Atomistic Computational Models To Evaluate Protein-Ligand Off-Target Interactions

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To be biologically active, small molecules, proteins and other cellular components must physically fit into their binding site(s) within their targets. A century ago, Fischer described this event as a lock-and-key fit. However, in reaching its precise binding location, a ligand (a molecule that binds to another) interacts with a variety of cellular components of various structures and functions. All these events increase the probability for a ligand, particularly a small molecule of exogenous cellular origin (e.g. synthetic drugs) to bind to an undesired off-target(s), altering their cellular functions. Computer simulations are currently well suited to address these problems as recognized with the 2013 Nobel Prize in Chemistry. The long-term goal of our research is to evaluate the interaction of small molecules with critical cellular off-targets. This grant application, however, will be centered on the potential interactions of small molecules with a critical class of proteins that controls the normal heart rhythm. We will focus on the potential blockade of cardiac ion channels by small molecules, a critical event that can lead to acquired cardiac long QT syndrome (LQTS) and fatal cardiac arrhythmias. Although LQTS has been often attributed to human Ether-à-go-go-Related Gene (hERG) channel blockage, recent studies show that multiple ion channel interactions are in fact required to predict changes in QT intervals. Our recent proof of principal study on the hERG ion channel provides the foundation for this grant application. Here, we propose to expand our efforts and build detailed molecular models for all cardiac ion channels and investigate their interactions with small molecules at the atomic level. Specifically, we will focus on the human Nav1.5 sodium channel, the Cav1.2 calcium channel and the KCNQ1 and Kir2.1 potassium channels. The available functional and structural information on these ion channels along with their immense reported interactions with various ligands as well as our established electrophysiology assays make them suitable platforms to develop and validate sensitive models to predict their potential off-target roles. ***Our methodology involves three main steps:***1. Build structural atomistic dynamical models for the cardiac ion channels.***2. Evaluate the interactions of the ion channels with small molecules.***3. Validate the outcomes of Aims 1 and 2 using experimental patch clamp assay and mutational analyses.*******The outcomes of our proposal will have a significant positive impact on Canadian biological sciences and the resulting computational framework may ultimately be scaled up and automated for use in industry and academia.*****