Uncertainty Quantification and Sensitivity Analysis of Partial Charges on Macroscopic Solvent Properties in Molecular Dynamics Simulations with a Machine Learning Model.

The molecular dynamics (MD) simulation technique is among the most broadly used computational methods to investigate atomistic phenomena in a variety of chemical and biological systems. One of the most common (and most uncertain) parametrization steps in MD simulations of soft materials is the assignment of partial charges to atoms. Here, we apply uncertainty quantification and sensitivity analysis calculations to assess the uncertainty associated with partial charge assignment in the context of MD simulations of an organic solvent. Our results indicate that the effect of partial charge variance on bulk properties, such as solubility parameters, diffusivity, dipole moment, and density, measured from MD simulations is significant; however, measured properties are observed to be less sensitive to partial charges of less accessible (or buried) atoms. Diffusivity, for example, exhibits a global sensitivity of up to 22 × 10-5 cm2/s per electron charge on some acetonitrile atoms. We then demonstrate that machine learning techniques, such as Gaussian process regression (GPR), can be effective and rapid tools for uncertainty quantification of MD simulations. We show that the formulation and application of an efficient GPR surrogate model for the prediction of responses effectively reduces the computational time of additional sample points from hours to milliseconds. This study provides a much-needed context for the effect that partial charge uncertainty has on MD-derived material properties to illustrate the benefit of considering partial charges as distributions rather than point-values. To aid in this treatment, this work then demonstrates methods for rapid characterization of resulting sensitivity in MD simulations.

Therapeutic plasma exchange as a novel treatment for severe intrahepatic cholestasis of pregnancy: Case series and mechanism of action.

INTRODUCTION: Intrahepatic cholestasis of pregnancy is characterised by pruritus and elevated serum bile acids. The pruritus can be severe, and pharmacological options achieve inconsistent symptomatic improvement. Raised bile acids are linearly associated with adverse fetal outcomes, with existing management of limited benefit. We hypothesised that therapeutic plasma exchange removes pruritogens and lowers total bile acid concentrations, and improves symptoms and biochemical abnormalities in severe cases that have not responded to other treatments. METHODS: Four women with severe pruritus and hypercholanemia were managed with therapeutic plasma exchange. Serial blood biochemistry and visual analogue scores of itch severity were obtained. Blood and waste plasma samples were collected before and after exchange; individual bile acids and sulfated progesterone metabolites were measured with HPLC-MS, autotaxin activity and cytokine profiles with enzymatic methods. Results were analysed using segmental linear regression to describe longitudinal trends, and ratio t tests. RESULTS: Total bile acids and visual analogue itch scores demonstrated trends to transiently improve following plasma exchange, with temporary symptomatic benefit reported. Individual bile acids (excluding the drug ursodeoxycholic acid), and the sulfated metabolites of progesterone reduced following exchange (P = .03 and P = .04, respectively), whilst analysis of waste plasma demonstrated removal of autotaxin and cytokines. CONCLUSIONS: Therapeutic plasma exchange can lower potentially harmful bile acids and improve itch, likely secondary to the demonstrated removal of pruritogens. However, the limited current experience and potential complications, along with minimal sustained symptomatic benefit, restrict its current use to women with the most severe disease for whom other treatment options have been exhausted.

Advances in Molecular Modeling of Nanoparticle-Nucleic Acid Interfaces.

Nanoparticles (NPs) play increasingly important roles in nanotechnology and nanomedicine in which nanoparticle surface chemistry allows for control over interactions with other nanoparticles and biomolecules. In particular, for applications in drug and gene delivery, a fundamental understanding of the NP-nucleic acid interface allows for development of more efficient and effective nanoparticle carriers. Computational modeling can provide insights of processes occurring at the inorganic NP-nucleic interface in detail that is difficult to access by experimental methods. With recent advances such as the use of graphics processing units (GPUs) for simulations, computational modeling has the potential to give unprecedented insight into inorganic-biological interfaces via the examination of increasingly large and complex systems. In this Topical Review, we briefly review computational methods relevant to the interactions of inorganic NPs and nucleic acids and highlight recent insights obtained from various computational methods that were applied to studies of inorganic nanoparticle-nanoparticle and nanoparticle-nucleic acid interfaces.

High-Performance Chromatographic Characterization of Surface Chemical Heterogeneities of Fluorescent Organic-Inorganic Hybrid Core-Shell Silica Nanoparticles.

In contrast to small-molar-mass compounds, detailed structural investigations of inorganic core-organic ligand shell hybrid nanoparticles remain challenging. The assessment of batch-reaction-induced heterogeneities of surface chemical properties and their correlation with particle size has been a particularly long-standing issue. Applying a combination of high-performance liquid chromatography (HPLC) and gel permeation chromatography (GPC) to ultra-small (<10 nm diameter) poly(ethylene glycol)-coated (PEGylated) fluorescent core-shell silica nanoparticles, we elucidate here previously unknown surface heterogeneities resulting from varying dye conjugation to nanoparticle silica cores and surfaces. Heterogeneities are predominantly governed by dye charge, as corroborated by molecular dynamics simulations. We demonstrate that this insight enables the development of synthesis protocols to achieve PEGylated and targeting ligand-functionalized PEGylated silica nanoparticles with dramatically improved surface chemical homogeneity, as evidenced by single-peak HPLC chromatograms. Because surface chemical properties are key to all nanoparticle interactions, we expect these methods and fundamental insights to become relevant to a number of systems for applications, including bioimaging and nanomedicine.

Progress in ligand design for monolayer-protected nanoparticles for nanobio interfaces.

Ligand-functionalized inorganic nanoparticles, also known as monolayer-protected nanoparticles, offer great potential as vehicles for in vivo delivery of drugs, genes, and other therapeutics. These nanoparticles offer highly customizable chemistries independent of the size, shape, and functionality imparted by the inorganic core. Their success as drug delivery agents depends on their interaction with three major classes of biomolecules: nucleic acids, proteins, and membranes. Here, the authors discuss recent advances and open questions in the field of nanoparticle ligand design for nanomedicine, with a focus on atomic-scale interactions with biomolecules. While the importance of charge and hydrophobicity of ligands for biocompatibility and cell internalization has been demonstrated, ligand length, flexibility, branchedness, and other properties also influence the properties of nanoparticles. However, a comprehensive understanding of ligand design principles lies in the cost associated with synthesizing and characterizing diverse ligand chemistries and the ability to carefully assess the structural integrity of biomolecules upon interactions with nanoparticles.

Fullerenes in Aromatic Solvents: Correlation between Solvation-Shell Structure, Solvate Formation, and Solubility.

In this work, an all-atom molecular dynamics simulation technique was employed to gain insight into the dynamic structure of the solvation shell formed around C60 and phenyl-C61-butyric acid methyl ester (PCBM) in nine aromatic solvents. A new method was developed to visualize and quantify the distribution of solvent molecule orientations in the solvation shell. A strong positive correlation was found between the regularity of solvent molecule orientations in the solvation shell and the experimentally obtained solubility limits for both C60 and PCBM. This correlation was extended to predict a solubility of 36 g/L for PCBM in 1,2,4-trimethylbenze. The relationship between solvation-shell structure and solubility provided detailed insight into solvate formation of C60 and solvation in relation to solvent molecular structure and properties. The determined dependence of the solvation-shell structure on the geometric shape of the solvent might allow for enhanced control of fullerene solution-phase behavior during processing by chemically tailoring the solvent molecular structure, potentially diminishing the need for costly and environmentally harmful halogenated solvents and/or additives.