References
- Maggiora GM. On outliers and activity cliffs – why QSAR often disappoints. J Chem Inf Model. 2006;46:1535–1535.
- Stumpfe D, Bajorath J. Exploring activity cliffs in medicinal chemistry. J Med Chem. 2012;55:2932–2942.
- Stumpfe D, Hu Y, Dimova D, et al. Recent progress in understanding activity cliffs and their utility in medicinal chemistry. J Med Chem. 2014;57:18–28.
- Kenny PW, Sadowski J. Structure modification in chemical databases. In: Oprea TI, editor. Chemoinformatics in drug discovery. Weinheim: Wiley-VCH; 2005. p. 271–285.
- Hussain J, Rea C. Computationally efficient algorithm to identify matched molecular pairs (MMPs) in large data sets. J Chem Inf Model. 2010;50:339–348.
- Hu X, Hu Y, Vogt M, et al. MMP-cliffs: systematic identification of activity cliffs on the basis of matched molecular pairs. J Chem Inf Model. 2012;52:1138–1145.
- Hu Y, Stumpfe D, Bajorath J. Advancing the activity cliff concept. F1000Res. 2013;2:199.
- Furtmann N, Hu Y, Gütschow M, et al. Identification and analysis of currently available high-confidence three-dimensional activity cliffs. RSC Adv. 2015;5:43660–43668.
- Hu Y, Furtmann N, Bajorath J. Extension of three-dimensional activity cliff information through systematic mapping of active analogs. RSC Adv. 2015;5:43006–43015.
- Stumpfe D, Dimova D, Bajorath J. Composition and topology of activity cliff clusters formed by bioactive compounds. J Chem Inf Model. 2014;54:451–461.
- Dimova D, Stumpfe D, Bajorath. J. A method for the evaluation of structure-activity relationship information associated with coordinated activity cliffs. J Med Chem. 2014;57:6553–6563.
- Dimova D, Bajorath J. Extraction of structure-activity relationship information from activity cliff clusters via matching molecular series. Eur J Med Chem. 2014;87:454–460.
- Dimova D, Stumpfe D, Hu Y, et al. Activity cliff clusters as a source of structure-activity relationship information. Expert Opin Drug Discov. 2015;10:441–447.
- Gaulton A, Bellis LJ, Bento AP, et al. ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 2011;40:D1100–D1107.
- Heikamp K, Hu X, Yan A, et al. Prediction of activity cliffs using support vector machines. J Chem Inf Model. 2012;52:2354–2365.
- Horvath D, Marcou G, Varnek A, et al. Prediction of activity cliffs using condensed graphs of reaction representations, descriptor recombination, support vector machine classification, and support vector regression. J Chem Inf Model. 2016;56:1631–1640.
- Husby J, Bottegoni G, Kufareva I, et al. Structure-based predictions of activity cliffs. J Chem Inf Model. 2015;55:1062–1076.