(1):317-341. doi: 10.1021/acs.jmedchem.8b00859

Singh N, Scalise M, Galluccio M, Wieder M, Seidel T , Langer T et al. Discovery of Potent Inhibitors for the Large Neutral Amino Acid Transporter 1 (LAT1) by Structure-Based Methods. International Journal of Molecular Sciences. 2019 Jan;20(1):27. doi: 10.3390/ijms20010027

Kainrad T, Hunold S, Seidel T , Langer T. LigandScout Remote: A new User-Friendly Interface for HPC and Cloud Resources. Journal of Chemical Information and Modeling. 2019 Jan;59(1):31-37. doi: 10.1021/acs.jcim.8b00716

Seidel T, Schuetz DA, Garon A, Langer T. The Pharmacophore Concept and Its Applications in Computer-Aided Drug Design. In Progress in the Chemistry of Organic Natural Products. Springer Science and Business Media Deutschland GmbH. 2019. p. 99-141. (Progress in the Chemistry of Organic Natural Products, Vol. 110). doi: 10.1007/978-3-030-14632-0_4

Schuetz DA, Seidel T, Garon A, Martini R, Körbel M, Ecker GF et al. GRAIL: GRids of phArmacophore Interaction fieLds. Journal of Chemical Theory and Computation. 2018 Sept;14(9):4958–4970. Epub 2018 Aug 3. doi: 10.1021/acs.jctc.8b00495

Poli G, Seidel T , Langer T. Conformational sampling of small molecules with iCon: Performance assessment in comparison with OMEGA. Frontiers in Chemistry. 2018 Jun 19;6:229. doi: 10.3389/fchem.2018.00229

Seidel T, Wolber G, S.murgueitio M. Pharmacophore Perception and Applications. In Applied Chemoinformatics: Achievements and Future Opportunities. Wiley. 2018. p. 259-282 doi: 10.1002/9783527806539.ch6f

Perricone U, Wieder M, Seidel T , Langer T, Padova A. The Use of Dynamic Pharmacophore in Computer-Aided Hit Discovery: A Case Study. In Mavromoustakos T, Kellici TF, editors, Rational Drug Design: Methods and Protocols. Vol. 1824. Springer Nature. 2018. p. 317-333. (Methods in Molecular Biology). doi: 10.1007/978-1-4939-8630-9

Perricone U, Wieder M, Seidel T , Langer T, Padova A, Almerico AM et al. A Molecular Dynamics–Shared Pharmacophore Approach to Boost Early-Enrichment Virtual Screening: A Case Study on Peroxisome Proliferator-Activated Receptor α. ChemMedChem: chemistry enabling drug discovery. 2017 Aug 22;12(16):1399-1407. doi: 10.1002/cmdc.201600526

Seidel T , Bryant S, Ibis G, Poli G, Langer T. 3D pharmacophore modeling techniques in computer-aided molecular design using LigandScout. In Varnek A, editor, Tutorials in Chemoinformatics. Wiley VCH. 2017. p. 279-309 doi: 10.1002/9781119161110.ch20, 10.1002/9781119161110.ch20

Wieder M, Garon A, Perricone U, Boresch S , Seidel T, Almerico AM et al. Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations. Journal of Chemical Information and Modeling. 2017 Feb;57(2):365-385. doi: 10.1021/acs.jcim.6b00674

Dipl.-Ing. Dr. Thomas Seidel

Dipl.-Ing. Dr. Thomas Seidel