Target Profile Prediction and Practical Evaluation of a Biginelli-Type Dihydropyrimidine Compound Library

摘要: We present a self-organizing map (SOM) approach to predicting macromolecular targets for combinatorial compound libraries. The aim was study the usefulness of SOM in combination with topological pharmacophore representation (CATS) selecting biologically active compounds from virtual collection, taking multi-component Biginelli dihydropyrimidine reaction as an example. synthesized candidate this library, which model suggested inhibitory activity against cyclin-dependent kinase 2 (CDK2) and other kinases. prediction confirmed vitro panel assay comprising 48 human conclude that computational technique may be used ligand-based silico pharmacology studies, off-target prediction, drug re-purposing, thereby complementing receptor-based approaches.