Structural and Functional Analysis of a β2-Adrenergic Receptor Complex with GRK5.

The phosphorylation of agonist-occupied G-protein-coupled receptors (GPCRs) by GPCR kinases (GRKs) functions to turn off G-protein signaling and turn on arrestin-mediated signaling. While a structural understanding of GPCR/G-protein and GPCR/arrestin complexes has emerged in recent years, the molecular architecture of a GPCR/GRK complex remains poorly defined. We used a comprehensive integrated approach of cross-linking, hydrogen-deuterium exchange mass spectrometry (MS), electron microscopy, mutagenesis, molecular dynamics simulations, and computational docking to analyze GRK5 interaction with the β2-adrenergic receptor (β2AR). These studies revealed a dynamic mechanism of complex formation that involves large conformational changes in the GRK5 RH/catalytic domain interface upon receptor binding. These changes facilitate contacts between intracellular loops 2 and 3 and the C terminus of the β2AR with the GRK5 RH bundle subdomain, membrane-binding surface, and kinase catalytic cleft, respectively. These studies significantly contribute to our understanding of the mechanism by which GRKs regulate the function of activated GPCRs. PAPERCLIP

Computational studies of drug-binding kinetics

The drug-receptor binding kinetics are defined by the rate at which a given drug associates with and dissociates from its binding site on its macromolecular receptor. The lead optimization stage of drug discovery programs usually emphasizes optimizing the affinity (as described by the equilibrium dissociation constant, Kd) of a drug which depends on the strength of its binding to a specific target. Since affinity is optimized under equilibrium conditions, it does not always ensures higher potency in vivo. There has been a growing consensus that, in addition to Kd, kinetic parameters (kon and koff ) should be optimized to improve the chances of a good clinical outcome. However, current understanding of the physicochemical features that contribute to differences in binding kinetics is limited. Experimental methods that are used to determine kinetic parameters for drug binding and unbinding are often time consuming and labor-intensive. Therefore, robust, high-throughput in silico methods are needed to predict binding kinetic parameters and to explore the mechanistic determinants of drug-protein binding. As the experimental data on drug-binding kinetics is continuously growing and the number of crystallographic structures of ligand-receptor complexes is also increasing, methods to compute three dimensional (3D) Quantitative-Structure-Kinetics relationships (QSKRs) offer great potential for predicting kinetic rate constants for new compounds. COMparative BINding Energy(COMBINE) analysis is one example of such approach that was developed to derive target-specific scoring functions based on molecular mechanics calculations. It has been used extensively to predict properties such as binding affinity, target selectivity, and substrate specificity. In this thesis, I made the first application of COMBINE analysis to derive Quantitative Structure-Kinetics Relationships (QSKRs) for the dissociation rates. I obtained models for koff of inhibitors of HIV-1 protease and heat shock protein 90 (HSP90) with very good predictive power and identified the key ligand-receptor interactions that contribute to the variance in binding kinetics. With technological and methodological advances, the use of all-atom unbiased Molecular Dynamics (MD) simulations can allow sampling upto the millisecond timescale and investigation of the kinetic profile of drug binding and unbinding to a receptor. However, the residence times of drug-receptor complexes are usually longer than the timescales that are feasible to simulate using conventional molecular dynamics techniques. Enhanced sampling methods can allow faster sampling of protein and ligand dynamics, thereby resulting in application of MD techniques to study longer timescale processes. I have evaluated the application of Tau-Random Acceleration Molecular Dynamics (Tau-RAMD), an enhanced sampling method based on MD, to compute the relative residence times of a series of compounds binding to Haspin kinase. A good correlation (R2 = 0.86) was observed between the computed residence times and the experimental residence times of these compounds. I also performed interaction energy calculations, both at the quantum chemical level and at the molecular mechanics level, to explain the experimental observation that the residence times of kinase inhibitors can be prolonged by introducing halogen-aromatic pi interactions between halogen atoms of inhibitors and aromatic residues at the binding site of kinases. I determined different energetic contributions to this highly polar and directional halogen-bonding interaction by partitioning the total interaction energy calculated at the quantum-chemical level into its constituent energy components. It was observed that the major contribution to this interaction energy comes from the correlation energy which describes second-order intermolecular dispersion interactions and the correlation corrections to the Hartree-Fock energy. In addition, a protocol to determine diffusional kon rates of low molecular weight compounds from Brownian Dynamics (BD) simulations of protein-ligand association was established using SDA 7 software. The widely studied test case of benzamidine binding to trypsin was used to evaluate a set of parameters and a robust set of optimal parameters was determined that should be generally applicable for computing the diffusional association rate constants of a wide range of protein-ligand binding pairs. I validated this protocol on inhibitors of several targets with varying complexity such as Human Coagulation Factor Xa, Haspin kinase and N1 Neuraminidase, and the computed diffusional association rate constants were compared with the experiments. I contributed to the development of a toolbox of computational methods: KBbox (http://kbbox.h-its.org/toolbox/), which provides information about various computational methods to study molecular binding kinetics, and different computational tools that employ them. It was developed to guide researchers on the use of the different computational and simulation approaches available to compute the kinetic parameters of drug-protein binding

Strategies to calculate water binding free energies in protein–ligand complexes

Water molecules are commonplace in protein binding pockets, where they can typically form a complex between the protein and a ligand or become displaced upon ligand binding. As a result, it is often of great interest to establish both the binding free energy and location of such molecules. Several approaches to predicting the location and affinity of water molecules to proteins have been proposed and utilized in the literature, although it is often unclear which method should be used under what circumstances. We report here a comparison between three such methodologies, Just Add Water Molecules (JAWS), Grand Canonical Monte Carlo (GCMC), and double-decoupling, in the hope of understanding the advantages and limitations of each method when applied to enclosed binding sites. As a result, we have adapted the JAWS scoring procedure, allowing the binding free energies of strongly bound water molecules to be calculated to a high degree of accuracy, requiring significantly less computational effort than more rigorous approaches. The combination of JAWS and GCMC offers a route to a rapid scheme capable of both locating and scoring water molecules for rational drug design

Quantifying the Role of Water in Ligand-Protein Binding Processes

The aim of this thesis is to quantify the contributions of water thermodynamics to the binding free energy in protein-ligand complexes. Various computational tools were directly applied, implemented, benchmarked and discussed. An own implementation of the IFST formulation was developed to facilitate easy integration in workflows that are based on Schrödinger software. By applying the tool to a well-defined test set of congeneric ligand pairs, the potential of IFST for quantitative predictions in lead-optimization was assessed. Furthermore, FEP calculations were applied to an extended test set to validate if these simulations can accurately account for solvent displacement in ligand modifications. As a fast tool that has applications in virtual screening problems, we finally developed and validated a new scoring function that incorporates terms for protein and ligand desolvation. This resulted in total in three distinct studies, that all elucidated different aspects of water thermodynamics in CADD. These three studies are presented in the next section. In the conclusion, the results and implications of these studies are discussed jointly, as well with possible future developments. An additional study was focused on virtual screening and toxicity prediction at the androgen receptor, where distinguishing agonists and antagonists poses difficulties. We proposed and validated an approach based on MD simulations and ensemble docking to improve predictions of androgen agonists and antagonists

SOLVATION ENERGY OF BIOMOLECULAR STRUCTURES: A STUDY OF THE EFFECT OF SALT ON BIOMOLECULES THROUGH IMPLICIT AS WELL AS EXPLICIT SOLVATION METHODS

In the current dissertation, studies related to solvation energy of protein structures using implicit as well explicit solvation methods have been discussed. Special focus is given to explore effect of salt on the fold stability of proteins and enzymes. Salt plays a crucial role in the functioning of all proteins, enzymes and nucleic acids. Change in salt concentration of the medium has large impact on stability and activity of these biological macromolecules. Therefore exploring mechanism of salt effect on them and development of an efficient model to calculate the salt effect has fundamental as well as practical importance in the field of sciences. In chapter two the development of an implicit solvation model to calculate salt effect on the fold stability of proteins and enzymes is shown. In combination of standard Poisson-Boltzmann formalism to calculate polar solvation energy, newly developed microscopic surface tension parameter as a function of ionic strength is used in the non-polar component of solvation free energy. The model was tested on series of Cold shock proteins whose stability as a function of NaCl concentration was calculated previously through experiments. Then the model was successfully used to explain the basis of experimentally observed increased stability of HIV-1 protease in the presence of high concentration of NaCl. Further, the same model also showed ability to capture salt specific Hofmeister effect on Cold shock proteins by using salt specific surface tension parameter. In the third chapter, similar studies were extended through molecular dynamics simulations of explicit solvated aqueous systems of protein and salt. Effect of salt on the translation and rotational motion of bulk water as well as water in different layers from protein surface was closely monitored. Self hydration of salt ions was seen to follow their rank in Hofmeister series. Alternatively effect of salt on rotational motion of water in different layers from protein surface showed that rank of an ion in Hofmeister series have no significant correlation with its effect on water structure making or breaking properties. The largest impact of salt on restricted motion of water was seen on the layer of water which is on the brink of being hydration water and bulk water. This is the same layer where water is been exchanged continually between hydrated water and bulk water. With these results, it can be articulated that effect of salt on the exchange rate of water between hydration shell and bulk may also be behind the origin of Hofmeister effect on protein. After looking at the salt effect through explicit as well as implicit solvation methods, in chapter four we will compare generalized Born with a simple switching (GBSW) implicit solvent and explicit solvent using TIP3P water model effect of solvent viscosity on peptide dynamics. We compared both solvents to see if absence of solvent viscosity and equilibration of solvent\u27s degrees of freedom makes implicit solvent faster in sampling same conformational phase space than explicit solvent. To reach same equilibrium and sample phase space GBSW proved to be faster by factor of 10 than explicit solvent. An additional modified explicit solvent which thermodynamically identical to the original but higher in viscosity was studied too. The results confirmed that equilibrium properties of peptide calculated through implicit or explicit solvent matches and the efficiency of implicit solvent to sample similar phase space comes from inherent lack of friction and viscosity

A combined cryo-EM and molecular dynamics approach reveals the mechanism of ErmBL-mediated translation arrest

Nascent polypeptides can induce ribosome stalling, regulating downstream genes. Stalling of ErmBL peptide translation in the presence of the macrolide antibiotic erythromycin leads to resistance in Streptococcus sanguis. To reveal this stalling mechanism we obtained 3.6-angstrom-resolution cryo-EM structures of ErmBL-stalled ribosomes with erythromycin. The nascent peptide adopts an unusual conformation with the C-terminal Asp10 side chain in a previously unseen rotated position. Together with molecular dynamics simulations, the structures indicate that peptide-bond formation is inhibited by displacement of the peptidyl-tRNA A76 ribose from its canonical position, and by non-productive interactions of the A-tRNA Lys11 side chain with the A-site crevice. These two effects combine to perturb peptide-bond formation by increasing the distance between the attacking Lys11 amine and the Asp10 carbonyl carbon. The interplay between drug, peptide and ribosome uncovered here also provides insight into the fundamental mechanism of peptide-bond formation