Bibliography

1

Xiao Qing Lewell, Duncan B. Judd, Stephen P. Watson, and Michael M. Hann. Recapretrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. Journal of Chemical Information and Computer Sciences, 38(3):511–522, 1998. PMID: 9611787. URL: https://doi.org/10.1021/ci970429i, arXiv:https://doi.org/10.1021/ci970429i, doi:10.1021/ci970429i.

2

Jörg Degen, Christof Wegscheid-Gerlach, Andrea Zaliani, and Matthias Rarey. On the art of compiling and using 'drug-like' chemical fragment spaces. ChemMedChem, 3(10):1503–1507, 2008. URL: https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/cmdc.200800178, arXiv:https://chemistry-europe.onlinelibrary.wiley.com/doi/pdf/10.1002/cmdc.200800178, doi:https://doi.org/10.1002/cmdc.200800178.

3

David Rogers and Mathew Hahn. Extended-connectivity fingerprints. Journal of Chemical Information and Modeling, 50(5):742–754, 2010. PMID: 20426451. URL: https://doi.org/10.1021/ci100050t, arXiv:https://doi.org/10.1021/ci100050t, doi:10.1021/ci100050t.

4

J. A. GRANT, M. A. GALLARDO, and B. T. PICKUP. A fast method of molecular shape comparison: a simple application of a gaussian description of molecular shape. Journal of Computational Chemistry, 17(14):1653–1666, 1996. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291096-987X%2819961115%2917%3A14%3C1653%3A%3AAID-JCC7%3E3.0.CO%3B2-K, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291096-987X%2819961115%2917%3A14%3C1653%3A%3AAID-JCC7%3E3.0.CO%3B2-K, doi:https://doi.org/10.1002/(SICI)1096-987X(19961115)17:14<1653::AID-JCC7>3.0.CO;2-K.

5

Thomas Seidel, Christian Permann, Oliver Wieder, Stefan M. Kohlbacher, and Thierry Langer. High-quality conformer generation with conforge: algorithm and performance assessment. Journal of Chemical Information and Modeling, 0(0):null, 0. PMID: 37624145. URL: https://doi.org/10.1021/acs.jcim.3c00563, arXiv:https://doi.org/10.1021/acs.jcim.3c00563, doi:10.1021/acs.jcim.3c00563.

6

Thomas A. Halgren. Merck molecular force field. i. basis, form, scope, parameterization, and performance of mmff94. Journal of Computational Chemistry, 17(5-6):490–519, 1996. URL: https://onlinelibrary.wiley.com/doi/abs/10.1002/%28SICI%291096-987X%28199604%2917%3A5/6%3C490%3A%3AAID-JCC1%3E3.0.CO%3B2-P, arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1002/%28SICI%291096-987X%28199604%2917%3A5/6%3C490%3A%3AAID-JCC1%3E3.0.CO%3B2-P, doi:https://doi.org/10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P.

7

Oliver Wieder, Mélaine Kuenemann, Marcus Wieder, Thomas Seidel, Christophe Meyer, Sharon D. Bryant, and Thierry Langer. Improved lipophilicity and aqueous solubility prediction with composite graph neural networks. Molecules, 2021. URL: https://www.mdpi.com/1420-3049/26/20/6185, doi:10.3390/molecules26206185.

8

Ya Chen, Thomas Seidel, Roxane Axel Jacob, Steffen Hirte, Angelica Mazzolari, Alessandro Pedretti, Giulio Vistoli, Thierry Langer, Filip Miljković, and Johannes Kirchmair. Active learning approach for guiding site-of-metabolism measurement and annotation. Journal of Chemical Information and Modeling, 0(0):null, 0. PMID: 38170877. URL: https://doi.org/10.1021/acs.jcim.3c01588, arXiv:https://doi.org/10.1021/acs.jcim.3c01588, doi:10.1021/acs.jcim.3c01588.

9

Doris A. Schuetz, Thomas Seidel, Arthur Garon, Riccardo Martini, Markus Körbel, Gerhard F. Ecker, and Thierry Langer. Grail: grids of pharmacophore interaction fields. Journal of Chemical Theory and Computation, 14(9):4958–4970, 2018. PMID: 30075621. URL: https://doi.org/10.1021/acs.jctc.8b00495, arXiv:https://doi.org/10.1021/acs.jctc.8b00495, doi:10.1021/acs.jctc.8b00495.

10

Marcus Wieder, Arthur Garon, Ugo Perricone, Stefan Boresch, Thomas Seidel, Anna Maria Almerico, and Thierry Langer. Common hits approach: combining pharmacophore modeling and molecular dynamics simulations. Journal of Chemical Information and Modeling, 57(2):365–385, 2017. PMID: 28072524. URL: https://doi.org/10.1021/acs.jcim.6b00674, arXiv:https://doi.org/10.1021/acs.jcim.6b00674, doi:10.1021/acs.jcim.6b00674.

11

Stefan Michael Kohlbacher, Matthias Schmid, Thomas Seidel, and Thierry Langer. Applications of the novel quantitative pharmacophore activity relationship method qphar in virtual screening and lead-optimisation. Pharmaceuticals, 2022. URL: https://www.mdpi.com/1424-8247/15/9/1122, doi:10.3390/ph15091122.

12

Christin Schärfer, Tanja Schulz-Gasch, Hans-Christian Ehrlich, Wolfgang Guba, Matthias Rarey, and Martin Stahl. Torsion angle preferences in druglike chemical space: a comprehensive guide. Journal of Medicinal Chemistry, 56(5):2016–2028, 2013. PMID: 23379567. URL: https://doi.org/10.1021/jm3016816, arXiv:https://doi.org/10.1021/jm3016816, doi:10.1021/jm3016816.

13

Wolfgang Guba, Agnes Meyder, Matthias Rarey, and Jérôme Hert. Torsion library reloaded: a new version of expert-derived smarts rules for assessing conformations of small molecules. Journal of Chemical Information and Modeling, 56(1):1–5, 2016. PMID: 26679290. URL: https://doi.org/10.1021/acs.jcim.5b00522, arXiv:https://doi.org/10.1021/acs.jcim.5b00522, doi:10.1021/acs.jcim.5b00522.

14

Patrick Penner, Wolfgang Guba, Robert Schmidt, Agnes Meyder, Martin Stahl, and Matthias Rarey. The torsion library: semiautomated improvement of torsion rules with smartscompare. Journal of Chemical Information and Modeling, 62(7):1644–1653, 2022. PMID: 35318851. URL: https://doi.org/10.1021/acs.jcim.2c00043, arXiv:https://doi.org/10.1021/acs.jcim.2c00043, doi:10.1021/acs.jcim.2c00043.

15

A. Patrícia Bento, Anne Hersey, Eloy Félix, Greg Landrum, Anna Gaulton, Francis Atkinson, Louisa J. Bellis, Marleen De Veij, and Andrew R. Leach. An open source chemical structure curation pipeline using rdkit. Journal of Cheminformatics, 12(1):51, Sep 2020. URL: https://doi.org/10.1186/s13321-020-00456-1, doi:10.1186/s13321-020-00456-1.

16

Martin Šícho, Conrad Stork, Angelica Mazzolari, Christina de Bruyn Kops, Alessandro Pedretti, Bernard Testa, Giulio Vistoli, Daniel Svozil, and Johannes Kirchmair. Fame 3: predicting the sites of metabolism in synthetic compounds and natural products for phase 1 and phase 2 metabolic enzymes. Journal of Chemical Information and Modeling, 59(8):3400–3412, 2019. PMID: 31361490. URL: https://doi.org/10.1021/acs.jcim.9b00376, arXiv:https://doi.org/10.1021/acs.jcim.9b00376, doi:10.1021/acs.jcim.9b00376.