Feldmann C - Search Results

1

N-Sulfonyl dipeptide nitriles as inhibitors of human cathepsin S: In silico design, synthesis and biochemical characterization.

Lemke C, Cianni L, Feldmann C, Gilberg E, Yin J, Dos Reis Rocho F, de Vita D, Bartz U, Bajorath J, Montanari CA, Gütschow M. Lemke C, et al. Among authors: feldmann c. Bioorg Med Chem Lett. 2020 Sep 15;30(18):127420. doi: 10.1016/j.bmcl.2020.127420. Epub 2020 Jul 17. Bioorg Med Chem Lett. 2020. PMID: 32763808

2

Can Cysteine Protease Cross-Class Inhibitors Achieve Selectivity?

Cianni L, Feldmann CW, Gilberg E, Gütschow M, Juliano L, Leitão A, Bajorath J, Montanari CA. Cianni L, et al. J Med Chem. 2019 Dec 12;62(23):10497-10525. doi: 10.1021/acs.jmedchem.9b00683. Epub 2019 Aug 15. J Med Chem. 2019. PMID: 31361135 Review.

3

Identifying Promiscuous Compounds with Activity against Different Target Classes.

Feldmann C, Miljković F, Yonchev D, Bajorath J. Feldmann C, et al. Molecules. 2019 Nov 18;24(22):4185. doi: 10.3390/molecules24224185. Molecules. 2019. PMID: 31752252 Free PMC article.

4

Biological Activity Profiles of Multitarget Ligands from X-ray Structures.

Feldmann C, Bajorath J. Feldmann C, et al. Molecules. 2020 Feb 12;25(4):794. doi: 10.3390/molecules25040794. Molecules. 2020. PMID: 32059498 Free PMC article.

5

Mapping the S1 and S1' subsites of cysteine proteases with new dipeptidyl nitrile inhibitors as trypanocidal agents.

Cianni L, Lemke C, Gilberg E, Feldmann C, Rosini F, Rocho FDR, Ribeiro JFR, Tezuka DY, Lopes CD, de Albuquerque S, Bajorath J, Laufer S, Leitão A, Gütschow M, Montanari CA. Cianni L, et al. Among authors: feldmann c. PLoS Negl Trop Dis. 2020 Mar 12;14(3):e0007755. doi: 10.1371/journal.pntd.0007755. eCollection 2020 Mar. PLoS Negl Trop Dis. 2020. PMID: 32163418 Free PMC article.

6

X-ray Structure-Based Chemoinformatic Analysis Identifies Promiscuous Ligands Binding to Proteins from Different Classes with Varying Shapes.

Feldmann C, Bajorath J. Feldmann C, et al. Int J Mol Sci. 2020 May 27;21(11):3782. doi: 10.3390/ijms21113782. Int J Mol Sci. 2020. PMID: 32471121 Free PMC article.

7

Prediction of Promiscuity Cliffs Using Machine Learning.

Blaschke T, Feldmann C, Bajorath J. Blaschke T, et al. Among authors: feldmann c. Mol Inform. 2021 Jan;40(1):e2000196. doi: 10.1002/minf.202000196. Epub 2020 Sep 29. Mol Inform. 2021. PMID: 32881355 Free PMC article.

8

Systematic Data Analysis and Diagnostic Machine Learning Reveal Differences between Compounds with Single- and Multitarget Activity.

Feldmann C, Yonchev D, Stumpfe D, Bajorath J. Feldmann C, et al. Mol Pharm. 2020 Dec 7;17(12):4652-4666. doi: 10.1021/acs.molpharmaceut.0c00901. Epub 2020 Nov 5. Mol Pharm. 2020. PMID: 33151084

9

Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning.

Feldmann C, Yonchev D, Bajorath J. Feldmann C, et al. Biomolecules. 2020 Nov 27;10(12):1605. doi: 10.3390/biom10121605. Biomolecules. 2020. PMID: 33260876 Free PMC article.

10

Machine learning reveals that structural features distinguishing promiscuous and non-promiscuous compounds depend on target combinations.

Feldmann C, Bajorath J. Feldmann C, et al. Sci Rep. 2021 Apr 12;11(1):7863. doi: 10.1038/s41598-021-87042-z. Sci Rep. 2021. PMID: 33846469 Free PMC article.

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