Investigating detailed interactions between novel PAR1 antagonist F16357 and the receptor using docking and molecular dynamic simulations

The domino effect triggered by the tethered ligand of the protease activated receptors

Protease activated receptors (PARs) are G-protein coupled receptors (GPCRs) that have a unique activation mechanism. Unlike other GPCRs that can be activated by free ligands, under physiological conditions, PARs are activated by the tethered ligand, which is a part of their N-terminus that is unmasked by proteolysis. It has been 30 years since the first member of the family, PAR1, was identified. In this review, we will discuss this unique tethered ligand mediate receptor activation of PARs in detail: how they interact with the proteases, the complex structural rearrangement of the receptors upon activation, and the termination of the signaling. We also summarize the structural studies of the PARs and how single nucleotide polymorphisms impact the receptor reactivity. Finally, we review the current strategies for inhibiting PAR function with therapeutic targets for anti-thrombosis. The focus of this review is PAR1 and PAR4 as they are the thrombin signal mediators on human platelets and therapeutics targets. We also include the structural studies of PAR2 as it informs the mechanism of action for PARs in general.

A Definition of "Multitargeticity": Identifying Potential Multitarget and Selective Ligands Through a Vector Analysis

The design of multitarget drugs is an essential area of research in Medicinal Chemistry since they have been proposed as potential therapeutics for the management of complex diseases. However, defining a multitarget drug is not an easy task. In this work, we propose a vector analysis for measuring and defining "multitargeticity." We developed terms, such as order and force of a ligand, to finally reach two parameters: multitarget indexes 1 and 2. The combination of these two indexes allows discrimination of multitarget drugs. Several training sets were constructed to test the usefulness of the indexes: an experimental training set, with real affinities, a docking training set, within theoretical values, and an extensive database training set. The indexes proved to be useful, as they were used independently in silico and experimental data, identifying actual multitarget compounds and even selective ligands in most of the training sets. We then applied these indexes to evaluate a virtual library of potential ligands for targets related to multiple sclerosis, identifying 10 compounds that are likely leads for the development of multitarget drugs based on their in silico behavior. With this work, a new milestone is made in the way of defining multitargeticity and in drug design.

Probing the cooperative mechanism of the μ–δ opioid receptor heterodimer by multiscale simulation

The activation-cooperativity of the μ–δ opioid receptor heterodimer was probed by multiscale simulation coupled with a protein structure network.