472 research outputs found

    On the Role of Electrostatics in Protein–Protein Interactions

    Get PDF
    The role of electrostatics in protein–protein interactions and binding is reviewed in this paper. A brief outline of the computational modeling, in the framework of continuum electrostatics, is presented and the basic electrostatic effects occurring upon the formation of the complex are discussed. The effect of the salt concentration and pH of the water phase on protein–protein binding free energy is demonstrated which indicates that the increase of the salt concentration tends to weaken the binding, an observation that is attributed to the optimization of the charge–charge interactions across the interface. It is pointed out that the pH-optimum (pH of optimal binding affinity) varies among the protein–protein complexes, and perhaps is a result of their adaptation to particular subcellular compartments. The similarities and differences between hetero- and homo-complexes are outlined and discussed with respect to the binding mode and charge complementarity

    Electrostatic Properties of Protein-Protein Complexes

    Get PDF
    Statistical electrostatic analysis of 37 protein-protein complexes extracted from the previously developed database of protein complexes (ProtCom, http://www.ces.clemson.edu/compbio/protcom) is presented. It is shown that small interfaces have a higher content of charged and polar groups compared to large interfaces. In a vast majority of the cases the average pKa shifts for acidic residues induced by the complex formation are negative, indicating that complex formation stabilizes their ionizable states, whereas the histidines are predicted to destabilize the complex. The individual pKa shifts show the same tendency since 80% of the interfacial acidic groups were found to lower their pKas, whereas only 25% of histidines raise their pKa upon the complex formation. The interfacial groups have been divided into three sets according to the mechanism of their pKa shift, and statistical analysis of each set was performed. It was shown that the optimum pH values (pH of maximal stability) of the complex tend to be the same as the optimum pH values of the complex components. This finding can be used in the homology-based prediction of the 3D structures of protein complexes, especially when one needs to evaluate and rank putative models. It is more likely for a model to be correct if both components of the model complex and the entire complex have the same or at least similar values of the optimum pH

    An investigation of structural stability in protein-ligand complexes reveals the balance between order and disorder

    Full text link
    The predominant view in structure-based drug design is that small-molecule ligands, once bound to their target structures, display a well-defined binding mode. However, structural stability (robustness) is not necessary for thermodynamic stability (binding affinity). In fact, it entails an entropic penalty that counters complex formation. Surprisingly, little is known about the causes, consequences and real degree of robustness of protein-ligand complexes. Since hydrogen bonds have been described as essential for structural stability, here we investigate 469 such interactions across two diverse structure sets, comprising of 79 drug-like and 27 fragment ligands, respectively. Completely constricted protein-ligand complexes are rare and may fulfill a functional role. Most complexes balance order and disorder by combining a single anchoring point with looser regions. 25% do not contain any robust hydrogen bond and may form loose structures. Structural stability analysis reveals a hidden layer of complexity in protein-ligand complexes that should be considered in ligand design

    A Medicinal Chemist’s Guide to Molecular Interactions

    Get PDF

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

    Get PDF
    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

    Characterization and exploitation of protein ligand interactions for structure based drug design

    Get PDF
    Most characterised protein-small molecule interactions that display a change in heat capacity (\bigtriangleupCp) occur with a negative \bigtriangleupCp value. This is often attributed to solvent reorganisation from reduction in solvent accessible apolar surface area accompanying complex formation. Positive \bigtriangleupCp values have not been widely reported and could typically be attributed to an increased solvent accessible apolar surface area, desolvation of polar surface area or structural transitions in the biomolecular complex. Heat shock protein-90 (Hsp90) is one of the abundant and important molecular ATP-dependent chaperones. The N-terminal domain of Hsp90 contains ATP/ADP binding site, where Hsp90-ADP interactions proceed with a large positive \bigtriangleupCp of 2.35 ± 0.46 kJ·mol-1·K-1. Interestingly geldanamycin, an Hsp90 inhibitor which binds to the same N-Hsp90-ADP/ATP binding site, interacts with a negative \bigtriangleupCp of -0.39 ± 0.04 kJ·mol-1·K-1. The semi-empirical correlation of the solvent accessible surface area change does not match well with the observed \bigtriangleupCp. This prompted us to investigate various factors affecting the thermodynamics of protein-small molecule binding including varying buffers, differing salt concentration, altering pH, substitution of different metal cations and performing interactions in heavy water. Molecular dynamics simulation and NMR studies have allowed us to disregard structural changes of N-Hsp90-ADP molecule from giving rise to positive \bigtriangleupCp. From a combination of these calorimetric, simulation and structural studies we have gathered a considerable body of evidence suggesting that the change in accessible surface area, ionic interactions and resultant desolvation of water molecules from the surface of a Mg2+ ion can contribute substantially to a positive \bigtriangleupCp. We conclude that this unique result appears to come from extensive disruption of the tightly bound water molecules present around Mg2+-ADP after binding to Hsp90, which then gives rise to a positive \bigtriangleupCp. In addition to these findings, the thermodynamics of 18 structurally related CDK2 inhibitors were investigated using ITC. CDK2 is a member of cyclin dependent kinases implicated in eukaryotic cell cycle progression and control. This investigation showed that even conservative changes in small molecule structure can reveal large variation in thermodynamic signature, while simple concepts such as van der Waals interactions, steric hindrance, and hydrophobicity are insufficient to explain it

    Quantitative models of biomolecular hydration thermodynamics

    Get PDF
    This thesis explores the use of cell theory calculations to characterise hydration thermodynamics in small molecules (cations, ions, hydrophobic molecules), proteins and protein-ligand complexes. Cell theory uses the average energies, forces and torques of a water molecule measured in its molecular frame of reference to parameterise a harmonic potential. From this harmonic potential analytical expressions for entropies and enthalpies are derived. In order to spatially resolve these thermodynamic quantities grid points are used to store the forces, torques, and energies of nearby waters which giving rise to the new grid cell theory (GCT) model. GCT allows one to monitor hydration thermodynamics at heterogeneous environments such as that of a protein surface. Through an understanding of the hydration thermodynamics around the protein and particularly around binding sites, robust protein-ligand scoring functions are created to estimate and rank protein-ligand binding affinities. GCT was then able to retrospectively rationalise the structure activity relationships made during lead optimisation of various ligand-protein systems including Hsp90, FXa, scytalone dehydratase among others. As well as this it was also used to analyse water behaviour in various protein environments with a dataset of 17 proteins. The grid cell theory implementation provides a theoretical framework which can aid the iterative design of ligands during the drug discovery and lead optimisation processes, and can provide insight into the effect of protein environment to hydration thermodynamics in general

    Computational studies of drug-binding kinetics

    Get PDF
    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
    corecore