Protein kinases are central mediators of signal-transduction cascades and attractive drug targets for therapeutic intervention. Since kinases are structurally and mechanistically related to each other, kinase inhibitor selectivity is often investigated by kinase profiling and considered as an important index for drug discovery. We here describe a versatile web server termed ProfKin for structure-based kinase profiling, which is based on a kinase-ligand focused database (KinLigDB). It provides all ready-to-use 3D structure coordinates of 4219 kinase-ligand complex structures covering 297 human kinases and the associated information, particularly including binding site type, binding ligand type, interaction fingerprints, downstream molecules and related human diseases. The web server works via predicting possible binding modes for the query molecule, prioritizing the binding modes guided by an interaction fingerprint analysis method, and giving a list of ranked kinases by a comprehensive index. Users can freely select entire or part of the KinLigDB database, e.g. via subfamily and binding site type, to customize the profiling contents. The superimpositions of the predicted binding poses of the query molecule with reference binding modes can be visually inspected on the website. The additional classification attributes and phylogenetic tree are also given for each top-ranked kinase.
Keywords: Interaction fingerprints; Kinase; Kinase inhibitor selectivity; Kinase profiling; Web server.
Copyright © 2021 Elsevier Masson SAS. All rights reserved.