Accelerated molecular dynamics simulations of ligand binding to a muscarinic G-protein-coupled receptor

Localization of Millisecond Dynamics: Dihedral Entropy from Accelerated MD

Here, we demonstrate a method to capture local dynamics on a time scale 3 orders of magnitude beyond state-of-the-art simulation approaches. We apply accelerated molecular dynamics simulations for conformational sampling and extract reweighted backbone dihedral distributions. Local dynamics are characterized by torsional probabilities, resulting in residue-wise dihedral entropies. Our approach is successfully validated for three different protein systems of increasing size: alanine dipeptide, bovine pancreatic trypsin inhibitor (BPTI), and the major birch pollen allergen Bet v 1a. We demonstrate excellent agreement of flexibility profiles with both large-scale computer simulations and NMR experiments. Thus, our method provides efficient access to local protein dynamics on extended time scales of high biological relevance.

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.

G-protein coupled receptors: advances in simulation and drug discovery

G-protein coupled receptors (GPCRs), the largest family of human membrane proteins, mediate cellular signaling and represent primary targets of about one third of currently marketed drugs. GPCRs undergo highly dynamic structural transitions during signal transduction, from binding of extracellular ligands to coupling with intracellular effector proteins. Molecular dynamics (MD) simulations have been utilized to investigate GPCR signaling mechanisms (such as pathways of ligand binding and receptor activation/deactivation) and to design novel small-molecule drug candidates. Future research directions point towards modeling cooperative binding of multiple orthosteric and allosteric ligands to GPCRs, GPCR oligomerization and interactions of GPCRs with different intracellular signaling proteins. Through methodological and supercomputing advances, MD simulations will continue to provide important insights into GPCR signaling mechanisms and further facilitate structure-based drug design.

Revealing Atomic-Level Mechanisms of Protein Allostery with Molecular Dynamics Simulations

Molecular dynamics (MD) simulations have become a powerful and popular method for the study of protein allostery, the widespread phenomenon in which a stimulus at one site on a protein influences the properties of another site on the protein. By capturing the motions of a protein's constituent atoms, simulations can enable the discovery of allosteric binding sites and the determination of the mechanistic basis for allostery. These results can provide a foundation for applications including rational drug design and protein engineering. Here, we provide an introduction to the investigation of protein allostery using molecular dynamics simulation. We emphasize the importance of designing simulations that include appropriate perturbations to the molecular system, such as the addition or removal of ligands or the application of mechanical force. We also demonstrate how the bidirectional nature of allostery-the fact that the two sites involved influence one another in a symmetrical manner-can facilitate such investigations. Through a series of case studies, we illustrate how these concepts have been used to reveal the structural basis for allostery in several proteins and protein complexes of biological and pharmaceutical interest.

Mechanistic Studies on the Stereoselectivity of the Serotonin 5-HT1A Receptor

G‐protein‐coupled receptors (GPCRs) are involved in a wide range of physiological processes, and they have attracted considerable attention as important targets for developing new medicines. A central and largely unresolved question in drug discovery, which is especially relevant to GPCRs, concerns ligand selectivity: Why do certain molecules act as activators (agonists) whereas others, with nearly identical structures, act as blockers (antagonists) of GPCRs? To address this question, we employed all‐atom, long‐timescale molecular dynamics simulations to investigate how two diastereomers (epimers) of dihydrofuroaporphine bind to the serotonin 5‐HT_1A receptor and exert opposite effects. By using molecular interaction fingerprints, we discovered that the agonist could mobilize nearby amino acid residues to act as molecular switches for the formation of a continuous water channel. In contrast, the antagonist epimer remained firmly stabilized in the binding pocket.

Activation and conformational dynamics of a class B G-protein-coupled glucagon receptor

The human glucagon receptor (GCGR) is a class B G-protein-coupled receptor (GPCR). The GCGR can be activated by glucagon and regulates the release of glucose. The GCGR has been proposed to be an important drug target for type 2 diabetes. Based on the structural model of a full-length glucagon-bound GCGR (glu-GCGR), we performed accelerated molecular dynamics (aMD) simulations, potential of mean force (PMF) calculations, cross-correlation analysis and community network analysis to study the activation mechanism and the conformational dynamics during the activation process. The PMF map depicts three different conformational states of the GCGR: the inactive, intermediate and active states. The activation of the GCGR is characterized by the outward movement of the intracellular side of helix VI. In the active state of the GCGR, the Arg173(2.46)-Ser350(6.41) and Glu245(3.50)-Thr351(6.42) hydrogen bonds break, and the χ1 rotamer of Phe322(5.54) changes from perpendicular to parallel to helix VI. The binding of the agonist glucagon decreases the correlated motions of the extracellular loops (ELCs) and the helices around the glucagon-binding site. During the activation of the GCGR, the connections between the intracellular sides of helices become weaker, and the connections between glucagon and ECLs and the extracellular sides of helices become stronger. These facilitate G-protein coupling on the intracellular side and glucagon binding on the extracellular side, and stabilize the GCGR in the active state. We expect that this study can provide useful information on the activation mechanism of the GCGR and facilitate the future design of GCGR inhibitors.

A Molecular Mechanism for Sequential Activation of a G Protein-Coupled Receptor

Ligands targeting G protein-coupled receptors (GPCRs) are currently classified as either orthosteric, allosteric, or dualsteric/bitopic. Here, we introduce a new pharmacological concept for GPCR functional modulation: sequential receptor activation. A hallmark feature of this is a stepwise ligand binding mode with transient activation of a first receptor site followed by sustained activation of a second topographically distinct site. We identify 4-CMTB (2-(4-chlorophenyl)-3-methyl-N-(thiazol-2-yl)butanamide), previously classified as a pure allosteric agonist of the free fatty acid receptor 2, as the first sequential activator and corroborate its two-step activation in living cells by tracking integrated responses with innovative label-free biosensors that visualize multiple signaling inputs in real time. We validate this unique pharmacology with traditional cellular readouts, including mutational and pharmacological perturbations along with computational methods, and propose a kinetic model applicable to the analysis of sequential receptor activation. We envision this form of dynamic agonism as a common principle of nature to spatiotemporally encode cellular information.

Advances in free-energy-based simulations of protein folding and ligand binding

Free-energy-based simulations are increasingly providing the narratives about the structures, dynamics and biological mechanisms that constitute the fabric of protein science. Here, we review two recent successes. It is becoming practical: first, to fold small proteins with free-energy methods without knowing substructures and second, to compute ligand-protein binding affinities, not just their binding poses. Over the past 40 years, the timescales that can be simulated by atomistic MD are doubling every 1.3 years--which is faster than Moore's law. Thus, these advances are not simply due to the availability of faster computers. Force fields, solvation models and simulation methodology have kept pace with computing advancements, and are now quite good. At the tip of the spear recently are GPU-based computing, improved fast-solvation methods, continued advances in force fields, and conformational sampling methods that harness external information.

Computational insights into different inhibition modes of the κ-opioid receptor with antagonists LY2456302 and JDTic

Residence time calculations were carried out based on binding free energy scanning of the metadynamics simulations on LY2456302–κ-OR and JDTic–κ-OR systems.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.