| Literature DB >> 24900855 |
Jenny Viklund1, Karin Kolmodin1, Gunnar Nordvall1, Britt-Marie Swahn1, Mats Svensson1, Ylva Gravenfors1, Fredrik Rahm1.
Abstract
In order to find optimal core structures as starting points for lead optimization, a multiparameter lead generation workflow was designed with the goal of finding BACE-1 inhibitors as a treatment for Alzheimer's disease. De novo design of core fragments was connected with three predictive in silico models addressing target affinity, permeability, and hERG activity, in order to guide synthesis. Taking advantage of an additive SAR, the prioritized cores were decorated with a few, well-characterized substituents from known BACE-1 inhibitors in order to allow for core-to-core comparisons. Prediction methods and analyses of how physicochemical properties of the core structures correlate to in vitro data are described. The syntheses and in vitro data of the test compounds are reported in a separate paper by Ginman et al. [J. Med. Chem. 2013, 56, 4181-4205]. The affinity predictions are described in detail by Roos et al. [J. Chem. Inf. 2014, DOI: 10.1021/ci400374z].Entities:
Keywords: BACE-1 inhibitor; core optimization; fragment optimization; multiparameter optimization; scaffold hopping; β-secretase inhibitor
Year: 2014 PMID: 24900855 PMCID: PMC4027760 DOI: 10.1021/ml5000433
Source DB: PubMed Journal: ACS Med Chem Lett ISSN: 1948-5875 Impact factor: 4.345