Advancing material property prediction: using physics-informed machine learning models for viscosity.

In materials science, accurately computing properties like viscosity, melting point, and glass transition temperatures solely through physics-based models is challenging. Data-driven machine learning (ML) also poses challenges in constructing ML models, especially in the material science domain where data is limited. To address this, we integrate physics-informed descriptors from molecular dynamics (MD) simulations to enhance the accuracy and interpretability of ML models. Our current study focuses on accurately predicting viscosity in liquid systems using MD descriptors. In this work, we curated a comprehensive dataset of over 4000 small organic molecules' viscosities from scientific literature, publications, and online databases. This dataset enabled us to develop quantitative structure-property relationships (QSPR) consisting of descriptor-based and graph neural network models to predict temperature-dependent viscosities for a wide range of viscosities. The QSPR models reveal that including MD descriptors improves the prediction of experimental viscosities, particularly at the small data set scale of fewer than a thousand data points. Furthermore, feature importance tools reveal that intermolecular interactions captured by MD descriptors are most important for viscosity predictions. Finally, the QSPR models can accurately capture the inverse relationship between viscosity and temperature for six battery-relevant solvents, some of which were not included in the original data set. Our research highlights the effectiveness of incorporating MD descriptors into QSPR models, which leads to improved accuracy for properties that are difficult to predict when using physics-based models alone or when limited data is available.

Ligand Lipophilicity Determines Molecular Mechanisms of Nanoparticle Adsorption to Lipid Bilayers.

The interactions of ligand-functionalized nanoparticles with the cell membrane affect cellular uptake, cytotoxicity, and related behaviors, but relating these interactions to ligand properties remains challenging. In this work, we perform coarse-grained molecular dynamics simulations to study how the adsorption of ligand-functionalized cationic gold nanoparticles (NPs) to a single-component lipid bilayer (as a model cell membrane) is influenced by ligand end group lipophilicity. A set of 2 nm diameter NPs, each coated with a monolayer of organic ligands that differ only in their end groups, was simulated to mimic NPs recently studied experimentally. Metadynamics calculations were performed to determine key features of the free energy landscape for adsorption as a function of the distance of the NP from the bilayer and the number of NP-lipid contacts. These simulations revealed that NP adsorption is thermodynamically favorable for all NPs due to the extraction of lipids from the bilayer and into the NP monolayer. To resolve ligand-dependent differences in adsorption behavior, string method calculations were performed to compute minimum free energy pathways for adsorption. These calculations revealed a surprising nonmonotonic dependence of the free energy barrier for adsorption on ligand end group lipophilicity. Large free energy barriers are predicted for the least lipophilic end groups because favorable NP-lipid contacts are initiated only through the unfavorable protrusion of lipid tail groups out of the bilayer. The smallest free energy barriers are predicted for end groups of intermediate lipophilicity which promote NP-lipid contacts by intercalating within the bilayer. Unexpectedly, large free energy barriers are also predicted for the most lipophilic end groups which remain sequestered within the ligand monolayer rather than intercalating within the bilayer. These trends are broadly in agreement with past experimental measurements and reveal how subtle variations in ligand lipophilicity dictate adsorption mechanisms and associated kinetics by influencing the interplay of lipid-ligand interactions.

Topological Analysis of Molecular Dynamics Simulations using the Euler Characteristic.

Molecular dynamics (MD) simulations are used in diverse scientific and engineering fields such as drug discovery, materials design, separations, biological systems, and reaction engineering. These simulations generate highly complex data sets that capture the 3D spatial positions, dynamics, and interactions of thousands of molecules. Analyzing MD data sets is key for understanding and predicting emergent phenomena and in identifying key drivers and tuning design knobs of such phenomena. In this work, we show that the Euler characteristic (EC) provides an effective topological descriptor that facilitates MD analysis. The EC is a versatile, low-dimensional, and easy-to-interpret descriptor that can be used to reduce, analyze, and quantify complex data objects that are represented as graphs/networks, manifolds/functions, and point clouds. Specifically, we show that the EC is an informative descriptor that can be used for machine learning and data analysis tasks such as classification, visualization, and regression. We demonstrate the benefits of the proposed approach through case studies that aim to understand and predict the hydrophobicity of self-assembled monolayers and the reactivity of complex solvent environments.

Predicting the Physicochemical Properties and Biological Activities of Monolayer-Protected Gold Nanoparticles Using Simulation-Derived Descriptors.

Gold nanoparticles are versatile materials for biological applications because their properties can be modulated by assembling ligands on their surface to form monolayers. However, the physicochemical properties and behaviors of monolayer-protected nanoparticles in biological environments are difficult to anticipate because they emerge from the interplay of ligand-ligand and ligand-solvent interactions that cannot be readily inferred from ligand chemical structure alone. In this work, we demonstrate that quantitative nanostructure-activity relationship (QNAR) models can employ descriptors calculated from molecular dynamics simulations to predict nanoparticle properties and cellular uptake. We performed atomistic molecular dynamics simulations of 154 monolayer-protected gold nanoparticles and calculated a small library of simulation-derived descriptors that capture nanoparticle structural and chemical properties in aqueous solution. We then parametrized QNAR models using interpretable regression algorithms to predict experimental measurements of nanoparticle octanol-water partition coefficients, zeta potentials, and cellular uptake obtained from a curated database. These models reveal that simulation-derived descriptors can accurately predict experimental trends and provide physical insight into what descriptors are most important for obtaining desired nanoparticle properties or behaviors in biological environments. Finally, we demonstrate model generalizability by predicting cell uptake trends for 12 nanoparticles not included in the original data set. These results demonstrate that QNAR models parametrized with simulation-derived descriptors are accurate, generalizable computational tools that could be used to guide the design of monolayer-protected gold nanoparticles for biological applications without laborious trial-and-error experimentation.

Lipophilicity of Cationic Ligands Promotes Irreversible Adsorption of Nanoparticles to Lipid Bilayers.

A mechanistic understanding of the influence of the surface properties of engineered nanomaterials on their interactions with cells is essential for designing materials for applications such as bioimaging and drug delivery as well as for assessing nanomaterial safety. Ligand-coated gold nanoparticles have been widely investigated because their highly tunable surface properties enable investigations into the effect of ligand functionalization on interactions with biological systems. Lipophilic ligands have been linked to adverse biological outcomes through membrane disruption, but the relationship between ligand lipophilicity and membrane interactions is not well understood. Here, we use a library of cationic ligands coated on 2 nm gold nanoparticles to probe the impact of ligand end group lipophilicity on interactions with supported phosphatidylcholine lipid bilayers as a model for cytoplasmic membranes. Nanoparticle adsorption to and desorption from the model membranes were investigated by quartz crystal microbalance with dissipation monitoring. We find that nanoparticle adsorption to model membranes increases with ligand lipophilicity. The effects of ligand structure on gold nanoparticle attachment were further analyzed using atomistic molecular dynamics simulations, which showed that the increase in ligand lipophilicity promotes ligand intercalation into the lipid bilayer. Together, the experimental and simulation results could be described by a two-state model that accounts for the initial attachment and subsequent conversion to a quasi-irreversibly bound state. We find that only nanoparticles coated with the most lipophilic ligands in our nanoparticle library undergo conversion to the quasi-irreversible state. We propose that the initial attachment is governed by interaction between the ligands and phospholipid tail groups, whereas conversion into the quasi-irreversibly bound state reflects ligand intercalation between phospholipid tail groups and eventual lipid extraction from the bilayer. The systematic variation of ligand lipophilicity enabled us to demonstrate that the lipophilicity of cationic ligands correlates with nanoparticle-bilayer adsorption and suggested that changing the nonpolar ligand R group promotes a mechanism of ligand intercalation into the bilayer associated with irreversible adsorption.

The Interplay of Ligand Properties and Core Size Dictates the Hydrophobicity of Monolayer-Protected Gold Nanoparticles.

The hydrophobicity of monolayer-protected gold nanoparticles is a crucial design parameter that influences self-assembly, preferential binding to proteins and membranes, and other nano-bio interactions. Predicting the effects of monolayer components on nanoparticle hydrophobicity is challenging due to the nonadditive, cooperative perturbations to interfacial water structure that dictate hydrophobicity at the nanoscale. In this work, we quantify nanoparticle hydrophobicity by using atomistic molecular dynamics simulations to calculate local hydration free energies at the nanoparticle-water interface. The simulations reveal that the hydrophobicity of large gold nanoparticles is determined primarily by ligand end group chemistry, as expected. However, for small gold nanoparticles, long alkanethiol ligands interact to form anisotropic bundles that lead to substantial spatial variations in hydrophobicity even for homogeneous monolayer compositions. We further show that nanoparticle hydrophobicity is modulated by changing the ligand structure, ligand chemistry, and gold core size, emphasizing that single-ligand properties alone are insufficient to characterize hydrophobicity. Finally, we illustrate that hydration free energy measurements correlate with the preferential binding of propane as a representative hydrophobic probe molecule. Together, these results show that both physical and chemical properties influence the hydrophobicity of small nanoparticles and must be considered together when predicting gold nanoparticle interactions with biomolecules.

Recycling of multilayer plastic packaging materials by solvent-targeted recovery and precipitation.

Many plastic packaging materials manufactured today are composites made of distinct polymer layers (i.e., multilayer films). Billions of pounds of these multilayer films are produced annually, but manufacturing inefficiencies result in large, corresponding postindustrial waste streams. Although relatively clean (as opposed to municipal wastes) and of near-constant composition, no commercially practiced technologies exist to fully deconstruct postindustrial multilayer film wastes into pure, recyclable polymers. Here, we demonstrate a unique strategy we call solvent-targeted recovery and precipitation (STRAP) to deconstruct multilayer films into their constituent resins using a series of solvent washes that are guided by thermodynamic calculations of polymer solubility. We show that the STRAP process is able to separate three representative polymers (polyethylene, ethylene vinyl alcohol, and polyethylene terephthalate) from a commercially available multilayer film with nearly 100% material efficiency, affording recyclable resins that are cost-competitive with the corresponding virgin materials.

Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks.

The rates of liquid-phase, acid-catalyzed reactions relevant to the upgrading of biomass into high-value chemicals are highly sensitive to solvent composition and identifying suitable solvent mixtures is theoretically and experimentally challenging. We show that the complex atomistic configurations of reactant-solvent environments generated by classical molecular dynamics simulations can be exploited by 3D convolutional neural networks to enable accurate predictions of Brønsted acid-catalyzed reaction rates for model biomass compounds. We develop a 3D convolutional neural network, which we call SolventNet, and train it to predict acid-catalyzed reaction rates using experimental reaction data and corresponding molecular dynamics simulation data for seven biomass-derived oxygenates in water-cosolvent mixtures. We show that SolventNet can predict reaction rates for additional reactants and solvent systems an order of magnitude faster than prior simulation methods. This combination of machine learning with molecular dynamics enables the rapid, high-throughput screening of solvent systems and identification of improved biomass conversion conditions.

Quantifying the Stability of the Hydronium Ion in Organic Solvents With Molecular Dynamics Simulations.

The solution-phase stability of the hydronium ion catalyst significantly affects the rates of acid-catalyzed reactions, which are ubiquitously utilized to convert biomass to valuable chemicals. In this work, classical molecular dynamics simulations were performed to quantify the stability of hydronium and chloride ions by measuring their solvation free energies in water, 1,4-dioxane (DIOX), tetrahydrofuran (THF), γ-valerolactone (GVL), N-methyl-2-pyrrolidone (NMP), acetone (ACE), and dimethyl sulfoxide (DMSO). By measuring the free energy for transferring a hydronium ion from pure water to pure organic solvent, we found that the hydronium ion is destabilized in DIOX, THF, and GVL and stabilized in NMP, ACE, and DMSO relative to water. The distinction between these organic solvents can be used to predict the preference of the hydronium ion for specific regions in aqueous mixtures of organic solvents. We then incorporated the stability of the hydronium ion into a correlative model for the acid-catalyzed conversion of 1,2-propanediol to propanal. The revised model is able to predict experimental reaction rates across solvent systems with different organic solvents. These results demonstrate the ability of classical molecular dynamics simulations to screen solvent systems for improved acid-catalyzed reaction performance.

Inherently variable responses to glucocorticoid stress among endogenous retroviruses isolated from 23 mouse strains.

Active participation of endogenous retroviruses (ERVs) in disease processes has been exemplified by the finding that the HERV (human ERV)-W envelope protein is involved in the pathogenesis of multiple sclerosis, an autoimmune disease. We also demonstrated that injury-elicited stressors alter the expression of murine ERVs (MuERVs), both murine leukemia virus-type and mouse mammary tumor virus (MMTV)-type (MMTV-MuERV). In this study, to evaluate MMTV-MuERVs' responses to stress (e.g., injury, infection)-elicited systemic glucocorticoid (GC) levels, we examined the GC-stress response of 64 MMTV-MuERV promoters isolated from the genomes of 23 mouse strains. All 64 promoters responded to treatment with a synthetic GC, dexamethasone (DEX), at a wide range from a 0.6- to 85.7-fold increase in reporter activity compared to no treatment. An analysis of the 10 lowest and 10 highest DEX responders revealed specific promoter elements exclusively present in either the three lowest or the two highest responders. Each promoter had a unique profile of transcription regulatory elements and the glucocorticoid response element (GRE) was identified in all promoters with the number of GREs ranging from 2 to 7. The three lowest DEX responders were the only promoters with two GREs. The findings from this study suggest that certain MMTV-MuERVs are more responsive to stress-elicited systemic GC elevation compared to the others. The mouse strain-specific genomic MMTV-MuERV profiles and individual MMTV-MuERVs' differential responses to GC-stress might explain, at least in part, the variable inflammatory responses to injury and/or infection, often observed among different mouse strains. This article is part of a Special Issue entitled: Immune and Metabolic Alterations in Trauma and Sepsis edited by Dr. Raghavan Raju.

ERE database: a database of genomic maps and biological properties of endogenous retroviral elements in the C57BL/6J mouse genome.

Endogenous retroviral elements (EREs), a family of transposable elements, constitute a substantial fraction of mammalian genomes. It is expected that profiles of the ERE sequences and their genomic locations are unique for each individual. Comprehensive characterization of the EREs' genomic locations and their biological properties is essential for understanding their roles in the pathophysiology of the host. In this study, we identified and mapped putative EREs (a total of 111 endogenous retroviruses [ERVs] and 488 solo long terminal repeats [sLTRs]) within the C57BL/6J mouse genome. The biological properties of individual ERE isolates (both ERVs and sLTRs) were then characterized in the following aspects: transcription potential, tropism trait, coding potential, recombination event, integration age, and primer binding site for replication. In addition, a suite of database management system programs was developed to organize and update the data acquired from current and future studies and to make the data accessible via internet.

Tropism, cytotoxicity, and inflammatory properties of two envelope genes of murine leukemia virus type-endogenous retroviruses of C57BL/6J mice.

Envelope (env) proteins of certain endogenous retroviruses (ERVs) participate in various pathophysiological processes. In this study, we characterized pathophysiologic properties of two murine leukemia virus-type ERV (MuLV-ERV) env genes cloned from the ovary of C57BL/6J mice. The two env genes (named ENV(OV1) and ENV(OV2)), with 1,926 bp coding region, originated from two MuLV-ERV loci on chromosomes 8 and 18, respectively. ENV(OV1) and ENV(OV2) were ~75 kDa and predominantly expressed on the cell membrane. They were capable of producing pseudotype murine leukemia virus virions. Tropism trait and infectivity of ENV(OV2) were similar to the polytropic env; however, ENV(OV1) had very low level of infectivity. Overexpression of ENV(OV2), but not ENV(OV1), exerted cytotoxic effects and induced expression of COX-2, IL-1ß, IL-6, and iNOS. These findings suggest that the ENV(OV1) and ENV(OV2) are capable of serving as an env protein for virion assembly, and they exert differential cytotoxicity and modulation of inflammatory mediators.

Prevalent de novo somatic mutations in superantigen genes of mouse mammary tumor viruses in the genome of C57BL/6J mice and its potential implication in the immune system.

BACKGROUND: Superantigens (SAgs) of mouse mammary tumor viruses (MMTVs) play a crucial role in T cell selection in the thymus in a T cell receptor (TCR) Vß-specific manner and SAgs presented by B cells activate T cells in the periphery. The peripheral T cell repertoire is dynamically shaped by the steady induction of T cell tolerance against self antigens throughout the lifespan. We hypothesize that de novo somatic mutation of endogenous MMTV SAgs contributes to the modulation of the peripheral T cell repertoire. RESULTS: SAg coding sequences were cloned from the genomic DNAs and/or cDNAs of various tissues of female C57BL/6J mice. A total of 68 unique SAg sequences (54 translated sequences) were identified from the genomic DNAs of liver, lungs, and bone marrow, which are presumed to harbor only three endogenous MMTV loci (Mtv-8, Mtv-9, and Mtv-17). Similarly, 69 unique SAg sequences (58 translated sequences) were cloned from the cDNAs of 18 different tissues. Examination of putative TCR Vß specificity suggested that some of the SAg isoforms identified in this study have Vß specificities different from the reference SAgs of Mtv-8, Mtv-9, or Mtv-17. CONCLUSION: The pool of diverse SAg isoforms, generated by de novo somatic mutation, may play a role in the shaping of the peripheral T cell repertoire including the autoimmune T cell population.

Two-photon luminescence from polar bis-terpyridyl-stilbene derivatives of Ir(III) and Ru(II).

Four structurally related iridium(III) and ruthenium(II) complexes bearing two polar terpyridyl-stilbene derived chromophores 4-(4-{2-[4-(methoxy)phenyl]ethenyl}phenyl)-2,2'-6',2''-terpyridine (ttpyeneanisole) and 4-(4-{2-[phenyl]ethenyl}phenyl)-2,2'-6',2''-terpyridine (tpystilbene) have been synthesised and characterised in the solid state and in solution. In the solid state, the dihedral angle subtending the pyridyl and tolyl groups of 27.1° in the Ir(III) complex [Ir(ttpyeneanisole)(2)]·3PF(6) is more acute than in the Ru(II) derivative [Ru(tpystilbene)(2)]·2PF(6) (35.5°), indicating the presence of a greater degree of π-delocalisation across the terpyridine unit in the former compound. Their luminescence properties in fluid solution have been investigated following both resonant and non-resonant excitation. We have shown that each of the complexes undergoes two-photon excitation when excited in the near infrared (740 to 820 nm), with two-photon absorption cross sections in the range 11-67 × 10(-50) cm(4) s photon(-1). The larger cross sections for the Ir(III) complexes reflect the differences observed in the solid state. This work therefore demonstrates that such complexes are promising as luminescent markers for 3D imaging and illustrates that simple functionalisation of the chromophores and the choice of metal can lead to marked enhancements in the two-photon cross sections (σ(2)) compared to those of simpler heteroleptic polypyridyl based derivatives.

Identification of putative endogenous retroviruses actively transcribed in the brain.

Remnant proviral sequences in the genome resulting from the ancient germline infection of exogenous retroviruses are called endogenous retroviruses (ERVs). The transcriptional activation of human ERVs (HERVs) in the brain of patients with some neurologic diseases suggests that ERVs may participate in certain disease processes in the central nervous system. In this study, we identified putative murine ERVs (MuERVs) which are transcriptionally active in the brain and characterized their biological properties to better understand the ERVs' roles in the brain pathophysiology. The brain and selective non-nervous tissues (heart, muscle, adrenal gland, and salivary gland) of female C57BL/6J mice were subjected to RT-PCR analyses of MuERV expression by amplifying the 3'-end U3 regions and full-length/subgenomic transcripts. The expression patterns of the U3 regions and subgenomic transcripts in the brain were unique compared to the other tissues as well as the genomic MuERV profile. Two putative MuERVs (8,027 and 5,668 bp) were mapped on the mouse genome (chromosome 10, and chromosomes 4 and 8, respectively) using the MuERV U3 sequences, which were evidently expressed in the brain, as probes. Biological properties of these putative MuERVs, such as transcription potential, primer binding site, coding potential, integration age, recombination, and flanking host genes, were characterized. In particular, one of the two putative MuERV isolates had coding potentials for intact group specific antigen (gag), and truncated polymerase (pol) and envelope (env) polypeptides, while the other was defective for all three polypeptides. The findings from this study suggest that a specific group of MuERVs are constitutively expressed in the brain and they may participate in normal and pathogenic events pertaining to the brain through their replication gene products (e.g., gag and env polypeptides) as well as interactions with flanking host genes.

Genome-wide expression profiles of endogenous retroviruses in lymphoid tissues and their biological properties.

Endogenous retroviruses (ERVs) constitute approximately 8-10% of the human and mouse genome. Some autoimmune diseases are attributed to the altered expression of ERVs. In this study, we examined the ERV expression profiles in lymphoid tissues and analyzed their biological properties. Tissues (spleen, thymus, and lymph nodes [axillary, inguinal, and mesenteric]) from C57BL/6J mice were analyzed for differential murine ERV (MuERV) expression by RT-PCR examination of polymorphic U3 sequences. Each tissue had a unique profile of MuERV expression. A genomic map identifying 60 putative MuERVs was established using 22 unique U3s as probes and their biological properties (primer binding site, coding potential, transcription regulatory element, tropism, recombination event, and integration age) were characterized. Interestingly, 12 putative MuERVs retained intact coding potentials for all three polypeptides essential for virus assembly and replication. We suggest that MuERV expression is differentially regulated in conjunction with the transcriptional environment of individual lymphoid tissues.

Genome-wide changes in expression profile of murine endogenous retroviruses (MuERVs) in distant organs after burn injury.

BACKGROUND: Previous studies have shown that burn-elicited stress signals alter expression of certain murine endogenous retroviruses (MuERVs) in distant organs of mice. These findings suggest that MuERVs may participate in a network of pathophysiologic events during post-burn systemic response. To gain a better understanding of the biological roles of MuERVs in post-burn systemic response, we examined the genome-wide changes in the MuERV expression profiles in distant organs and the biological properties of the putative-burn related MuERVs were characterized. RESULTS: Female C57BL/6J mice were subjected to an approximately 18 % total body surface area flame burn and tissues (liver, lung, and kidney) were harvested at 3 hours and 24 hours after injury. The changes in the MuERV expression profiles in these tissues were examined by RT-PCR using a primer set flanking the non-ecotropic MuERV U3 promoter region within the 3' long terminal repeat. There were differential changes in the expression profiles of MuERV U3 regions after injury in all three tissues examined. Subsequently, a total of 31 unique U3 promoter sequences were identified from the tissues of both burn and no burn mice. An analysis of viral tropisms revealed that putative MuERVs harboring these U3 promoter sequences were presumed to be either xenotropic or polytropic. Some putative transcription regulatory elements were present predominantly in U3 promoter sequences isolated from burn and no burn mice, respectively. In addition, in silico mapping using these U3 sequences as a probe against the mouse genome database identified 59 putative MuERVs. The biological properties (coding potentials for retroviral polypeptides, primer binding sites, tropisms, branching ages, recombination events, and neighboring host genes) of each putative MuERV were characterized. In particular, 16 putative MuERVs identified in this study retained intact coding potentials for all three retroviral polypeptides (gag, pol, and env). None of the putative MuERVs identified in this study were mapped to the coding sequences of host genes. CONCLUSION: In this study, we identified and characterized putative MuERVs whose expression might be altered in response to burn-elicited systemic stress signals. Further investigation is needed to understand the role of these MuERVs in post-burn systemic pathogenesis, in particular, via characterization of their interaction with host genes, MuERV gene products, and viral activities.