Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence homology); however, very few systematically classify functional families (FunFams) comprising evolutionary relatives that share similar functional properties. We have developed the FunFam-MARC (Multidomain ARchitecture-based Clustering) protocol, which uses multi-domain architectures of protein kinases and specificity-determining residues for functional family classification. FunFam-MARC predicts 2210 kinase functional families (KinFams), which have increased functional coherence, in terms of EC annotations, compared to the widely used KinBase classification. Our protocol provides a comprehensive classification for kinase sequences from >10,000 organisms. We associate human KinFams with diseases and drugs and identify 28 druggable human KinFams, i.e., enriched in clinically approved drugs. Since relatives in the same druggable KinFam tend to be structurally conserved, including the drug-binding site, these KinFams may be valuable for shortlisting therapeutic targets. Information on the human KinFams and associated 3D structures from AlphaFold2 are provided via our CATH FTP website and Zenodo. This gives the domain structure representative of each KinFam together with information on any drug compounds available. For 32% of the KinFams, we provide information on highly conserved residue sites that may be associated with specificity.

Nep1 is a protein essential for the formation of the eukaryotic and archaeal small ribosomal subunit. It is an enzyme responsible for the site–specific SAM–dependent methylation of pseudouridine (Ψ) during the pre–rRNA processing. It possesses a non–trivial topology, namely, a 3 ₁ knot in the active site. Herein, we investigate the structure and mechanism of catalysis of Nep1 using a combination of bioinformatics, computational, and experimental methods. In particular, we address the issue of seemingly unfeasible deprotonation of Ψ nucleobase in the active site of Nep1 by a distant aspartate residue (e.g., D101 in Nep1 of S. cerevisiae ). Sequence alignment analysis across different organisms identifies a conserved serine/threonine residue that may play a role of a proton–transfer mediator (e.g., S233 in Nep1 from S. cerevisiae ), facilitating the reaction. Two enzyme–substrate complexes, one based on an available crystal structure and the other generated by molecular docking, of representative eukaryotic (from S. cerevisiae ) and archaeal (from A. fulgidus ) Nep1 homologs are subjected to molecular dynamics (MD) simulations. The resulting trajectories confirm that the hydroxyl–containing amino acid can indeed adopt a position suitable for proton–shuttling, with the OH group located in between the proton donor and acceptor. However, during the MD simulations, a water molecule emerges from arrangements of the active site, which can assume the role of the proton–transfer mediator instead. To discern between these two alternative pathways, we evaluate the possible methylation mechanisms by quantum–chemical calculations based on density functional theory, using the cluster approach. The obtained energy profiles indicate that the most facile course of the reaction for both the yeast and archaeal enzymes is to engage the water molecule. These results are corroborated by agreement of the computed energy barriers with experimentally measured enzyme kinetics. Moreover, mutational studies show that, while aspartate D101 is crucial for the catalytic activity, serine S233 is irrelevant in this context, indirectly supporting the water–mediated proton transfer. Our findings comprehensively elucidate the mode of action of Nep1 and provide implication for understanding the catalytic mechanisms of other enzymes that involve a proton transfer in the active site over extended distances.