Thermal and concentration effects on 1H NMR relaxation of Gd3+-aqua using MD simulations and measurements.

Gadolinium-based contrast agents are key in clinical MRI for enhancing the longitudinal NMR relativity (r1) of hydrogen nuclei (1H) in water and improving the contrast among different tissues. The importance of MRI in clinical practice cannot be gainsaid, yet the interpretation of MRI relies on models with severe assumptions, reflecting a poor understanding of the molecular-scale relaxation processes. In a step towards building a clearer understanding of the relaxation processes, here we investigate thermal and concentration effects on r1 of the Gd3+-aqua complex using both semi-classical molecular dynamics (MD) simulations and measurements. We follow the MD simulation approach recently introduced by [Singer et al., Phys. Chem. Chem. Phys., 2021, 23, 20974], in which no NMR relaxation model or free-parameter is assumed to predict r1, thereby bringing new insights into the physics of r1 on a molecular scale. We expand the autocorrelation function G(t) in terms of molecular modes and determine the thermal activation energies of the two largest modes, both of which are consistent with the range of literature values for rotational diffusion. We also determine the activation energies for translational diffusion and low-field electron-spin relaxation, both of which are consistent with the literature. Furthermore, we validate the MD simulations at human body temperature and concentrations of the paramagnetic ion used in clinical MRI, and we quantify the uncertainties in both simulations and measurements.

Predicting 1H NMR relaxation in Gd3+-aqua using molecular dynamics simulations.

Atomistic molecular dynamics simulations are used to predict 1H NMR T1 relaxation of water from paramagnetic Gd3+ ions in solution at 25 °C. Simulations of the T1 relaxivity dispersion function r1 computed from the Gd3+-1H dipole-dipole autocorrelation function agree within ≃8% of measurements in the range f0 ≃ 5 ↔ 500 MHz, without any adjustable parameters in the interpretation of the simulations, and without any relaxation models. The simulation results are discussed in the context of the Solomon-Bloembergen-Morgan inner-sphere relaxation model, and the Hwang-Freed outer-sphere relaxation model. Below f0 ≲ 5 MHz, the simulation overestimates r1 compared to measurements, which is used to estimate the zero-field electron-spin relaxation time. The simulations show potential for predicting r1 at high frequencies in chelated Gd3+ contrast-agents used for clinical MRI.

Toward in silico CMC: An industrial collaborative approach to model-based process development.

The Third Modeling Workshop focusing on bioprocess modeling was held in Kenilworth, NJ in May 2019. A summary of these Workshop proceedings is captured in this manuscript. Modeling is an active area of research within the biotechnology community, and there is a critical need to assess the current state and opportunities for continued investment to realize the full potential of models, including resource and time savings. Beyond individual presentations and topics of novel interest, a substantial portion of the Workshop was devoted toward group discussions of current states and future directions in modeling fields. All scales of modeling, from biophysical models at the molecular level and up through large scale facility and plant modeling, were considered in these discussions and are summarized in the manuscript. Model life cycle management from model development to implementation and sustainment are also considered for different stages of clinical development and commercial production. The manuscript provides a comprehensive overview of bioprocess modeling while suggesting an ideal future state with standardized approaches aligned across the industry.

Adsorption and Phase Behavior of Pure/Mixed Alkanes in Nanoslit Graphite Pores: An iSAFT Application.

The prediction of fluid phase behavior in nanoscale pores is critical for shale gas/oil development. In this work, we use a molecular density functional theory (DFT) to study the effect of molecular size and shape on partitioning to graphite nanopores as a model of shale. Here, interfacial statistical associating fluid theory (iSAFT) is applied to model alkane (C1 - C8) adsorption/desorption/phase behavior in graphite slit pores for both pure fluids and mixtures. The pure component parameters were fit to the bulk saturated liquid density and vapor pressure data in selected temperature ranges. The potential of interaction between the fluid and graphite is modeled with a Steele 10-4-3 potential that is fit to the potential of mean force from single-molecule simulations. Good agreement is found between theory and molecular simulation for the density distributions of pure components in slit pores. The critical properties of methane, ethane, and their mixtures as well as the shift in bubble point and dew point densities were studied, showing good agreement with simulation. The competitive adsorption of mixtures of normal and branched alkanes in graphite pores was also studied. Heavier components more strongly adsorb up to the point that the entropic penalty due to confinement reduces adsorption.

Mini-grand canonical ensemble: Chemical potential in the solvation shell.

Quantifying the statistics of occupancy of solvent molecules in the vicinity of solutes is central to our understanding of solvation phenomena. Number fluctuations in small solvation shells around solutes cannot be described within the macroscopic grand canonical framework using a single chemical potential that represents the solvent bath. In this communication, we hypothesize that molecular-sized observation volumes such as solvation shells are best described by coupling the solvation shell with a mixture of particle baths each with its own chemical potential. We confirm our hypotheses by studying the enhanced fluctuations in the occupancy statistics of hard sphere solvent particles around a distinguished hard sphere solute particle. Connections with established theories of solvation are also discussed.

Coordination state probabilities and the solvation free energy of Zn2+ in aqueous methanol solutions.

Coordination state probabilities for the [Zn(H(2)O)(n)(CH(3)OH)(m)](2+) complex in aqueous methanol solutions are calculated as a function of the bulk solution concentration, and the number of methanol ligands, m = 0, 1, ..., 6 with n+m = 6. Zinc ion solvation free energies, which serve to normalize these probabilities, also reproduce the methanol concentration dependence of the experimentally derived free energy of zinc ion transfer from water to aqueous methanol solutions. Coordination state probabilities, p(n, m), are derived by extending quasi-chemical theory of ion hydration to solvent mixtures and mixed ligands. Free energy contributions to p(n, m) include the free energy of forming the mixed-ligand complex in the ideal gas, obtained by quantum chemical calculations, and the solvation free energy of the complex, approximated by a dielectric continuum model. We find that replacing water ligands with methanol ligands preferentially stabilizes methanol-rich complexes in the ideal gas. Conversely, water-rich complexes are stabilized by the solvation free energy contribution, such that the [Zn(H(2)O)(6)](2+) complex is the dominant species in solution for all methanol concentrations considered. Stabilization of the methanol-rich complexes is a consequence of the local coordination chemistry, dominated by the delocalization of charge on the zinc ion, while the stabilization of water-rich complexes is a consequence of favorable ion-solvent electrostatic interactions and smaller dielectric cavities for the water-rich complexes at fixed total charge in the dielectric continuum model. Our analysis also highlights an entropic contribution associated with the reversible work required to remove n water and m methanol molecules from bulk solution to form the [Zn(H(2)O)(n)(CH(3)OH)(m)](2+) complex, which captures the methanol concentration dependence of the solvation free energy of the zinc ion.

Elucidating the 1H NMR Relaxation Mechanism in Polydisperse Polymers and Bitumen Using Measurements, MD Simulations, and Models.

The mechanism behind the 1H nuclear magnetic resonance (NMR) frequency dependence of T1 and the viscosity dependence of T2 for polydisperse polymers and bitumen remains elusive. We elucidate the matter through NMR relaxation measurements of polydisperse polymers over an extended range of frequencies (f0 = 0.01-400 MHz) and viscosities (η = 385-102 000 cP) using T1 and T2 in static fields, T1 field-cycling relaxometry, and T1ρ in the rotating frame. We account for the anomalous behavior of the log-mean relaxation times T1LM ∝ f0 and T2LM ∝ (η/T)-1/2 with a phenomenological model of 1H-1H dipole-dipole relaxation, which includes a distribution in molecular correlation times and internal motions of the nonrigid polymer branches. We show that the model also accounts for the anomalous T1LM and T2LM in previously reported bitumen measurements. We find that molecular dynamics (MD) simulations of the T1 ∝ f0 dispersion and T2 of similar polymers simulated over a range of viscosities (η = 1-1000 cP) are in good agreement with measurements and the model. The T1 ∝ f0 dispersion at high viscosities agrees with previously reported MD simulations of heptane confined in a polymer matrix, which suggests a common NMR relaxation mechanism between viscous polydisperse fluids and fluids under nanoconfinement, without the need to invoke paramagnetism.

Molecular dynamics simulations of NMR relaxation and diffusion of bulk hydrocarbons and water.

Molecular dynamics (MD) simulations are used to investigate 1H nuclear magnetic resonance (NMR) relaxation and diffusion of bulk n-C5H12 to n-C17H36 hydrocarbons and bulk water. The MD simulations of the 1H NMR relaxation times T1,2 in the fast motion regime where T1=T2 agree with measured (de-oxygenated) T2 data at ambient conditions, without any adjustable parameters in the interpretation of the simulation data. Likewise, the translational diffusion DT coefficients calculated using simulation configurations agree with measured diffusion data at ambient conditions. The agreement between the predicted and experimentally measured NMR relaxation times and diffusion coefficient also validate the forcefields used in the simulation. The molecular simulations naturally separate intramolecular from intermolecular dipole-dipole interactions helping bring new insight into the two NMR relaxation mechanisms as a function of molecular chain-length (i.e. carbon number). Comparison of the MD simulation results of the two relaxation mechanisms with traditional hard-sphere models used in interpreting NMR data reveals important limitations in the latter. With increasing chain length, there is substantial deviation in the molecular size inferred on the basis of the radius of gyration from simulation and the fitted hard-sphere radii required to rationalize the relaxation times. This deviation is characteristic of the local nature of the NMR measurement, one that is well-captured by molecular simulations.

Breast Cancer-Specific miR Signature Unique to Extracellular Vesicles Includes "microRNA-like" tRNA Fragments.

UNLABELLED: Extracellular vesicles (EV), including exosomes and shed vesicles, have been implicated in intercellular communication; however, their biomarker potential is less clear. Therefore, EVs derived from MCF7 and MCF10A cells were analyzed to identify unique miRNA (miR) profiles that distinguish their origin. One characteristic common to the miR profiles of MCF7 EVs and their parent cells is the high abundance of miR-21, let-7a, miR-100, and miR-125b, and low levels of miR-205. A second characteristic is the high abundance of "miRNA-like" tRNA fragments, which is unique to the MCF7 EVs, and is not found in comparing the cellular profiles. In addition, correlations were examined in the MCF7 cellular expression levels of these five miRs and two tRNA-derived miRNAs, miR-720 and miR-1274b, and compared with the correlations in MCF7 EV levels. Interestingly, correlations in the cellular expression of miR-125b, miR-100, and let-7a are mirrored in the EVs. In contrast, correlations in tRNA-derived miRNA levels are found only in the EVs. The findings suggest that EV miR clusters can be defined based on functional miR interactions related to correlated cellular expression levels or physical miR interactions, for example, aggregation due to comparable binding affinities to common targets. IMPLICATIONS: These results point to using high levels of tRNA-derived small RNA fragments in combination with known miR signatures of tumors to distinguish tumor-derived EVs in circulation from EVs derived from other cell sources. Such biomarkers would be unique to the EVs where high abundances of tRNA fragments are amplified with respect to their cellular levels.

Quasi-chemical theory of cosolvent hydrophobic preferential interactions.

Cosolvent hydrophobic preferential interactions with methane in aqueous methanol solutions are evaluated on the basis of the solute excess chemical potential derived from molecular simulations using the quasi-chemical (QC) theory generalization of the potential distribution theorem (PDT). We find that the methane-methanol preferential interaction parameter derived from QC theory quantitatively captures the favorable solvation of methane in methanol solutions in terms of important local solute-solvent (water and methanol) intermolecular interactions within a defined inner shell around the solute, and nonlocal solute interactions with solvent molecules outside this inner shell. Moreover, a unique inner shell can be defined such that the preferential interaction parameter is derived exclusively from the free energy of cavity formation in the aqueous cosolvent solution without the solute, where this cavity corresponds to the specified inner shell, and the mean interaction or binding energy of the solute with solvent molecules outside this inner shell. This inner-shell definition leads to a description of solute-cosolvent preferential interactions in which the molecular details of those interactions are derived from the effect of cosolvent on cavity statistics in the aqueous cosolvent solution alone. The finding suggests that solution thermodynamic behavior beyond steric exclusion (macromolecular crowding) contribute to the molecular mechanisms by which cosolvent preferential interactions influence protein stability and activity.