Lateral organization of mixed, two-phosphatidylcholine liposomes as investigated by GPS, the slope of Laurdan generalized polarization spectra

The effect of the excitation or emission wavelengths on Laurdan generalized polarization (GP) can be evaluated by GPS, a quantitative, simplified determination of the GP spectrum slope, the thermotropic dependence of which allows the assessment of phospholipid lamellar membrane phase, as shown in a recent publication of our laboratory [J.B. Velázquez, M.S. Fernández, Arch. Biochem. Biophys. 455 (2006) 163-174]. In the present work, we applied Laurdan GPS to phase transition studies of mixed, two-phosphatidylcholine liposomes prepared from variable proportions of dimyristoyl- and dipalmitoylphosphatidylcholine (DMPC and DPPC, respectively). We have found that the GPS function reports a clear limit between the gel/liquid-crystalline phase coexistence region and the liquid-crystalline state, not only at a certain temperature T_c for liposomes of constant composition submitted to temperature scans, but also at a defined mole fraction X_c, for two-component liposomes of variable composition at constant temperature. The T_c or the X_c values obtained from GPS vs. temperature or GPS vs. composition plots, respectively, allow the construction of a partial phase diagram for the DMPC-DPPC mixtures, showing the boundary between the two-phase coexisting region and the liquid-crystalline state. Likewise, at the onset of the transition region, i.e., the two-phase coexisting region as detected by GPS, it is possible to determine, although with less precision, a temperature T_o or a mole fraction X_o defining a boundary located below but near the limit between the gel and ripple phase, reported in the literature. These GPS results are consistent with the proposal by several authors that a fraction of L_α phospholipids coexists with gel phospholipids in the rippled phase.     

Design of HIV-1-PR inhibitors that do not create resistance: blocking the folding of single monomers

The main problems found in designing drugs are those of optimizing the drug-target interaction and of avoiding the insurgence of resistance. We suggest a scheme for the design of inhibitors that can be used as leads for the development of a drug and that do not face either of these problems, and then apply it to the case of HIV-1-PR. It is based on the knowledge that the folding of single-domain proteins, such as each of the monomers forming the HIV-1-PR homodimer, is controlled by local elementary structures (LES), stabilized by local contacts among hydrophobic, strongly interacting, and highly conserved amino acids that play a central role in the folding process. Because LES have evolved over many generations to recognize and strongly interact with each other so as to make the protein fold fast and avoid aggregation with other proteins, highly specific (and thus little toxic) as well as effective folding-inhibitor molecules suggest themselves: short peptides (or eventually their mimetic molecules) displaying the same amino acid sequence of that of LES (p-LES). Aside from being specific and efficient, these inhibitors are expected not to induce resistance; in fact, mutations in HIV-1-PR that successfully avoid the action of p-LES imply the destabilization of one or more LES and thus should lead to protein denaturation. Making use of Monte Carlo simulations, we first identify the LES of the HIV-1-PR and then show that the corresponding p-LES peptides act as effective inhibitors of the folding of the protease.     

Stochastic simulation of actin dynamics reveals the role of annealing and fragmentation

Recent observations of F-actin dynamics call for theoretical models to interpret and understand the quantitative data. A number of existing models rely on simplifications and do not take into account F-actin fragmentation and annealing. We use Gillespie's algorithm for stochastic simulations of the F-actin dynamics including fragmentation and annealing. The simulations vividly illustrate that fragmentation and annealing have little influence on the shape of the polymerization curve and on nucleotide profiles within filaments but drastically affect the F-actin length distribution, making it exponential. We find that recent surprising measurements of high length diffusivity at the critical concentration cannot be explained by fragmentation and annealing events unless both fragmentation rates and frequency of undetected fragmentation and annealing events are greater than previously thought. The simulations compare well with experimentally measured actin polymerization data and lend additional support to a number of existing theoretical models.     

Singular value decomposition of 3-D DNA melting curves reveals complexity in the melting process

The thermal denaturation of synthetic deoxypolynucleotides of defined sequence was studied by a three dimensional melting technique in which complete UV absorbance spectra were recorded as a function of temperature. The results of such an experiment defined a surface bounded by absorbance, wavelength, and temperature. A matrix of the experimental data was built, and analyzed by the method of singular value decomposition (SVD). SVD provides a rigorous, model-free analytical tool for evaluating the number of significant spectral species required to account for the changes in UV absorbance accompany-ing the duplex – to – single strand transition. For all of the polynucleotides studied (Poly dA – Poly dT; [Poly (dAdT)]₂; Poly dG – Poly dC; [Poly(dGdC)]₂), SVD indicated the existence of at least 4 – 5 significant spectral species. The DNA melting transition for even these simple repeating sequences cannot, therefore, be a simple two-state process. The basis spectra obtained by SVD analysis were found to be unique for each polynucleotide studied. Differential scanning calorimetry was used to obtain model free estimates for the enthalpy of melting for the polynucleotides studied, with results in good agreement with previously published values. Received: 16 April 1997 / Accepted: 9 July 1997     

A Monte Carlo Study of the Argon Fluid Around a Benzene Molecule

Abstract

Monte Carlo simulations have been carried out for argon fluid containing one benzene molecule at the supercritical region. The purpose in this study is to examine the effect of plate-like molecule on the structure of neighboring fluid composed of simple spherical molecules of the system. In the first neighbor shell of argon from the center of benzene molecule, the average potential energy of argon atoms is confirmed to have a large density dependence. This potential energy is relatively large in the high density region. It is found that the spatial distribution of argon fluid is significantly affected by the molecular shape of benzene and it has little direct connection with the attractive interaction between benzene and argon.     

Grid computing and molecular simulations: the vision of the eMinerals project

This paper discusses a number of aspects of using grid computing methods in support of molecular simulations, with examples drawn from the eMinerals project. A number of components for a useful grid infrastructure are discussed, including the integration of compute and data grids, automatic metadata capture from simulation studies, interoperability of data between simulation codes, management of data and data accessibility, management of jobs and workflow, and tools to support collaboration. Use of a grid infrastructure also brings certain challenges, which are discussed. These include making use of boundless computing resources, the necessary changes, and the need to be able to manage experimentation.     

Potential optimization for the calculation of shocked liquid nitromethane properties

We present the results of the optimization of a classical molecular force field used to calculate the properties of shocked nitromethane by Monte Carlo simulations. The optimization technique allows a good transferability of the potential parameters on a broad range of thermodynamic conditions (temperature and pressure) since a large variety of reference data can be used in the optimization procedure, including densities, vaporization enthalpies or pressures along the Hugoniot curve. Results of calculated properties of shocked nitromethane are in good agreement with experimental shock Hugoniot data, including temperature measurements of second shock Hugoniot.     

Framework for the inter-comparison of ecological footprint of universities

The ecological footprint (EF) method represents the suitability of a given population on the carrying capacity of the total system. It was developed in order to measure the relationship between nature and humans, being supported on the premise that each individual requires a surface area that provides goods and services essential to life. In this article only in EF for universities is studied, but most of the underlying concepts and methods are valid for any other human activity for which EF may be applied.In this study an uncertainty analysis of EF of universities is made. This is, to the authors’ knowledge, the first time such a study is published on the subject. The intention is to demonstrate the usefulness of uncertainty analysis in the evaluation of results, inter-comparability, and on communication of EF outcomes.Results showed that EF model uncertainties have large impact on EF estimates, in particular in what regards the decision about accounting or not the contribution of key parameters. Inclusion or not of very sensitive parameters, for which there is also high uncertainty, in the estimation of EF may have a strong impact on the estimated values and also in the inter-comparability of EF estimates. This is the case of mobility.Uncertainty analysis, by studying model uncertainty, parameter uncertainty and variability, can provide a robust framework for the inter-comparison of ecological footprints of universities. In fact, the method may prove useful for the assessment of ecological footprints of any kind.     

Monte Carlo simulation of protein folding in the presence of residue-specific binding sites

Ensemble growth Monte Carlo (EGMC) and dynamic Monte Carlo (DMC) simulations are used to study sequential folding and thermodynamic stability of hydrophobic-polar (HP) chains that fold to a compact structure. Molecularly imprinted cavities are modeled as hard walls having sites that are attractive to specific polar residues on the chain. Using EGMC simulation, we find that the folded conformation can be stabilized using a small number of carefully selected residue-specific sites while a random selection of surface-bound residues may only slightly contribute toward stabilizing the folded conformation, and in some cases may hinder the folding of the chain. DMC simulations of the surface-bound chain confirm increased stability of the folded conformation over a free chain. However, a different trend of the equilibrium population of folded chains as a function of residue-external site interactions is predicted with the two simulation methods.     

The role of molecular modelling and simulation in the discovery and deployment of metal-organic frameworks for gas storage and separation*

ABSTRACT

Metal-organic frameworks (MOFs) are highly tuneable, extended-network, crystalline, nanoporous materials with applications in gas storage, separations, and sensing. We review how molecular models and simulations of gas adsorption in MOFs have informed the discovery of performant MOFs for methane, hydrogen, and oxygen storage, xenon, carbon dioxide, and chemical warfare agent capture, and xylene enrichment. Particularly, we highlight how large, open databases of MOF crystal structures, post-processed to enable molecular simulations, are a platform for computational materials discovery. We discuss how to orient research efforts to routinise the computational discovery of MOFs for adsorption-based engineering applications.     

The crystal structure of the phosphatidylinositol 4‐kinase IIα

Phosphoinositides are a class of phospholipids generated by the action of phosphoinositide kinases with key regulatory functions in eukaryotic cells. Here, we present the atomic structure of phosphatidylinositol 4‐kinase type IIα (PI4K IIα), in complex with ATP solved by X‐ray crystallography at 2.8 Å resolution. The structure revealed a non‐typical kinase fold that could be divided into N‐ and C‐lobes with the ATP binding groove located in between. Surprisingly, a second ATP was found in a lateral hydrophobic pocket of the C‐lobe. Molecular simulations and mutagenesis analysis revealed the membrane binding mode and the putative function of the hydrophobic pocket. Taken together, our results suggest a mechanism of PI4K IIα recruitment, regulation, and function at the membrane.     

A comparative evaluation of modelling strategies for the effect of treatment and host interactions on the spread of drug resistance

The evolutionary responses of infectious pathogens often have ruinous consequences for the control of disease spread in the population. Drug resistance is a well-documented instance that is generally driven by the selective pressure of drugs on both the replication of the pathogen within hosts and its transmission between hosts. Management of drug resistance therefore requires the development of treatment strategies that can impede the emergence and spread of resistance in the population. This study evaluates various treatment strategies for influenza infection as a case study by comparing the long-term epidemiological outcomes predicted by deterministic and stochastic versions of a homogeneously mixing (mean-field) model and those predicted by a heterogeneous model that incorporates spatial pair-wise correlation. We discuss the importance of three major parameters in our evaluation: the basic reproduction number, the population level of treatment, and the degree of clustering as a key parameter determining the structure of heterogeneous interactions. The results show that, as a common feature in all models, high treatment levels during the early stages of disease outset can result in large resistant outbreaks, with the possibility of a second wave of infection appearing in the pair-approximation model. Our simulations demonstrate that, if the basic reproduction number exceeds a threshold value, the population-wide spread of the resistant pathogen emerges more rapidly in the pair-approximation model with significantly lower treatment levels than in the homogeneous models. We tested an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. The findings indicate that the overall disease incidence is reduced as the degree of clustering increases, and a longer delay should be considered for implementing the large-scale treatment.     

Design of a folding inhibitor of the HIV-1 protease

A novel way to inhibit HIV-1 protease by destabilizing its native state is discussed. A simplified protein model is used together with Monte Carlo simulations, to assess the destabilizing effect of peptides displaying the same sequence as specific fragments of the protein which are essential for its stability. Model calculations also show that it is unlikely that the protein can escape the inhibitory peptide by point mutations.     

Determination of the conformation of folding initiation sites in proteins by computer simulation

Experimental evidence and theoretical models both suggest that protein folding begins by specific short regions of the polypeptide chain intermittently assuming conformations close to their final ones. The independent folding properties and small size of these folding initiation sites make them suitable subjects for computational methods aimed at deriving structure from sequence. We have used a torsion space Monte Carlo procedure together with an all-atom free energy function to investigate the folding of a set of such sites. The free energy function is derived by a potential of mean force analysis of experimental protein structures. The most important contributions to the total free energy are the local main chain electrostatics, main chain hydrogen bonds, and the burial of nonpolar area. Six proposed independent folding units and four control peptides 11–14 residues long have been investigated. Thirty Monte Carlo simulations were performed on each peptide, starting from different random conformations. Five of the six folding units adopted conformations close to the experimental ones in some of the runs. None of the controls did so, as expected. The generated conformations which are close to the experimental ones have among the lowest free energies encountered, although some less native like low free energy conformations were also found. The effectiveness of the method on these peptides, which have a wide variety of experimental conformations, is encouraging in two ways: First, it provides independent evidence that these regions of the sequences are able to adopt native like conformations early in folding, and therefore are most probably key components of the folding pathways. Second, it demonstrates that available simulation methods and free energy functions are able to produce reasonably accurate structures. Extensions of the methods to the folding of larger portions of proteins are suggested. © 1995 Wiley-Liss, Inc.     

A Monte Carlo Simulation Study of Orientational Domain Clusters in the Planar Quadrupole Model

Abstract

We have carried out a series of Monte Carlo simulations of the planar quadrupole model, using the Distributed Array Processor. A very large system size, 16 384 molecules, was employed, and special attention was given to orientational domain clustering near the order—disorder transition. Very slow fluctuations of the orientational order parameter, possibly associated with switching from one orientational domain to another, are observed. Close to the phase transition, domain clusters become extremely ramified, with highly irregular borders. On heating through the transition, the low-temperature dominant domain disappears, essentially by becoming a fractal object. The associated Hausdorff dimension decreases from D = 2 to D = 1.6 as this occurs. Although our results are consistent with a continuous, rather than a first-order, phase transition, effects of finite system size and long time scales prevent us from drawing a definite conclusion on this point.     

A Monte Carlo method for the simulation of kinetie models

The purpose of this note is to illustrate the feasibility of simulating kinetic systems, such as commonly encountered in photosynthesis research, using the Monte Carlo (MC) method. In this approach, chemical events are considered at the molecular level where they occur randomly and the macroscopic kinetic evolution results from averaging a large number of such events. Their repeated simulation is easily accomplished using digital computing. It is shown that the MC approach is well suited to the capabilities and resources of modern microcomputers. A software package is briefly described and discussed, allowing a simple programming of any kinetic model system and its resolution. The execution is reasonably fast and accurate; it is not subject to such instabilities as found with the conventional analytical approach.Abbreviations MC Monte Carlo - RN random number - PSU photosynthetic unit Dedicated to Prof. L.N.M. Duysens on the occasion of his retirement.     

Dependence of folding dynamics and structural stability on the location of a hydrophobic pair in beta-hairpins

We study the dependence of folding time, nucleation site, and stability of a model beta-hairpin on the location of a cross-strand hydrophobic pair, using a coarse-grained off-lattice model with the aid of Monte Carlo simulations. Our simulations have produced 6500 independent folding trajectories dynamically, forming the basis for extensive statistical analysis. Four folding pathways, zipping-out, middle-out, zipping-in, and reptation, have been closely monitored and discussed in all seven sequences studied. A hydrophobic pair placed near the beta-turn or in the middle section effectively speed up folding; a hydrophobic pair placed close to the terminal ends or next to the beta-turn encourages stability of the entire chain.