Protamine binding to surfactants in emulsions: modelling and computer simulation

The cationic antimicrobial peptide, protamine, has been found to destabilize oil/water (O/W) emulsions formed using soy lecithin or Tween-20. Experiments suggested that the destabilization took place via flocculation. We have modelled the interactions between protamine and an O/W interface stabilized by hypothetical amphiphilic molecule (HAM) surfactants. The intent was to suggest what properties such surfactants must possess in order that protamine will not destabilize an O/W emulsion stabilized by HAMs. We considered interfaces formed from mixtures of neutral HAMs together with (a) positively charged HAMs which possess an attractive (van der Waals, hydrogen bonding) interaction with protamine or with (b) negatively charged HAMs with no significant attractive interaction. We represented the oil and water as continuum dielectrics, with the water containing 100 mM monovalent ions and we carried out Monte Carlo computer simulations. We found that a single protamine does not bind to a single interface in case (a) but that there is a range of charged-HAM concentration, c, for which the binding of protamine becomes progressively stronger as c increases in case (b). We investigated stability by studying under what conditions protamines will cause the aggregation of two HAM-stabilized interfaces, and we have identified values of c for which the interfaces are stable. We note that the transition from bound to unbound states of two HAM interfaces with five protamines are examples of entropy-driven unbinding transitions with the entropy of the protamines overcoming the net attractive interactions. We conclude by identifying regions of the phase diagram in which stable emulsions should exist in the presence of protamine.     

Large scale relative protein ligand binding affinities using non-equilibrium alchemy

Ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design. However, their broad uptake and impact is held back by the notoriously complex setup of the calculations. Only a few tools other than the free energy perturbation approach by Schrödinger Inc. (referred to as FEP+) currently enable end-to-end application. Here, we present for the first time an approach based on the open-source software pmx that allows to easily set up and run alchemical calculations for diverse sets of small molecules using the GROMACS MD engine. The method relies on theoretically rigorous non-equilibrium thermodynamic integration (TI) foundations, and its flexibility allows calculations with multiple force fields. In this study, results from the Amber and Charmm force fields were combined to yield a consensus outcome performing on par with the commercial FEP+ approach. A large dataset of 482 perturbations from 13 different protein–ligand datasets led to an average unsigned error (AUE) of 3.64 ± 0.14 kJ mol⁻¹, equivalent to Schrödinger''s FEP+ AUE of 3.66 ± 0.14 kJ mol⁻¹. For the first time, a setup is presented for overall high precision and high accuracy relative protein–ligand alchemical free energy calculations based on open-source software.

Relative ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design.     

Theory and simulation of diffusion-influenced, stochastically gated ligand binding to buried sites

We consider the diffusion-influenced rate coefficient of ligand binding to a site located in a deep pocket on a protein; the binding pocket is flexible and can reorganize in response to ligand entrance. We extend to this flexible protein-ligand system a formalism developed previously [A. M. Berezhkovskii, A, Szabo, and H.-X. Zhou, J. Chem. Phys. 135, 075103 (2011)] for breaking the ligand-binding problem into an exterior problem and an interior problem. Conformational fluctuations of a bottleneck or a lid and the binding site are modeled as stochastic gating. We present analytical and Brownian dynamics simulation results for the case of a cylindrical pocket containing a binding site at the bottom. Induced switch, whereby the conformation of the protein adapts to the incoming ligand, leads to considerable rate enhancement.     

Molecular dynamics simulation of the ligand binding domain of mGluR1 in response to agonist and antagonist binding

The interdomain movements of the ligand binding domain (LBD) of mGluR1 in response to agonist or antagonist binding are studied by 2 ns molecular dynamics (MD) simulations. Our results indicate that MD is able to reproduce many of the experimentally determined features of the open and closed conformations of LBD. Analysis of the ligand behavior over time allows to delineate some of the molecular determinants responsible for the agonist-induced or antagonist-blocked LBD responses.     

Rapid and accurate estimation of protein–ligand relative binding affinities using site-identification by ligand competitive saturation

Predicting relative protein–ligand binding affinities is a central pillar of lead optimization efforts in structure-based drug design. The site identification by ligand competitive saturation (SILCS) methodology is based on functional group affinity patterns in the form of free energy maps that may be used to compute protein–ligand binding poses and affinities. Presented are results obtained from the SILCS methodology for a set of eight target proteins as reported originally in Wang et al. (J. Am. Chem. Soc., 2015, 137, 2695–2703) using free energy perturbation (FEP) methods in conjunction with enhanced sampling and cycle closure corrections. These eight targets have been subsequently studied by many other authors to compare the efficacy of their method while comparing with the outcomes of Wang et al. In this work, we present results for a total of 407 ligands on the eight targets and include specific analysis on the subset of 199 ligands considered previously. Using the SILCS methodology we can achieve an average accuracy of up to 77% and 74% when considering the eight targets with their 199 and 407 ligands, respectively, for rank-ordering ligand affinities as calculated by the percent correct metric. This accuracy increases to 82% and 80%, respectively, when the SILCS atomic free energy contributions are optimized using a Bayesian Markov-chain Monte Carlo approach. We also report other metrics including Pearson''s correlation coefficient, Pearlman''s predictive index, mean unsigned error, and root mean square error for both sets of ligands. The results obtained for the 199 ligands are compared with the outcomes of Wang et al. and other published works. Overall, the SILCS methodology yields similar or better-quality predictions without a priori need for known ligand orientations in terms of the different metrics when compared to current FEP approaches with significant computational savings while additionally offering quantitative estimates of individual atomic contributions to binding free energies. These results further validate the SILCS methodology as an accurate, computationally efficient tool to support lead optimization and drug discovery.

Predicting relative protein–ligand binding affinities is a central pillar of lead optimization efforts in structure-based drug design.     

New insights from molecular dynamic simulation studies of the multiple binding modes of a ligand with G-quadruplex DNA

G-quadruplexes are higher-order DNA and RNA structures formed from guanine-rich sequences. These structures have recently emerged as a new class of potential molecular targets for anticancer drugs. An understanding of the three-dimensional interactions between small molecular ligands and their G-quadruplex targets in solution is crucial for rational drug design and the effective optimization of G-quadruplex ligands. Thus far, rational ligand design has been focused mainly on the G-quartet platform. It should be noted that small molecules can also bind to loop nucleotides, as observed in crystallography studies. Hence, it would be interesting to elucidate the mechanism underlying how ligands in distinct binding modes influence the flexibility of G-quadruplex. In the present study, based on a crystal structure analysis, the models of a tetra-substituted naphthalene diimide ligand bound to a telomeric G-quadruplex with different modes were built and simulated with a molecular dynamics simulation method. Based on a series of computational analyses, the structures, dynamics, and interactions of ligand-quadruplex complexes were studied. Our results suggest that the binding of the ligand to the loop is viable in aqueous solutions but dependent on the particular arrangement of the loop. The binding of the ligand to the loop enhances the flexibility of the G-quadruplex, while the binding of the ligand simultaneously to both the quartet and the loop diminishes its flexibility. These results add to our understanding of the effect of a ligand with different binding modes on G-quadruplex flexibility. Such an understanding will aid in the rational design of more selective and effective G-quadruplex binding ligands.     

Absolute and relative configuartion of L-660,631

The relative and absolute stereochemistry of the potent antifungal agent L-660,631 has been determined to be 1 by synthesis of an appropriate degradation product.     

Determination of ligand to DNA binding parameters from two-dimensional DSC curves

The application of the theory of DNA denaturation linked to ligand binding to differential scanning calorimetry (DSC) is a useful tool to simultaneously characterize the energetics of denaturation and binding. Although the general theory is well known, the current DSC-based approaches to study the DNA–ligand interaction do not utilize the full potential of this method. In this paper, we propose the analytical approach for detailed analysis of DNA–ligand interaction from DSC data. The DNA macromolecule is represented as an assembly of cooperative units which melt by two-state model. The explicit account of ligand distribution on polymeric DNA and the temperature dependences of melting and binding constants, as well as of enthalpies, are considered. Such approach enables to extract the binding constant, stoichiometry, enthalpy, entropy, and heat capacity changes from multiple excess heat capacity profiles obtained at varying concentrations of the ligand (i.e. two-dimensional DSC curves). The applicability of the developed approach was demonstrated using an example salmon testes DNA–proflavine DSC experiment. The full set of DNA melting and proflavine binding thermodynamic parameters was obtained. Comparison of the proflavine binding parameters obtained from DSC with those determined from alternative experimental methods has proved the usefulness of the DSC method for evaluation of the binding thermodynamics in DNA–ligand system. In addition, the approach developed in the present study, allows to evaluate the concentration dependences of all species in solution as a function of temperature. Analysis of these dependences has enabled to interpret fine effects on the DSC curves of DNA–ligand complexes.     

Absolute and relative binding affinity of cucurbit[7]uril towards a series of cationic guests

We determined the relative binding constants (K_rel) for guests 1–19 towards cucurbit[7]uril by ¹H NMR competition experiments in 100 mM Na₃PO₄-buffered D₂O. In these experiments, we use guest 11 as the reference guest because of its strong binding towards CB[7] and its advantageous spectroscopic properties (e.g. slow exchange on NMR timescale and distinct resonances for key protons). To convert the determined K_rel values to absolute binding constants, we performed a direct UV–vis titration of 1 with CB[7] to determine K_a for CB[7]√1. The trends in the determined values of K_rel and K_a are discussed with respect to the importance of the concentration of metal ions in the buffer, the influence of hydroxyl groups located at the portals or inside the CB[7] cavity, geometry of the guest (e.g. regioisomers), the number of guest C atoms and secondary electrostatic interactions.     

Kinetics of ligand binding to membrane receptors from equilibrium fluctuation analysis of single binding events

Equilibrium fluctuation analysis of single binding events has been used to extract binding kinetics of ligand interactions with cell-membrane bound receptors. Time-dependent total internal reflection fluorescence (TIRF) imaging was used to extract residence-time statistics of fluorescently stained liposomes derived directly from cell membranes upon their binding to surface-immobilized antibody fragments. The dissociation rate constants for two pharmaceutical relevant antibodies directed against different B-cell expressed membrane proteins was clearly discriminated, and the affinity of the interaction could be determined by inhibiting the interaction with increasing concentrations of soluble antibodies. The single-molecule sensitivity made the analysis possible without overexpressed membrane proteins, which makes the assay attractive in early drug-screening applications.     

Computation of relative binding free energy for an inhibitor and its analogs binding with Erk kinase using thermodynamic integration MD simulation

In the present study, we carried out thermodynamic integration molecular dynamics simulation for a pair of analogous inhibitors binding with Erk kinase to investigate how computation performs in reproducing the relative binding free energy. The computation with BCC-AM1 charges for ligands gave ?1.1?kcal/mol, deviated from experimental value of ?2.3?kcal/mol by 1.2?kcal/mol, in good agreement with experimental result. The error of computed value was estimated to be 0.5?kcal/mol. To obtain convergence, switching vdw interaction on and off required approximately 10 times more CPU time than switching charges. Residue-based contributions and hydrogen bonding were analyzed and discussed. Furthermore, subsequent simulation using RESP charge for ligand gave ΔΔG of ?1.6?kcal/mol. The computed results are better than the result of ?5.6?kcal/mol estimated using PBSA method in a previous study. Based on these results, we further carried out computations to predict ΔΔG for five new analogs, focusing on placing polar and nonpolar functional groups at the meta site of benzene ring shown in the Fig.?1, to see if these ligands have better binding affinity than the above ligands. The computations resulted that a ligand with polar –OH group has better binding affinity than the previous examined ligand by ~2.0?kcal/mol and two other ligands have better affinity by ~1.0?kcal/mol. The predicted better inhibitors of this kind should be of interest to experimentalist for future experimental enzyme and/or cell assays.     

Multiscale modeling and simulation methods with applications to dendritic polymers

Dendrimers and hyperbranched polymers represent a novel class of structurally controlled macromolecules derived from a branches-upon-branches structural motif. The synthetic procedures developed for dendrimer preparation permit nearly complete control over the critical molecular design parameters, such as size, shape, surface/interior chemistry, flexibility, and topology. Dendrimers are well defined, highly branched macromolecules that radiate from a central core and are synthesized through a stepwise, repetitive reaction sequence that guarantees complete shells for each generation, leading to polymers that are mono-disperse. This property of dendrimers makes it particularly natural to coarsen interactions in order to simulate dynamic processes occurring at larger length and longer time scales. In this paper, we describe methods to construct 3-dimensional molecular structures of dendrimers (Continuous Configuration Boltzmann Biased direct Monte Carlo, CCBB MC) and methods towards coarse graining dendrimer interactions (NEIMO and hierarchical NEIMO methods) and representation of solvent dendrimer interactions through continuum solvation theories, Poisson–Boltzmann (PB) and Surface Generalized Born (SGB) methods. We will describe applications to PAMAM, stimuli response hybrid star-dendrimer polymers, and supra molecular assemblies crystallizing to A15 colloidal structure or Pm6m liquid crystals.     

A plastic phase of water from computer simulation

We report a member of ices called plastic or rotator phase, in which individual water molecules make facile rotations as in liquid state but are held tightly in an ordered structure. Molecular dynamics simulations of three classical models of water show that a plastic ice phase appears at a temperature when ice VII is heated or liquid water is cooled at high pressures above several gigapascals. A large amount of latent heat is absorbed when ice VII is transformed to the rotator phase at 590 K and 10 GPa, which is a typical characteristic of the plastic transitions for nearly spherical molecules. In addition to the spontaneous formation of plastic phase in the simulations, its existence is supported by robustness of plastic phase for hypothetical water with varying degrees of Coulombic interactions.     

Calculation of entropy with computer simulation methods

A new approximate method for calculating entropy with computer simulation methods is proposed. The sampling probability of an equilibrium configuration is calculated by means of the frequency of occurrence of what we call here local states (related to the state of the particle and its neighbors); hence entropy can be calculated as well. The method is applied to the Metropolis' Monte Carlo simulation for the case of the square Ising lattice. The results are in very good agreement with theory even close to the critical temperature. The method is used also to calculate non-equilibrium entropy.     

Partial enthalpies and related quantities in mixtures from computer simulation

We report a method of calculating partial molar quantities in mixtures by computer simulation. The method is based on an extension of Widom's potential distribution theorem and provides an alternative way of computing partial enthalpies and volumes.     

Influencing receptor-ligand binding mechanisms with multivalent ligand architecture

Multivalent ligands can function as inhibitors or effectors of biological processes. Potent inhibitory activity can arise from the high functional affinities of multivalent ligand-receptor interactions. Effector functions, however, are influenced not only by apparent affinities but also by alternate factors, including the ability of a ligand to cluster receptors. Little is known about the molecular features of a multivalent ligand that determine whether it will function as an inhibitor or effector. We envisioned that, by altering multivalent ligand architecture, ligands with preferences for different binding mechanisms would be generated. To this end, a series of 28 ligands possessing structural diversity was synthesized. This series provides the means to explore the effects of ligand architecture on the inhibition and clustering of a model protein, the lectin concanavalin A (Con A). The structural parameters that were varied include scaffold shape, size, valency, and density of binding elements. We found that ligands with certain architectures are effective inhibitors, but others mediate receptor clustering. Specifically, high molecular weight, polydisperse polyvalent ligands are effective inhibitors of Con A binding, whereas linear oligomeric ligands generated by the ring-opening metathesis polymerization have structural properties that favor clustering. The shape of a multivalent ligand also influences specific aspects of receptor clustering. These include the rate at which the receptor is clustered, the number of receptors in the clusters, and the average interreceptor distance. Our results indicate that the architecture of a multivalent ligand is a key parameter in determining its activity as an inhibitor or effector. Diversity-oriented syntheses of multivalent ligands coupled with effective assays that can be used to compare the contributions of different binding parameters may afford ligands that function by specific mechanisms.     

Heat capacity effects associated with urea and tetramethylurea hydration: insight from computer simulation

1. Download : Download high-res image (117KB)
2. Download : Download full-size image

     

Xanthene-based ligand with two adjacent beta-diiminato binding sites

A novel potential ligand has been designed where two beta-dialdimine units are linked by a xanthene backbone (H2Xanthdim). The synthesis proceeds via a double vinamidinium salt and the products of its hydrolysis (containing eneamine/malonaldehyde units), which were converted into H2Xanthdim via a reaction with 2,3-dimethylaniline. The reaction of H2Xanthdim with n-butyllithium yields ((Et2O)Li)2Xanthdim, which was isolated and crystallized. The crystal structures of both H2Xanthdim and its lithium salt are discussed.     

Comparison of thermodynamic integration and Bennett acceptance ratio for calculating relative protein‐ligand binding free energies

The performances of Bennett's acceptance ratio method and thermodynamic integration (TI) for the calculation of free energy differences in protein simulations are compared. For the latter, the standard trapezoidal rule, Simpson's rule, and Clenshaw‐Curtis integration are used as numerical integration methods. We evaluate the influence of the number and definition of intermediate states on the precision, accuracy, and efficiency of the free energy calculations. Our results show that non‐equidistantly spaced intermediate states are in some cases beneficial for the TI methods. Using several combinations of softness parameters and the λ power dependence, it is shown that these benefits are strongly dependent on the shape of the integrand. Although TI is more user‐friendly due to its simplicity, it was found that Bennett's acceptance ratio method is the more efficient method. It is also the least dependent on the choice of the intermediate states, making it more robust than TI. © 2013 Wiley Periodicals, Inc.