Liquids exist in a relatively small part of the enormous range of temperatures and pressures existing in the universe. Nevertheless, they are of vital importance for physics and chemistry, for technology, and for life itself. A century of effort since the pioneering work of van der Waals has led to a fairly complete basic understanding of the static and dynamic physicochemical properties of liquids. Advances in statistical mechanics (the fundamental formulations of Gibbs and Boltzmann, integral equations and perturbation theories, computer simulations), in knowledge of intermolecular forces, and in experimental techniques; have all contributed to this. Thirty years ago the very existence of liquids seemed a little mysterious; today one can make fairly precise predictions of the solid-liquid-gas phase diagram and of the microscopic and macroscopic static and dynamic properties of liquids. This paper is a survey, with particular emphasis on equilibrium properties, of the theory which underlies that basic understanding, which is now at least comparable with our understanding of the physics of solids.

What is "liquid"? Understanding the states of matter

This article, on protein-based polymers comprised of repeating peptide sequences, reviews studies from the author's laboratory covering a period of more than two decades; it presents a general mechanism for protein folding and function and demonstrates the mechanism by designing model proteins capable of performing many of the energy conversions that sustain life and by designing diverse biomolecular machines and materials with promising applications for society. All polymers with the correct balance of apolar and polar moieties, including water soluble proteins and protein-based polymers, increase order by a hydrophobic folding and assembly transition as the temperature is raised above a critical onset temperature, designated as Tt. Instead of varying the temperature, however, innumerable variables lower the value of Tt from above to below the operating temperature to drive folding and function. Thus, this inverse temperature transition provides a fundamental mechanism whereby proteins fold and function ...

Physical Chemistry of Biological Free Energy Transduction As Demonstrated by Elastic Protein-Based Polymers†

Fluorescence imaging is the most powerful technique currently available for continuous observation of dynamic intracellular processes in living cells. Suitable fluorescence probes are naturally of critical importance for fluorescence imaging, but only a very limited range of biomolecules can currently be visualized because of the lack of flexible design strategies for fluorescence probes. At present, design is largely empirical. Here we show that the carboxylic group of traditional fluorescein dyes, formerly considered indispensable, has been replaced with other substituents, affording various kinds of new fluoresceins. Further, by breaking out of the traditional structure of fluorescein, we developed the first and totally rational design strategy for novel fluorescence probes based on a strict photochemical basis. The value of this approach is exemplified by its application to develop a novel, highly sensitive, and membrane-permeable fluorescence probe for β-galactosidase, which is the most widely used r...

Evolution of Fluorescein as a Platform for Finely Tunable Fluorescence Probes

Implicit methods for modeling protein electrostatics require dielectric properties of the system to be known, in particular, the value of the dielectric constant of protein. While numerous values of the internal protein dielectric constant were reported in the literature, still there is no consensus of what the optimal value is. Perhaps this is due to the fact that the protein dielectric constant is not a "constant" but is a complex function reflecting the properties of the protein's structure and sequence. Here, we report an implementation of a Gaussian-based approach to deliver the dielectric constant distribution throughout the protein and surrounding water phase by utilizing the 3D structure of the corresponding macromolecule. In contrast to previous reports, we construct a smooth dielectric function throughout the space of the system to be modeled rather than just constructing a "Gaussian surface" or smoothing molecule-water boundary. Analysis on a large set of proteins shows that (a) the average dielectric constant inside the protein is relatively low, about 6-7, and reaches a value of about 20-30 at the protein's surface, and (b) high average local dielectric constant values are associated with charged residues while low dielectric constant values are automatically assigned to the regions occupied by hydrophobic residues. In terms of energetics, a benchmarking test was carried out against the experimental pKa's of 89 residues in staphylococcal nuclease (SNase) and showed that it results in a much better RMSD (= 1.77 pK) than the corresponding calculations done with a homogeneous high dielectric constant with an optimal value of 10 (RMSD = 2.43 pK).

On the Dielectric "Constant" of Proteins: Smooth Dielectric Function for Macromolecular Modeling and Its Implementation in DelPhi.

A potential function for ArKr is derived which is able to reproduce the best data available for the differential and the integral cross section, the second virial coefficient and the diffusion and viscosity within the quoted experimental errors.

An accurate intermolecular potential for argon

m–6–8 Potential Function

APPLICATION OF THE m-6-8 POTENTIAL TO SIMPLE GASES.

The pK(a)s of 96 acids and bases introduced into buried sites in the staphylococcal nuclease protein (SNase) were calculated using the multiconformation continuum electrostatics (MCCE) program and the results compared with experimental values. The pK(a)s are obtained by Monte Carlo sampling of coupled side chain protonation and position as a function of pH. The dependence of the results on the protein dielectric constant (e(prot)) in the continuum electrostatics analysis and on the Lennard-Jones non-electrostatics parameters was evaluated. The pK(a)s of the introduced residues have a clear dependence on e(prot,) whereas native ionizable residues do not. The native residues have electrostatic interactions with other residues in the protein favoring ionization, which are larger than the desolvation penalty favoring the neutral state. Increasing e(prot) scales both terms, which for these residues leads to small changes in pK(a). The introduced residues have a larger desolvation penalty and negligible interactions with residues in the protein. For these residues, changing e(prot) has a large influence on the calculated pK(a). An e(prot) of 8-10 and a Lennard-Jones scaling of 0.25 is best here. The X-ray crystal structures of the mutated proteins are found to provide somewhat better results than calculations carried out on mutations made in silico. Initial relaxation of the in silico mutations by Gromacs and extensive side chain rotamer sampling within MCCE can significantly improve the match with experiment.

MCCE analysis of the pKas of introduced buried acids and bases in staphylococcal nuclease

The nonlinear integral equation of the hypernetted chain (HNC) approximation is solved for a fluid of hard spheres. An inconsistency introduced by the approximation results in a disagreement between two forms of the equation of state. The resulting pair of equations of state are compared with each other, with those obtained for the Born—Green and (approximate) Kirkwood equations by Kirkwood, Maun, and Alder, and with a reference isotherm made up of a combination of the five‐term virial series at low and intermediate densities and the gas‐like isotherm of molecular dynamics at high densities. The HNC equations of state are found to be a considerable improvement over those of the Born—Green and Kirkwood theories. At intermediate and high densities, the two HNC isotherms bracket the reference isotherm, their mean being a very good approximation to it. The HNC equation exhibits a tendency toward a gas—solid phase transition at extremely high densities. A transition is not actually predicted, however.

Numerical Solutions of the Convolution‐Hypernetted Chain Integral Equation for the Pair Correlation Function of a Fluid. I. The Lennard‐Jones (12, 6) Potential

Summary: Data-parallel programming techniques can dramatically decrease the time needed to analyze large datasets. While these methods have provided significant improvements for sequencing-based analyses, other areas of biological informatics have not yet adopted them. Here, we introduce Biospark, a new framework for performing data-parallel analysis on large numerical datasets. Biospark builds upon the open source Hadoop and Spark projects, bringing domain-specific features for biology. Availability and Implementation: Source code is licensed under the Apache 2.0 open source license and is available at the project website: https://www.assembla.com/spaces/roberts-lab-public/wiki/Biospark Contact: eroberts@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Biospark: scalable analysis of large numerical datasets from biological simulations and experiments using Hadoop and Spark.

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