Geometric and potential driving formation and evolution of biomolecular surfaces

This paper presents new geometrical flow equations for the theoretical modeling of biomolecular surfaces in the context of multiscale implicit solvent models. To account for the local variations near the biomolecular surfaces due to interactions between solvent molecules, and between solvent and solute molecules, we propose potential driven geometric flows, which balance the intrinsic geometric forces that would occur for a surface separating two homogeneous materials with the potential forces induced by the atomic interactions. Stochastic geometric flows are introduced to account for the random fluctuation and dissipation in density and pressure near the solvent–solute interface. Physical properties, such as free energy minimization (area decreasing) and incompressibility (volume preserving), are realized by some of our geometric flow equations. The proposed approach for geometric and potential forces driving the formation and evolution of biological surfaces is illustrated by extensive numerical experiments and compared with established minimal molecular surfaces and molecular surfaces. Local modification of biomolecular surfaces is demonstrated with potential driven geometric flows. High order geometric flows are also considered and tested in the present work for surface generation. Biomolecular surfaces generated by these approaches are typically free of geometric singularities. As the speed of surface generation is crucial to implicit solvent model based molecular dynamics, four numerical algorithms, a semi-implicit scheme, a Crank–Nicolson scheme, and two alternating direction implicit (ADI) schemes, are constructed and tested. Being either stable or conditionally stable but admitting a large critical time step size, these schemes overcome the stability constraint of the earlier forward Euler scheme. Aided with the Thomas algorithm, one of the ADI schemes is found to be very efficient as it balances the speed and accuracy.      

The Lagrangian stochastic model for estimating footprint and water vapor fluxes over inhomogeneous surfaces

This study investigated a two-dimensional Lagrangian stochastic dispersion model for estimating water vapor fluxes and footprint over homogeneous and inhomogeneous surfaces. Over the homogeneous surface, particle trajectories were computed from a 2-D Lagrangian model forced by Eulerian velocity statistics determined by Monin–Obukhov similarity theory (MOST). For an inhomogeneous surface, the velocity and atmospheric stability profiles were computed using a second-order Eulerian closure model, and these local profiles were then used to drive the Lagrangian model. The model simulations were compared with water vapor flux measurements carried out above an irrigated bare soil site and an irrigated potato site. The inhomogeneity involved a step change in surface roughness, humidity, and temperature. Good agreement between eddy-correlation-measured and Lagrangian-model-predicted water vapor fluxes was found for both sites. Hence, this analysis demonstrates the practical utility of second-order closure models in conjunction with Lagrangian analysis to estimate the scalar footprint in planar inhomogeneous flows.     

A CFF 91-based Continuum Solvation Model: Solvation Free Energies of Small Organic Molecules and Conformations of the Alanine Dipeptide in Solution

Abstract

For molecular mechanics simulations of solvated molecules, it is important to use a consistent approach for calculating both the force field energy and the solvation free energy. A continuum solvation model based upon the atomic charges provided with the CFF91 force field is derived. The electrostatic component of the solvation free energy is described by the Poisson-Bolzmann equation while the nonpolar comonent of the solvation energy is assumed to be proportional to the solvent accessible surface area of the solute. Solute atomic radii used to describe the interface between the solute and solvent are fitted to reproduce the energies of small organic molecules. Data for 140 compounds are presented and compared to experiment and to the results from the well-characterized quantum mechanical solvation model AM1-SM2. In particular, accurate results are obtained for amino acid neutral analogues (mean unsigned error of 0.3 kcal/mol). The conformational energetics of the solvated alanine dipeptide is discussed.     

Optimizing the affinity and specificity of ligand binding with the inclusion of solvation effect

Solvation effect is an important factor for protein–ligand binding in aqueous water. Previous scoring function of protein–ligand interactions rarely incorporates the solvation model into the quantification of protein–ligand interactions, mainly due to the immense computational cost, especially in the structure‐based virtual screening, and nontransferable application of independently optimized atomic solvation parameters. In order to overcome these barriers, we effectively combine knowledge‐based atom–pair potentials and the atomic solvation energy of charge‐independent implicit solvent model in the optimization of binding affinity and specificity. The resulting scoring functions with optimized atomic solvation parameters is named as specificity and affinity with solvation effect (SPA‐SE). The performance of SPA‐SE is evaluated and compared to 20 other scoring functions, as well as SPA. The comparative results show that SPA‐SE outperforms all other scoring functions in binding affinity prediction and “native” pose identification. Our optimization validates that solvation effect is an important regulator to the stability and specificity of protein–ligand binding. The development strategy of SPA‐SE sets an example for other scoring function to account for the solvation effect in biomolecular recognitions. Proteins 2015; 83:1632–1642. © 2015 Wiley Periodicals, Inc.     

Simulation of Solvation Dynamics in H-Bonding Solvents: Dynamics of Solute–Solvent H-Bonds in Methanol–Water Mixtures

Molecular dynamics (MD) simulations have been undertaken in order to investigate the collective solvent reorganization following an instantaneous electronic charge transfer between distinct atomic sites of diatomic probe molecules immersed in methanol–water mixtures. Our previous studies of solvation dynamics in these mixtures [28,29] are extended here to the analysis of nonequilibrium time-dependent solute–solvent site–site pair distribution functions for the equimolar mixture using two different solute sizes. This has allowed us to obtain a more detailed picture of the solvent reorganization in response to the solute's excitation. Special attention is devoted to the dynamics of rupture and formation of hydrogen bonds between the smaller probe solute and solvent molecules, and its relationship to the molecular mechanisms of solvation dynamics in these systems on distinct time scales. This revised version was published online in June 2006 with corrections to the Cover Date.     

Computational fluid dynamics simulations of particle deposition in large-scale, multigenerational lung models

Computational fluid dynamics (CFD) has emerged as a useful tool for the prediction of airflow and particle transport within the human lung airway. Several published studies have demonstrated the use of Eulerian finite-volume CFD simulations coupled with Lagrangian particle tracking methods to determine local and regional particle deposition rates in small subsections of the bronchopulmonary tree. However, the simulation of particle transport and deposition in large-scale models encompassing more than a few generations is less common, due in part to the sheer size and complexity of the human lung airway. Highly resolved, fully coupled flowfield solution and particle tracking in the entire lung, for example, is currently an intractable problem and will remain so for the foreseeable future. This paper adopts a previously reported methodology for simulating large-scale regions of the lung airway (Walters, D. K., and Luke, W. H., 2010, "A Method for Three-Dimensional Navier-Stokes Simulations of Large-Scale Regions of the Human Lung Airway," ASME J. Fluids Eng., 132(5), p. 051101), which was shown to produce results similar to fully resolved geometries using approximate, reduced geometry models. The methodology is extended here to particle transport and deposition simulations. Lagrangian particle tracking simulations are performed in combination with Eulerian simulations of the airflow in an idealized representation of the human lung airway tree. Results using the reduced models are compared with those using the fully resolved models for an eight-generation region of the conducting zone. The agreement between fully resolved and reduced geometry simulations indicates that the new method can provide an accurate alternative for large-scale CFD simulations while potentially reducing the computational cost of these simulations by several orders of magnitude.     

Monte Carlo Study of Structural and Thermodynamic Properties of Liquid Chloroform Using a Five Site Model

A five site potential model combining Lennard–Jones plus Coulomb potential functions has been developed for chloroform molecule. The partial charges needed for Coulombic interactions were derived using the chelpg procedure implemented in the gaussian 92 program. These calculations were performed at the MP2 level with MC-311G* basis set for Cl and 6-311G** for C and H atoms. The parameters for the Lennard–Jones potentials were optimized to reproduce experimental values for the density and enthalpy of vaporization of the pure liquid at 298 K and 1 atm. The statistical mechanics calculations were performed with the Monte Carlo method in the isothermic and isobaric (NpT) ensemble. Besides the values obtained for density, ρ, and molar enthalpy of vaporization at constant pressure, Δ H_V, for liquid chloroform, results for molar volume, V_m, molar heat capacity, C_p, isobaric thermal expansivity, α_p, and isothermal compressibility, κ_T, for this pure liquid are also in very good agreement with experimental observations. Size effects on the values of thermodynamic properties were investigated. The potential model was also tested by computing the free energy for solvating one chloroform molecule into its own liquid at 298 K using a statistical perturbation approach. The result obtained compares well with the experimental value. Site–site pair correlation functions were calculated and are in good accordance with theoretical results available in the literature. Dipole–dipole correlation functions for the present five site model were also calculated at different carbon–carbon distances. These correlations were compared to those obtained using the four site model reported in the literature. An investigation of the solvent dependence of the relative free energy for cis/trans conversion of a hypothetical solute in TIP4P water and chloroform was accomplished. The results show strong interaction of water and chloroform molecules with the gauche conformer. The value obtained for the free energy barrier for cis/trans rotation in TIP4P water is higher than that for chloroform. This result is in agreement with the continuous theory for solvation as the conformer with higher dipole moment is more favoured by the solvent with higher dieletric constant. The results also show an increase in entropy as the solute goes from the cis to the trans geometry and this result is more appreciable in the aqueous solution. This revised version was published online in June 2006 with corrections to the Cover Date.     

Tomato ethylene receptor-CTR interactions: visualization of NEVER-RIPE interactions with multiple CTRs at the endoplasmic reticulum

In the model plant Arabidopsis, members of a family of two-componentsystem His kinase-like ethylene receptors have direct protein–proteininteractions with a single downstream Ser/Thr kinase CTR1. Thesecomponents of the ethylene signalling network found in Arabidopsisare conserved in the climacteric fruit tomato, but both theethylene receptors and CTR1-like proteins (LeCTRs) in tomatoare encoded by multigene families. Here, using a yeast two-hybridinteraction assay, it is shown that the tomato receptors LeETR1,LeETR2, and NEVER-RIPE (NR) can interact with multiple LeCTRs.In vivo protein localization studies with fluorescent taggedproteins revealed that the ethylene receptor NR was targetedto the endoplasmic reticulum (ER) when transiently expressedin onion epidermal cells, whereas the four LeCTR proteins werefound in the cytoplasm and nucleus. When co-expressed with NR,three LeCTRs (1, 3, and 4), but not LeCTR2, also adopted thesame ER localization pattern in an NR receptor-dependent mannerbut not in the absence of NR. The receptor–CTR interactionswere confirmed by biomolecular fluorescence complementation(BiFC) showing that NR could form a protein complex with LeCTR1,3, and 4. This suggested that ethylene receptors recruit theseLeCTR proteins to the ER membrane through direct protein–proteininteraction. The receptor–CTR interactions and localizationobserved in the study reinforce the idea that ethylene receptorstransmit the signal to the downstream CTRs and show that a singlereceptor can interact with multiple CTR proteins. It remainsunclear whether the different LeCTRs are functionally redundantor have unique roles in ethylene signalling. Key words: BiFC, endoplasmic reticulum, Ser/Thr kinase, tomato ethylene signalling, two-component system His kinase     

Systems for the detection and analysis of protein–protein interactions

The analysis of protein–protein interactions is important for developing a better understanding of the functional annotations of proteins that are involved in various biochemical reactions in vivo. The discovery that a protein with an unknown function binds to a protein with a known function could provide a significant clue to the cellular pathway concerning the unknown protein. Therefore, information on protein–protein interactions obtained by the comprehensive analysis of all gene products is available for the construction of interactive networks consisting of individual protein–protein interactions, which, in turn, permit elaborate biological phenomena to be understood. Systems for detecting protein–protein interactions in vitro and in vivo have been developed, and have been modified to compensate for limitations. Using these novel approaches, comprehensive and reliable information on protein–protein interactions can be determined. Systems that permit this to be achieved are described in this review.K. Kuroda, M. Kato and J. Mima contributed equally to this work.     

Laccase-catalysed protein–flavonoid conjugates for flax fibre modification

The introduction of flavonoid compounds into proteins can improve the natural properties of proteins, being promising products which essentially require antioxidant property. The oxidative conjugation of protein–flavonoids was processed by laccase catalysis resulting in the synthesis of biologically functional polymers. The new reaction products were detected in terms of sodium dodecyl sulfate polyacrylamide gel electrophoresis and matrix-assisted laser desorption/ionisation-time of flight mass spectra, showing a greater molecular weight formation. Their characterisations were further carried out in terms of UV–Vis spectroscopy, photon correlation spectroscopy, differential scanning calorimetry and Fourier transform infrared (FT-IR) spectroscopy analysis. In addition, their application of protein–flavonoid conjugates onto flax fibres was exploited to supplement a suitable microorganism environment of protein-possessed fibres. The anchoring of conjugates onto cationised fibres was successfully performed by ionic interaction with negatively charged proteins. The level of anchoring efficiency was quantified in terms of measuring colour strength (k/s) and fluorescence microscopy analysis. The conjugates onto fibres presented acceptable durability in terms of washing resistance and the surface became hydrophilic when α-casein–catechin was applied (lower contact angle 48°). By the anchoring of protein–flavonoid conjugates onto flax fibres, the final products with new colour generation and antioxidant activity (>93%) were obtained.     

Combining NMR Relaxation with Chemical Shift Perturbation Data to Drive Protein–protein Docking

The modeling of biomolecular complexes by computational docking using the known structures of their constituents is developing rapidly to become a powerful tool in structural biology. It is especially useful in combination with even limited experimental information describing the interface. Here we demonstrate for the first time the use of diffusion anisotropy in combination with chemical shift perturbation data to drive protein–protein docking. For validation purposes we make use of simulated diffusion anisotropy data. Inclusion of this information, which can be derived from NMR relaxation rates and reports on the orientation of the components of a complex with respect to the rotational diffusion tensor, substantially improves the docking results.     

Prediction of Interacting Protein Pairs from Sequence Using a Bayesian Method

With the development of bioinformatics, more and more protein sequence information has become available. Meanwhile, the number of known protein–protein interactions (PPIs) is still very limited. In this article, we propose a new method for predicting interacting protein pairs using a Bayesian method based on a new feature representation. We trained our model using data on 6,459 PPI pairs from the yeast Saccharomyces cerevisiae core subset. Using six species of DIP database, our model demonstrates an average prediction accuracy of 93.67%. The result showed that our method is superior to other methods in both computing time and prediction accuracy.     

Mechanistic study of the structure–activity relationship for the free radical scavenging activity of baicalein

Density functional theory calculations were performed to evaluate the antioxidant activity of baicalein. The conformational behaviors of both the isolated and the aqueous-solvated species (simulated with the conductor-like polarizable continuum solvation model) were analyzed at the M052X/6-311 + G(d,p) level. The most stable tautomers of various forms of baicalein displayed three IHBs between O4 and OH5, O5 and OH6, and O6 and OH7. The most stable tautomer of the baicalein radical was obtained by dehydrogenating the hydroxyl at C6, while the most stable anion tautomer was obtained by deprotonating the C7 hydroxyl in gaseous and aqueous phases. The expected antioxidant activity of baicalein was explained by its ionization potentials (IPs) and homolytic O–H bond dissociation enthalpies (BDEs), which were obtained via the UM052X optimization level of the corresponding radical species. Heterolytic O–H bond cleavages (proton dissociation enthalpies, PDEs) were also computed. The calculated IP, BDE, and PDE values suggested that one-step H-atom transfer, rather than sequential proton loss–electron transfer or electron transfer–proton transfer, would be the most favorable mechanism for explaining the antioxidant activity of baicalein in the gas phase and in nonpolar solvents. In aqueous solution, the SPLET mechanism was more important.     

A Lagrangian particle method for reaction–diffusion systems on deforming surfaces

Reaction–diffusion processes on complex deforming surfaces are fundamental to a number of biological processes ranging from embryonic development to cancer tumor growth and angiogenesis. The simulation of these processes using continuum reaction–diffusion models requires computational methods capable of accurately tracking the geometric deformations and discretizing on them the governing equations. We employ a Lagrangian level-set formulation to capture the deformation of the geometry and use an embedding formulation and an adaptive particle method to discretize both the level-set equations and the corresponding reaction–diffusion. We validate the proposed method and discuss its advantages and drawbacks through simulations of reaction–diffusion equations on complex and deforming geometries.     

A novel two-layer, coupled finite element approach for modeling the nonlinear elastic and viscoelastic behavior of human erythrocytes

A novel finite element approach is presented to simulate the mechanical behavior of human red blood cells (RBC, erythrocytes). As the RBC membrane comprises a phospholipid bilayer with an intervening protein network, we propose to model the membrane with two distinct layers. The fairly complex characteristics of the very thin lipid bilayer are represented by special incompressible solid shell elements and an anisotropic viscoelastic constitutive model. Properties of the protein network are modeled with an isotropic hyperelastic third-order material. The elastic behavior of the model is validated with existing optical tweezers studies with quasi-static deformations. Employing material parameters consistent with literature, simulation results are in excellent agreement with experimental data. Available models in literature neglect either the surface area conservation of the RBC membrane or realistic loading conditions of the optical tweezers experiments. The importance of these modeling assumptions, that are both included in this study, are discussed and their influence quantified. For the simulation of the dynamic motion of RBC, the model is extended to incorporate the cytoplasm. This is realized with a monolithic fully coupled fluid-structure interaction simulation, where the fluid is described by the incompressible Navier–Stokes equations in an arbitrary Lagrangian Eulerian framework. It is shown that both membrane viscosity and cytoplasm viscosity have significant influence on simulation results. Characteristic recovery times and energy dissipation for varying strain rates in dynamic laser trap experiments are calculated for the first time and are found to be comparable with experimental data.     

Protein-protein interaction site mapping using NMR-detected mutational scanning

We demonstrate a novel NMR method for the mapping of protein–protein interaction sites. In our approach protein–protein binding sites are mapped by competition binding experiments using indirect NMR reporter technology and Ala positional scanning. The methodology provides high sensitivity, ease of implementation and high-throughput capabilities. The feasibility of the technique is demonstrated with an application to the β-Catenin/Tcf4 complex.     

Modeling of peptides and proteins in a membrane environment: I. A solvation model mimicking a lipid bilayer

A theoretical solvation model of peptides and proteins that mimics the heterogeneous membrane-water system was proposed. Our approach is based on the combined use of atomic parameters of solvation for water and hydrocarbons, which approximates the hydrated polar groups and acyl chains of lipids, respectively. This model was tested in simulations of several peptides: a nonpolar 20-mer polyleucine, a hydrophobic peptide with terminal polar groups, and a strongly amphiphilic peptide. The conformational space of the peptides in the presence of the membrane was studied by the Monte Carlo method. Unlike a polar solvent and vacuum, the membrane-like environment was shown to stabilize the α-helical conformation: low-energy structures have a helicity index of 100% in all cases. At the same time, the energetically most favorable orientations of the peptides relative to the membrane depend on their hydrophobic properties: nonpolar polyleucine is entirely immersed in the bilayer and the hydrophobic peptide with polar groups at the termini adopts a transbilayer orientation, whereas the amphiphilic peptide lies at the interface parallel to the membrane plane. The results of the simulations agree well with the available experimental data for these systems. In the following communications of this series, we plan to describe applications of the solvation model to membrane-bound proteins and peptides with biologically important functional activities.     

Product yields from irradiated glycylglycine in oxygen-free solutions: Monte Carlo simulations and comparison with experiments

The radiation chemistry of photon-irradiated aqueous solutions of biological molecules may be considered under four distinct time regimes: physical transport (≤10^–15 s); prechemical conversion of H₂O⁺, H₂O^*, and subexcitation electrons into free radicals and molecular products (10^–15 s to 10^–12 s); chemical reactions within individual electron tracks (10^–12 s to 10^–6 s); and chemical reactions within overlapping tracks (>10^–6 s). We have previously reported of the use of the Monte Carlo radiation transport/chemistry codes OREC and RADLYS to model the radiolysis of glycylglycine in oxygen-free solution to a time of 1 μs. These simulations successfully predicted the yields of free ammonia, an end product created solely in the reaction of the hydrated electron with the solute within individual tracks. Other measurable products are only partially created during intratrack reactions, and thus one must additionally consider the late, intertrack chemistry of this system. In this paper, we extend our simulations of glycylglycine radiolysis to model for the first time the events which occur during this late chemistry stage. The model considers the product rates of the reactants in bulk solution by using previously available microsecond intratrack yields given by single-track OREC/RADLYS simulations and an x-ray dose rate of 2.80 Gy min^–1 as used in a companion experimental program. These rates are then applied in a series of coupled, differential rate equations that describe the solution chemistry of glycylglycine radiolysis. Product yields are reported as a function of time over a total irradiation period of 10⁴ s. Excellent overall agreement is seen between the theoretical predictions and measurements of five radiolysis end products: free ammonia, acetylglycine, diaminosuccinic acid, aspartic acid, and succinic acid. The model also gives the explicit contributions of intratrack and intertrack reactions to the various end products. For example, the model predicts that ∼56% and 93% of succinic acid and aspartic acid, respectively, are produced during intertrack reactions at a solute concentration of 0.05 M; these contributions drop to 0.07% and 11%, respectively, at 1.2 M. Received: 22 May 1998 / Accepted in revised form: 27 August 1998