Spectral and Luminescence Properties of Linseed Oils of Different Prehistory.

The spectral and luminescence properties of linseed oils with different background have been studied. High informativity of oil fluorophores (phenols, tocopherols, polyunsaturated fatty acids, vitamins, pigments) as to their native state depending on the influence of various destructive factors: extended storage period of oil (three years), exposure to sunlight for 50 h and contact with temperatures in the range of 60 ºC > t > 46 ºC was registered.It was revealed that: 1. Exposure of linseed oil to sunlight for 50 h and contact with temperatures 60 ºC > t > 46 ºC during the process of oil extraction don't lead to visible changes in the structures of their luminescence spectra and luminescence excitation spectra. 2. Long storage period of oil (> 3 years) leads to: (a) decomposition of phenols, tocopherols, polyunsaturated fatty acids (linoleic, linolenic, arachidonic), vitamins (B2, E, carotene), accompanied by the appearance of emission bands with maxima λmax = 350, 370, 390, 425, 440, 470, 520 nm, which are attributed to the products of their oxidation, increase of their luminescence intensity and changes in the structure of the luminescence excitation spectra of fluorophores: phenols, tocopherols, polyunsaturated fatty acids (linoleic, linolenic, arachidonic) and vitamins (B2, E, carotene); (b) decrease in the intensity of the luminescence bands of phenol, tocopherol, carotene and chlorophyll pigment.

Bayesian refinement of protein structures and ensembles against SAXS data using molecular dynamics.

Small-angle X-ray scattering is an increasingly popular technique used to detect protein structures and ensembles in solution. However, the refinement of structures and ensembles against SAXS data is often ambiguous due to the low information content of SAXS data, unknown systematic errors, and unknown scattering contributions from the solvent. We offer a solution to such problems by combining Bayesian inference with all-atom molecular dynamics simulations and explicit-solvent SAXS calculations. The Bayesian formulation correctly weights the SAXS data versus prior physical knowledge, it quantifies the precision or ambiguity of fitted structures and ensembles, and it accounts for unknown systematic errors due to poor buffer matching. The method further provides a probabilistic criterion for identifying the number of states required to explain the SAXS data. The method is validated by refining ensembles of a periplasmic binding protein against calculated SAXS curves. Subsequently, we derive the solution ensembles of the eukaryotic chaperone heat shock protein 90 (Hsp90) against experimental SAXS data. We find that the SAXS data of the apo state of Hsp90 is compatible with a single wide-open conformation, whereas the SAXS data of Hsp90 bound to ATP or to an ATP-analogue strongly suggest heterogenous ensembles of a closed and a wide-open state.

Quantifying the influence of the ion cloud on SAXS profiles of charged proteins.

Small-angle X-ray scattering (SAXS) is a popular experimental technique used to obtain structural information on biomolecules in solution. SAXS is sensitive to the overall electron density contrast between the biomolecule and the buffer, including contrast contributions from the hydration layer and the ion cloud. This property may be used advantageously to probe the properties of the ion cloud around charged biomolecules. However, in turn, contributions from the hydration layer and ion cloud may complicate the interpretation of the data, because these contributions must be modelled during structure validation and refinement. In this work, we quantified the influence of the ion cloud on SAXS curves of two charged proteins, bovine serum albumin (BSA) and glucose isomerase (GI), solvated in five different alkali chloride buffers of 100 mM or 500 mM concentrations. We compared three computational methods of varying physical detail, for deriving the ion cloud effect on the radius of gyration Rg of the proteins, namely (i) atomistic molecular dynamics simulations in conjunction with explicit-solvent SAXS calculations, (ii) non-linear Poisson-Boltzmann calculations, and (iii) a simple spherical model in conjunction with linearized Poisson-Boltzmann theory. The calculations for BSA are validated against experimental data. We find favorable agreement among the three computational methods and the experiment, suggesting that the influence of the ion cloud on Rg, as detected by SAXS, may be predicted with nearly analytic calculations. Our analysis further suggests that the ion cloud effect on Rg is dominated by the long-range distribution of the ions around the proteins, as described by Debye-Hückel theory, whereas the local salt structure near the protein surface plays a minor role.

Markov State Model of Ion Assembling Process.

We study the process of ion assembling in aqueous solution by means of molecular dynamics. In this article, we present a method to study many-particle assembly using the Markov state model formalism. We observed that at NaCl concentration higher than 1.49 mol/kg, the system tends to form a big ionic cluster composed of roughly 70-90% of the total number of ions. Using Markov state models, we estimated the average time needed for the system to make a transition from discorded state to a state with big ionic cluster. Our results suggest that the characteristic time to form an ionic cluster is a negative exponential function of the salt concentration. Moreover, we defined and analyzed three different kinetic states of a single ion particle. These states correspond to a different particle location during nucleation process.

Network analysis of proton transfer in liquid water.

Proton transfer in macromolecular systems is a fascinating yet elusive process. In the last ten years, molecular simulations have shown to be a useful tool to unveil the atomistic mechanism. Notwithstanding, the large number of degrees of freedom involved make the accurate description of the process very hard even for the case of proton diffusion in bulk water. Here, multi-state empirical valence bond molecular dynamics simulations in conjunction with complex network analysis are applied to study proton transfer in liquid water. Making use of a transition network formalism, this approach takes into account the time evolution of several coordinates simultaneously. Our results provide evidence for a strong dependence of proton transfer on the length of the hydrogen bond solvating the Zundel complex, with proton transfer enhancement as shorter bonds are formed at the acceptor site. We identify six major states (nodes) on the network leading from the "special pair" to a more symmetric Zundel complex required for transferring the proton. Moreover, the second solvation shell specifically rearranges to promote the transfer, reiterating the idea that solvation beyond the first shell of the Zundel complex plays a crucial role in the process.

The quest for self-consistency in hydrogen bond definitions.

In the last decades several hydrogen-bond definitions were proposed by classical computer simulations. Aiming at validating their self-consistency on a wide range of conditions, here we present a comparative study of six among the most common hydrogen-bond definitions for temperatures ranging from 220 K to 400 K and six classical water models. Our results show that, in the interval of temperatures investigated, a generally weak agreement among definitions is present. Moreover, cutoff choice for geometrically based definitions depends on both temperature and water model. As such, analysis of the same water model at different temperatures as well as different water models at the same temperature would require the development of specific cutoff values. Interestingly, large discrepancies were found between two hydrogen-bond definitions which were recently introduced to improve on more conventional methods. Our results reinforce the idea that a more universal way to characterize hydrogen bonds in classical molecular systems is needed.

Towards a microscopic description of the free-energy landscape of water.

Free-energy landscape theory is often used to describe complex molecular systems. Here, a microscopic description of water structure and dynamics based on configuration-space-networks and molecular dynamics simulations of the TIP4P/2005 model is applied to investigate the free-energy landscape of water. The latter is built on top of a large set of water microstates describing the kinetic stability of local hydrogen-bond arrangements up to the second solvation shell. In temperature space, the landscape displays three different regimes. At around ambient conditions, the free-energy surface is characterized by many short-lived basins of attraction which are structurally well-defined (inhomogeneous regime). At lower temperatures instead, the liquid rapidly becomes homogeneous. In this regime, the free energy is funneled-like, with fully coordinated water arrangements at the bottom of the funnel. Finally, a third regime develops below the temperature of maximal compressibility (Widom line) where the funnel becomes steeper with few interconversions between microstates other than the fully coordinated ones. Our results present a way to manage the complexity of water structure and dynamics, connecting microscopic properties to its ensemble behavior.

Combined Small-Angle X-ray and Neutron Scattering Restraints in Molecular Dynamics Simulations.

Small-angle X-ray and small-angle neutron scattering (SAXS/SANS) provide unique structural information on biomolecules and their complexes in solution. SANS may provide multiple independent data sets by means of contrast variation experiments, that is, by measuring at different D2O concentrations and different perdeuteration conditions of the biomolecular complex. However, even the combined data from multiple SAXS/SANS sets is by far insufficient to define all degrees of freedom of a complex, leading to a significant risk of overfitting when refining biomolecular structures against SAXS/SANS data. Hence, to control against overfitting, the low-information SAXS/SANS data must be complemented by accurate physical models, and, if possible, refined models should be cross-validated against independent data not used during the refinement. We present a method for refining atomic biomolecular structures against multiple sets of SAXS and SANS data using all-atom molecular dynamics simulations. Using the protein citrate synthase and the protein/RNA complex Sxl-Unr-msl2 mRNA as test cases, we demonstrate how multiple SAXS and SANS sets may be used for refinement and cross-validation, thereby excluding overfitting during refinement. For the Sxl-Unr-msl2 complex, we find that perdeuteration of the Unr domain leads to a unique, slightly compacted conformation, whereas other perdeuteration conditions lead to similar solution conformations compared to the nondeuterated state. In line with our previous method for predicting SAXS curves, SANS curves were predicted with explicit-solvent calculations, taking atomic models for both the hydration layer and the excluded solvent into account, thereby avoiding the use of solvent-related fitting parameters and solvent-reduced neutron scattering lengths. We expect the method to be useful for deriving and validating solution structures of biomolecules and soft-matter complexes, and for critically assessing whether multiple SAXS and SANS sets are mutually compatible.

Water structure-forming capabilities are temperature shifted for different models.

A large number of water models exist for molecular simulations. They differ in the ability to reproduce specific features of real water instead of others, like the correct temperature for the density maximum or the diffusion coefficient. Past analysis mostly concentrated on ensemble quantities, while few data were reported on the different microscopic behavior. Here, we compare seven widely used classical water models (SPC, SPC/E, TIP3P, TIP4P, TIP4P-Ew, TIP4P/2005, and TIP5P) in terms of their local structure-forming capabilities through hydrogen bonds for temperatures ranging from 210 to 350 K by the introduction of a set of order parameters taking into account the configuration of up to the second solvation shell. We found that all models share the same structural pattern up to a temperature shift. When this shift is applied, all models overlap onto a master curve. Interestingly, increased stabilization of fully coordinated structures extending to at least two solvation shells is found for models that are able to reproduce the correct position of the density maximum. Our results provide a self-consistent atomic-level structural comparison protocol, which can be of help in elucidating the influence of different water models on protein structure and dynamics.