Design and exploration of target-selective chemical space representations.
We report the design of target-selective chemical spaces using CA-DynaMAD, a mapping algorithm that generates and navigates flexible space representations for the identification of active or selective compounds. The algorithm iteratively increases the dimensionality of reference spaces in a controlled manner by evaluating a single descriptor per iteration. For seven sets of closely related biogenic amine G protein coupled receptor (GPCR) antagonists with different selectivity, target-selective reference spaces were designed and used to identify selective compounds by screening a biologically annotated database. Combinations of descriptors that constitute target-selective reference spaces identified with CA-DynaMAD can also be used to build other computational models for the prediction of compound selectivity.
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
Ingo
I
Vogt
Jürgen
J
Bajorath
D000465:Algorithms; D001679:Biogenic Amines / Q000737:chemistry*; D015195:Drug Design; D043562:Receptors, G-Protein-Coupled / Q000037:antagonists & inhibitors / Q000737:chemistry*
D001679:Biogenic Amines; D043562:Receptors, G-Protein-Coupled