Global Ring Study to Investigate the Comparability of Total Assay Performance of Commercial Claudin 18 Antibodies for Evaluation in Gastric Cancer.

Claudin 18.2 (CLDN18.2), the dominant isoform of CLDN18 in gastric tissues, is a highly specific tight junction protein of the gastric mucosa with variably retained expressions in gastric and gastroesophageal junction cancers. Additionally, CLDN18.2-targeted treatment with zolbetuximab, in combination with chemotherapy, has recently been assessed in 2 phase-III studies of patients with HER2-negative, locally advanced, unresectable, or metastatic gastric or gastroesophageal junction adenocarcinoma. These trials used the investigational VENTANA CLDN18 (43-14A) RxDx immunohistochemistry (IHC) assay on the Ventana BenchMark platform to identify patients eligible for CLDN18.2-targeted treatment. We report the findings of a global ring study evaluating the analytical comparability of concordance of the results of 3 CLDN18 antibodies (Ventana, LSBio, and Novus) stained on 3 IHC-staining platforms (Ventana, Dako, and Leica). A tissue microarray (TMA), comprising 15 gastric cancer cases, was stained by 27 laboratories across 11 countries. Each laboratory stained the TMAs using at least 2 of the 3 evaluated CLDN18 antibodies. Stained TMAs were assessed and scored using an agreed IHC-scoring algorithm, and the results were collated for statistical analysis. The data confirmed a high level of concordance for the VENTANA CLDN18 (43-14A; Ventana platform only) and LSBio antibodies on both the Dako and Leica platforms, with accuracy, precision, sensitivity, and specificity rates all reaching a minimum acceptable ≥85% threshold and good-to-excellent levels of concordance as measured by Cohen's kappa coefficient. The Novus antibody showed the highest level of variability against the reference central laboratory results for the same antibody/platform combinations. It also failed to meet the threshold for accuracy and sensitivity when used on either the Dako or Leica platform. These results demonstrated the reliability of IHC testing for CLDN18 expression in gastric tumor samples when using commercially available platforms with an appropriate methodology and primary antibody selection.

The Sphingosine and Phytosphingosine Ceramide Ratio in Lipid Models Forming the Short Periodicity Phase: An Experimental and Molecular Simulation Study.

The lipids located in the outermost layer of the skin, the stratum corneum (SC), play a crucial role in maintaining the skin barrier function. The primary components of the SC lipid matrix are ceramides (CERs), cholesterol (CHOL), and free fatty acids (FFAs). They form two crystalline lamellar phases: the long periodicity phase (LPP) and the short periodicity phase (SPP). In inflammatory skin conditions like atopic dermatitis and psoriasis, there are changes in the SC CER composition, such as an increased concentration of a sphingosine-based CER (CER NS) and a reduced concentration of a phytosphingosine-based CER (CER NP). In the present study, a lipid model was created exclusively forming the SPP, to examine whether alterations in the CER NS:CER NP molar ratio would affect the lipid organization. Experimental data were combined with molecular dynamics simulations of lipid models containing CER NS:CER NP at ratios of 1:2 (mimicking a healthy SC ratio) and 2:1 (observed in inflammatory skin diseases), mixed with CHOL and lignoceric acid as the FFA. The experimental findings show that the acyl chains of CER NS and CER NP and the FFA are in close proximity within the SPP unit cell, indicating that CER NS and CER NP adopt a linear conformation, similarly as observed for the LPP. Both the experiments and simulations indicate that the lamellar organization is the same for the two CER NS:CER NP ratios while the SPP NS:NP 1:2 model had a slightly denser hydrogen bonding network than the SPP NS:NP 2:1 model. The simulations show that this might be attributed to intermolecular hydrogen bonding with the additional hydroxide group on the headgroup of CER NP compared with CER NS.

MoSDeF-GOMC: Python Software for the Creation of Scientific Workflows for the Monte Carlo Simulation Engine GOMC.

MoSDeF-GOMC is a python interface for the Monte Carlo software GOMC to the Molecular Simulation Design Framework (MoSDeF) ecosystem. MoSDeF-GOMC automates the process of generating initial coordinates, assigning force field parameters, and writing coordinate (PDB), connectivity (PSF), force field parameter, and simulation control files. The software lowers entry barriers for novice users while allowing advanced users to create complex workflows that encapsulate simulation setup, execution, and data analysis in a single script. All relevant simulation parameters are encoded within the workflow, ensuring reproducible simulations. MoSDeF-GOMC's capabilities are illustrated through a number of examples, including prediction of the adsorption isotherm for CO2 in IRMOF-1, free energies of hydration for neon and radon over a broad temperature range, and the vapor-liquid coexistence curve of a four-component surrogate for the jet fuel S-8. The MoSDeF-GOMC software is available on GitHub at https://github.com/GOMC-WSU/MoSDeF-GOMC.

Multiscale Simulation of Ternary Stratum Corneum Lipid Mixtures: Effects of Cholesterol Composition.

Molecular dynamics simulations of mixtures of the ceramide nonhydroxy-sphingosine (NS), cholesterol, and a free fatty acid are performed to gain molecular-level understanding of the structure of the lipids found in the stratum corneum layer of skin. A new coarse-grained force field for cholesterol was developed using the multistate iterative Boltzmann inversion (MS-IBI) method. The coarse-grained cholesterol force field is compatible with previously developed coarse-grained force fields for ceramide NS, free fatty acids, and water and validated against atomistic simulations of these lipids using the CHARMM force field. Self-assembly simulations of multilayer structures using these coarse-grained force fields are performed, revealing that a large fraction of the ceramides adopt extended conformations, which cannot occur in the single bilayer in water structures typically studied using molecular simulation. Cholesterol fluidizes the membrane by promoting packing defects, and an increase in cholesterol content is found to reduce the bilayer thickness due to an increase in interdigitation of the C24 lipid tails, consistent with experimental observations. Using a reverse-mapping procedure, a self-assembled coarse-grained multilayer system is used to construct an equivalent structure with atomistic resolution. Simulations of this atomistic structure are found to closely agree with experimentally derived neutron scattering length density profiles. Significant interlayer hydrogen bonding is observed in the inner layers of the atomistic multilayer structure that are not found in the outer layers in contact with water or in equivalent bilayer structures. This work highlights the importance of simulating multilayer structures, as compared to the more commonly studied bilayer systems, to enable more appropriate comparisons with multilayer experimental membranes. These results also provide validation of the efficacy of the MS-IBI derived coarse-grained force fields and the framework for multiscale simulation.

High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning.

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.

Examining the self-assembly of patchy alkane-grafted silica nanoparticles using molecular simulation.

In this work, molecular dynamics simulations are used to examine the self-assembly of anisotropically coated "patchy" nanoparticles. Specifically, we use a coarse-grained model to examine silica nanoparticles coated with alkane chains, where the poles of the grafted nanoparticle are bare, resulting in strongly attractive patches. Through a systematic screening process, the patchy nanoparticles are found to form dispersed, string-like, and aggregated phases, dependent on the combination of alkane chain length, coating chain density, and the fractional coated surface area. Correlation analysis is used to identify the ability of various particle descriptors to predict bulk phase behavior from more computationally efficient single grafted nanoparticle simulations and demonstrates that the solvent-accessible surface area of the nanoparticle core is a key predictor of bulk phase behavior. The results of this work enhance our knowledge of the phase space of patchy nanoparticles and provide a powerful approach for future screening of these materials.

Effect of Ceramide Tail Length on the Structure of Model Stratum Corneum Lipid Bilayers.

Lipid bilayers composed of non-hydroxy sphingosine ceramide (CER NS), cholesterol (CHOL), and free fatty acids (FFAs), which are components of the human skin barrier, are studied via molecular dynamics simulations. Since mixtures of these lipids exist in dense gel phases with little molecular mobility at physiological conditions, care must be taken to ensure that the simulations become decorrelated from the initial conditions. Thus, we propose and validate an equilibration protocol based on simulated tempering, in which the simulation takes a random walk through temperature space, allowing the system to break out of metastable configurations and hence become decorrelated from its initial configuration. After validating the equilibration protocol, which we refer to as random-walk molecular dynamics, the effects of the lipid composition and ceramide tail length on bilayer properties are studied. Systems containing pure CER NS, CER NS + CHOL, and CER NS + CHOL + FFA, with the CER NS fatty acid tail length varied within each CER NS-CHOL-FFA composition, are simulated. The bilayer thickness is found to depend on the structure of the center of the bilayer, which arises as a result of the tail-length asymmetry between the lipids studied. The hydrogen bonding between the lipid headgroups and with water is found to change with the overall lipid composition, but is mostly independent of the CER fatty acid tail length. Subtle differences in the lateral packing of the lipid tails are also found as a function of CER tail length. Overall, these results provide insight into the experimentally observed trend of altered barrier properties in skin systems where there are more CERs with shorter tails present.

Molecular dynamics simulations of stratum corneum lipid mixtures: A multiscale perspective.

The lipid matrix of the stratum corneum (SC) layer of skin is essential for human survival; it acts as a barrier to prevent rapid dehydration while keeping potentially hazardous material outside the body. While the composition of the SC lipid matrix is known, the molecular-level details of its organization are difficult to infer experimentally, hindering the discovery of structure-property relationships. To this end, molecular dynamics simulations, which give molecular-level resolution, have begun to play an increasingly important role in understanding these relationships. However, most simulation studies of SC lipids have focused on preassembled bilayer configurations, which, owing to the slow dynamics of the lipids, may influence the final structure and hence the calculated properties. Self-assembled structures would avoid this dependence on the initial configuration, however, the size and length scales involved make self-assembly impractical to study with atomistic models. Here, we report on the development of coarse-grained models of SC lipids designed to study self-assembly. Building on previous work, we present the interactions between the headgroups of ceramide and free fatty acid developed using the multistate iterative Boltzmann inversion method. Validation of the new interactions is performed with simulations of preassembled bilayers and good agreement between the atomistic and coarse-grained models is found for structural properties. The self-assembly of mixtures of ceramide and free fatty acid is investigated and both bilayer and multilayer structures are found to form. This work therefore represents a necessary step in studying SC lipid systems on multiple time and length scales.

Investigating Alkylsilane Monolayer Tribology at a Single-Asperity Contact with Molecular Dynamics Simulation.

Chemisorbed monolayer films are known to possess favorable characteristics for nanoscale lubrication of micro- and nanoelectromechanical systems (MEMS/NEMS). Prior studies have shown that the friction observed for monolayer-coated surfaces features a strong dependence on the geometry of contact. Specifically, tip-like geometries have been shown to penetrate into monolayer films, inducing defects in the monolayer chains and leading to plowing mechanisms during shear, which result in higher coefficients of friction (COF) than those observed for planar geometries. In this work, we use molecular dynamics simulations to examine the tribology of model silica single-asperity contacts under shear with monolayer-coated substrates featuring various film densities. It is observed that lower monolayer densities lead to reduced COFs, in contrast to results for planar systems where COF is found to be nearly independent of monolayer density. This is attributed to a liquid-like response to shear, whereby fewer defects are imparted in monolayer chains from the asperity, and chains are easily displaced by the tip as a result of the higher free volume. This transition in the mechanism of molecular plowing suggests that liquid-like films should provide favorable lubrication at single-asperity contacts.

Investigating the Structure of Multicomponent Gel-Phase Lipid Bilayers.

Single- and multicomponent lipid bilayers of 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC), 1,2-distearoyl-sn-glycero-3-phosphatidylcholine (DSPC), isostearyl isostearate, and heptadecanoyl heptadecanoate in the gel phase are studied via molecular dynamics simulations. It is shown that the structural properties of multicomponent bilayers can deviate strongly from the structures of their single-component counterparts. Specifically, the lipid mixtures are shown to adopt a compact packing by offsetting the positioning depths at which different lipid species are located in the bilayer. This packing mechanism affects the area per lipid, the bilayer height, and the chain tilt angles and has important consequences for other bilayer properties, such as interfacial hydrogen bonding and bilayer permeability. In particular, the simulations suggest that bilayers containing isostearyl isostearate or heptadecanoyl heptadecanoate are less permeable than pure 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine or DSPC bilayers. Furthermore, hydrogen-bond analysis shows that the residence times of lipid-water hydrogen bonds depend strongly on the bilayer composition, with longer residence times for bilayers that have a higher DSPC content. The findings illustrate and explain the fundamental differences between the properties of single- and multicomponent bilayers.

Influence of Surface Morphology on the Shear-Induced Wear of Alkylsilane Monolayers: Molecular Dynamics Study.

Chemisorbed alkylsilane monolayer coatings have been shown to possess favorable lubrication properties; however, film degradation prevents the widespread use of these materials as lubricants in micro- and nanoelectromechanical systems (MEMS/NEMS). In this work, molecular dynamics (MD) simulations are used to provide insight into the conditions that promote the degradation and wear of these materials. This is achieved through removal of interfacial chain-substrate bonds during shear and the examination of the mobility of the resulting free, unbound chains. Specific focus is given to the effects of surface morphology, which has been shown previously to strongly influence frictional forces in monolayer systems. In-plane order of chain attachments is shown to lead to pressure-induced orientational ordering of monolayers, promoting film stability. This behavior is lost as nonideality is introduced into the substrate and chain patterning on the surface becomes disordered. The presence of surface roughness is found to reduce film stability, with localization of wear observed for chain attachment sites nearest the interface of contact. The influence of substrate nonideality on monolayer degradation is shown to diminish as chain length is increased.

Molecular dynamics study of alkylsilane monolayers on realistic amorphous silica surfaces.

Interfacial properties of n-alkylsilane monolayers on silica have been investigated with molecular dynamics simulations using both reactive and classical (i.e., nonreactive) force fields. A synthesis mimetic simulation (SMS) procedure using the reactive force field ReaxFF has been developed to mimic the experimental processing of silicon wafers involved in the preparation of alkylsilane monolayers; in the SMS procedure, amorphous silica surfaces are generated and exposed to hydrogen peroxide (H2O2) to create a hydroxide surface layer. Alkylsilane monolayers are then assembled on these surfaces, and their behavior is studied. To investigate the impact of the SMS procedure on monolayer properties, simulations have also been performed using more idealized monolayers assembled on crystalline surfaces and non-H2O2-processed amorphous surfaces. The simulations reported here demonstrate that processing-induced silica surface roughness plays a key role in the structure and frictional performance of monolayers. Furthermore, ignoring these effects results in a significant underestimation of the coefficient of friction and an overestimation of the orientational ordering of the monolayers.

Tunable transition from hydration to monomer-supported lubrication in zwitterionic monolayers revealed by molecular dynamics simulation.

The tribology of 2-methacryloyloxyethyl phosphorylcholine monolayers in water is studied using molecular dynamics simulations. Our results show two distinct shear regimes where the first is dominated by hydration lubrication, exhibiting near zero friction coefficients, and the second by chain-chain interactions, resembling monomer-supported lubrication. These results provide insight into the hydration lubrication mechanism - a phenomena thought to underlie the extremely efficient lubrication provided by surfaces functionalized with polyzwitterionic polymer brushes and the mammalian synovial joint.

Examination of the phase transition behavior of nano-confined fluids by statistical temperature molecular dynamics.

The fluid-solid phase transition behavior of nano-confined Lennard-Jones fluids as a function of temperature and degree of nanoconfinement has been studied via statistical temperature molecular dynamics (STMD). The STMD method allows the direct calculation of the density of states and thus the heat capacity with high efficiency. The fluids are simulated between parallel solid surfaces with varying pore sizes, wall-fluid interaction energies, and registry of the walls. The fluid-solid phase transition behavior has been characterized through determination of the heat capacity. The results show that for pores of ideal-spacing, the order-disorder transition temperature (T(ODT)) is reduced as the pore size increases until values consistent with that seen in a bulk system. Also, as the interaction between the wall and fluid is reduced, T(ODT) is reduced due to weak constraints from the wall. However, for non-ideal spacing pores, quite different behavior is obtained, e.g., generally T(ODT) are largely reduced, and T(ODT) is decreased as the wall constraint becomes larger. For unaligned walls (i.e., whose lattices are not in registry), the fluid-solid transition is also detected as T is reduced, indicating non-ideality in orientation of the walls does not impact the formation of a solid, but results in a slight change in T(ODT) compared to the perfectly aligned systems. The STMD method is demonstrated to be a robust way for probing the phase transitions of nanoconfined fluids systematically, enabling the future examination of the phase transition behavior of more complex fluids.

Examining the aggregation behavior of polymer grafted nanoparticles using molecular simulation and theory.

Grafting polymers to nanoparticles is one approach used to control and enhance the structure and properties of nanomaterials. However, predicting the aggregation behavior of tethered nanoparticles (TNPs) is a somewhat trial and error process as a result of the large number of possible polymer tethers, nanoparticles, and solvent species that can be studied. With the main goal of understanding how to control the dispersion and aggregation of TNP systems, molecular simulations and the hetero-statistical associating fluid theory for potentials of variable range have been used to calculate the fluid phase equilibrium of TNPs in both vacuum and in simple solvents under a wide range of conditions. The role of graft length, graft density, and solvent interactions is examined and trends established. Additionally, the fluid distribution ratio (k value) is used to study the solubility of TNPs in industrially relevant solvents including carbon dioxide, nitrogen, propane, and ethylene.

Derivation of coarse-grained potentials via multistate iterative Boltzmann inversion.

In this work, an extension is proposed to the standard iterative Boltzmann inversion (IBI) method used to derive coarse-grained potentials. It is shown that the inclusion of target data from multiple states yields a less state-dependent potential, and is thus better suited to simulate systems over a range of thermodynamic states than the standard IBI method. The inclusion of target data from multiple states forces the algorithm to sample regions of potential phase space that match the radial distribution function at multiple state points, thus producing a derived potential that is more representative of the underlying interactions. It is shown that the algorithm is able to converge to the true potential for a system where the underlying potential is known. It is also shown that potentials derived via the proposed method better predict the behavior of n-alkane chains than those derived via the standard IBI method. Additionally, through the examination of alkane monolayers, it is shown that the relative weight given to each state in the fitting procedure can impact bulk system properties, allowing the potentials to be further tuned in order to match the properties of reference atomistic and/or experimental systems.

E(n) Equivariant Graph Neural Network for Learning Interactional Properties of Molecules.

We have developed a multi-input E(n) equivariant graph convolution-based model designed for the prediction of chemical properties that result from the interaction of heterogeneous molecular structures. By incorporating spatial features and constraining the functions learned from these features to be equivariant to E(n) symmetries, the interactional-equivariant graph neural network (IEGNN) can efficiently learn from the 3D structure of multiple molecules. To verify the IEGNN's capability to learn interactional properties, we tested the model's performance on three molecular data sets, two of which are curated in this study and made publicly available for future interactional model benchmarking. To enable the loading of these data sets, an open-source data structure based on the PyTorch Geometric library for batch loading multigraph data points is also created. Finally, the IEGNN's performance on a data set consisting of an unknown interactional relationship (the frictional properties resulting between monolayers with variable composition) is examined. The IEGNN model developed was found to have the lowest mean absolute percent error for the predicted tribological properties of four of the six data sets when compared to previous methods.

Computational investigation of glycosylation effects on a family 1 carbohydrate-binding module.

Carbohydrate-binding modules (CBMs) are ubiquitous components of glycoside hydrolases, which degrade polysaccharides in nature. CBMs target specific polysaccharides, and CBM binding affinity to cellulose is known to be proportional to cellulase activity, such that increasing binding affinity is an important component of performance improvement. To ascertain the impact of protein and glycan engineering on CBM binding, we use molecular simulation to quantify cellulose binding of a natively glycosylated Family 1 CBM. To validate our approach, we first examine aromatic-carbohydrate interactions on binding, and our predictions are consistent with previous experiments, showing that a tyrosine to tryptophan mutation yields a 2-fold improvement in binding affinity. We then demonstrate that enhanced binding of 3-6-fold over a nonglycosylated CBM is achieved by the addition of a single, native mannose or a mannose dimer, respectively, which has not been considered previously. Furthermore, we show that the addition of a single, artificial glycan on the anterior of the CBM, with the native, posterior glycans also present, can have a dramatic impact on binding affinity in our model, increasing it up to 140-fold relative to the nonglycosylated CBM. These results suggest new directions in protein engineering, in that modifying glycosylation patterns via heterologous expression, manipulation of culture conditions, or introduction of artificial glycosylation sites, can alter CBM binding affinity to carbohydrates and may thus be a general strategy to enhance cellulase performance. Our results also suggest that CBM binding studies should consider the effects of glycosylation on binding and function.

Examining the phase transition behavior of amphiphilic lipids in solution using statistical temperature molecular dynamics and replica-exchange Wang-Landau methods.

Two different techniques - replica-exchange Wang-Landau (REWL) and statistical temperature molecular dynamics (STMD) - were applied to systematically study the phase transition behavior of self-assembling lipids as a function of temperature using an off-lattice lipid model. Both methods allow the direct calculation of the density of states with improved efficiency compared to the original Wang-Landau method. A 3-segment model of amphiphilic lipids solvated in water has been studied with varied particle interaction energies (ε) and lipid concentrations. The phase behavior of the lipid molecules with respect to bilayer formation has been characterized through the calculation of the heat capacity as a function of temperature, in addition to various order parameters and general visual inspection. The simulations conducted by both methods can go to very low temperatures with the whole system exhibiting well-ordered structures. With optimized parameters, several bilayer phases are observed within the temperature range studied, including gel phase bilayers with frozen water, mixed water (i.e., frozen and liquid water), and liquid water, and a more fluid bilayer with liquid water. The results obtained from both methods, STMD and REWL, are consistently in excellent agreement with each other, thereby validating both the methods and the results.

The skin barrier: An extraordinary interface with an exceptional lipid organization.

The barrier function of the skin is primarily located in the stratum corneum (SC), the outermost layer of the skin. The SC is composed of dead cells with highly organized lipid lamellae in the intercellular space. As the lipid matrix forms the only continuous pathway, the lipids play an important role in the permeation of compounds through the SC. The main lipid classes are ceramides (CERs), cholesterol (CHOL) and free fatty acids (FFAs). Analysis of the SC lipid matrix is of crucial importance in understanding the skin barrier function, not only in healthy skin, but also in inflammatory skin diseases with an impaired skin barrier. In this review we provide i) a historical overview of the steps undertaken to obtain information on the lipid composition and organization in SC of healthy skin and inflammatory skin diseases, ii) information on the role CERs, CHOL and FFAs play in the lipid phase behavior of very complex lipid model systems and how this knowledge can be used to understand the deviation in lipid phase behavior in inflammatory skin diseases, iii) knowledge on the role of both, CER subclasses and chain length distribution, on lipid organization and lipid membrane permeability in complex and simple model systems with synthetic CERs, CHOL and FFAs, iv) similarity in lipid phase behavior in SC of different species and complex model systems, and vi) future directions in modulating lipid composition that is expected to improve the skin barrier in inflammatory skin diseases.