Ligand binding site superposition and comparison based on Atomic Property Fields: identification of distant homologues, convergent evolution and PDB-wide clustering of binding sites

A new binding site comparison algorithm using optimal superposition of the continuous pharmacophoric property distributions is reported. The method demonstrates high sensitivity in discovering both, distantly homologous and convergent binding sites. Good quality of superposition is also observed on multiple examples. Using the new approach, a measure of site similarity is derived and applied to clustering of ligand binding pockets in PDB

Structural Biology of Human H3K9 Methyltransferases

SET domain methyltransferases deposit methyl marks on specific histone tail lysine residues and play a major role in epigenetic regulation of gene transcription. We solved the structures of the catalytic domains of GLP, G9a, Suv39H2 and PRDM2, four of the eight known human H3K9 methyltransferases in their apo conformation or in complex with the methyl donating cofactor, and peptide substrates. We analyzed the structural determinants for methylation state specificity, and designed a G9a mutant able to tri-methylate H3K9. We show that the I-SET domain acts as a rigid docking platform, while induced-fit of the Post-SET domain is necessary to achieve a catalytically competent conformation. We also propose a model where long-range electrostatics bring enzyme and histone substrate together, while the presence of an arginine upstream of the target lysine is critical for binding and specificity. Enhanced version: This article can also be viewed as an enhanced version in which the text of the article is integrated with interactive 3D representations and animated transitions. Please note that a web plugin is required to access this enhanced functionality. Instructions for the installation and use of the web plugin are available i

Population based models of cortical drug response: insights from anaesthesia

A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia