Lobell M - Search Results

1

Novel TIE-2 inhibitor BAY-826 displays in vivo efficacy in experimental syngeneic murine glioma models.

Schneider H, Szabo E, Machado RA, Broggini-Tenzer A, Walter A, Lobell M, Heldmann D, Süssmeier F, Grünewald S, Weller M. Schneider H, et al. Among authors: lobell m. J Neurochem. 2017 Jan;140(1):170-182. doi: 10.1111/jnc.13877. Epub 2016 Dec 12. J Neurochem. 2017. PMID: 27787897 Free article.

2

Discovery of Rogaratinib (BAY 1163877): a pan-FGFR Inhibitor.

Collin MP, Lobell M, Hübsch W, Brohm D, Schirok H, Jautelat R, Lustig K, Bömer U, Vöhringer V, Héroult M, Grünewald S, Hess-Stumpp H. Collin MP, et al. Among authors: lobell m. ChemMedChem. 2018 Mar 6;13(5):437-445. doi: 10.1002/cmdc.201700718. Epub 2018 Feb 16. ChemMedChem. 2018. PMID: 29451369

3

Cardiovascular effects of a novel potent and highly selective azaindole-based inhibitor of Rho-kinase.

Kast R, Schirok H, Figueroa-Pérez S, Mittendorf J, Gnoth MJ, Apeler H, Lenz J, Franz JK, Knorr A, Hütter J, Lobell M, Zimmermann K, Münter K, Augstein KH, Ehmke H, Stasch JP. Kast R, et al. Among authors: lobell m. Br J Pharmacol. 2007 Dec;152(7):1070-80. doi: 10.1038/sj.bjp.0707484. Epub 2007 Oct 15. Br J Pharmacol. 2007. PMID: 17934515 Free PMC article.

4

Design and synthesis of potent and selective azaindole-based Rho kinase (ROCK) inhibitors.

Schirok H, Kast R, Figueroa-Pérez S, Bennabi S, Gnoth MJ, Feurer A, Heckroth H, Thutewohl M, Paulsen H, Knorr A, Hütter J, Lobell M, Münter K, Geiss V, Ehmke H, Lang D, Radtke M, Mittendorf J, Stasch JP. Schirok H, et al. Among authors: lobell m. ChemMedChem. 2008 Dec;3(12):1893-904. doi: 10.1002/cmdc.200800211. ChemMedChem. 2008. PMID: 18973168

5

In silico ADMET traffic lights as a tool for the prioritization of HTS hits.

Lobell M, Hendrix M, Hinzen B, Keldenich J, Meier H, Schmeck C, Schohe-Loop R, Wunberg T, Hillisch A. Lobell M, et al. ChemMedChem. 2006 Nov;1(11):1229-36. doi: 10.1002/cmdc.200600168. ChemMedChem. 2006. PMID: 16991174

6

CypScore: Quantitative prediction of reactivity toward cytochromes P450 based on semiempirical molecular orbital theory.

Hennemann M, Friedl A, Lobell M, Keldenich J, Hillisch A, Clark T, Göller AH. Hennemann M, et al. Among authors: lobell m. ChemMedChem. 2009 Apr;4(4):657-69. doi: 10.1002/cmdc.200800384. ChemMedChem. 2009. PMID: 19243088

7

Improving the hit-to-lead process: data-driven assessment of drug-like and lead-like screening hits.

Wunberg T, Hendrix M, Hillisch A, Lobell M, Meier H, Schmeck C, Wild H, Hinzen B. Wunberg T, et al. Among authors: lobell m. Drug Discov Today. 2006 Feb;11(3-4):175-80. doi: 10.1016/S1359-6446(05)03700-1. Drug Discov Today. 2006. PMID: 16533716 Review.

8

Bayer's in silico ADMET platform: a journey of machine learning over the past two decades.

Göller AH, Kuhnke L, Montanari F, Bonin A, Schneckener S, Ter Laak A, Wichard J, Lobell M, Hillisch A. Göller AH, et al. Among authors: lobell m. Drug Discov Today. 2020 Sep;25(9):1702-1709. doi: 10.1016/j.drudis.2020.07.001. Epub 2020 Jul 9. Drug Discov Today. 2020. PMID: 32652309 Free article. Review.

9

Best of both worlds: combining pharma data and state of the art modeling technology to improve in Silico pKa prediction.

Fraczkiewicz R, Lobell M, Göller AH, Krenz U, Schoenneis R, Clark RD, Hillisch A. Fraczkiewicz R, et al. Among authors: lobell m. J Chem Inf Model. 2015 Feb 23;55(2):389-97. doi: 10.1021/ci500585w. Epub 2014 Dec 16. J Chem Inf Model. 2015. PMID: 25514239

10

Recent advances in the prediction of blood-brain partitioning from molecular structure.

Lobell M, Molnár L, Keserü GM. Lobell M, et al. J Pharm Sci. 2003 Feb;92(2):360-70. doi: 10.1002/jps.10282. J Pharm Sci. 2003. PMID: 12532385

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