Carbohydrate-derived amphiphilic macromolecules: a biophysical structural characterization and analysis of binding behaviors to model membranes.

The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials

Accurate predictions of cellular response using QSPR: a feasibility test of rational design of polymeric biomaterials

Abstract We present a Surrogate (semi-empirical) model for prediction of cellular response to the surfaces of biodegradable polymers that have been designed for tissue engineering applications. The predictions of our model, when tested against experimental results, show a high degree of accuracy that is sufficient for rational design of polymeric materials for biomedical applications. The model was determined by fitting experimental data for a series of 62 polyarylates to a small number of polymer structure-based 'molecular descriptors' using the technique of partial least squares (PLS) regression. While PLS is commonly applied in quantitative structure activity relationship (QSAR) analysis employed in the pharmaceutical industry, this study marks the first time the technique has been extended to the problem of biomaterials discovery/design. Quantitative predictions of cellular response to six polymers (untested prior to model building) concurred with experiment within 15.8% on average. This performance compares quite favorably with the overall variation in experimental values for the library of polyarylates. Examination of the PLS 'loadings' reveals those structure-based features most associated with variations in the polymer performance properties, thereby providing direct guidance to the synthetic chemist in biomaterials design.

Accurate predictions of cellular response using QSPR: a feasibility test of rational design of polymeric biomaterials

Abstract We present a Surrogate (semi-empirical) model for prediction of cellular response to the surfaces of biodegradable polymers that have been designed for tissue engineering applications. The predictions of our model, when tested against experimental results, show a high degree of accuracy that is sufficient for rational design of polymeric materials for biomedical applications. The model was determined by fitting experimental data for a series of 62 polyarylates to a small number of polymer structure-based 'molecular descriptors' using the technique of partial least squares (PLS) regression. While PLS is commonly applied in quantitative structure activity relationship (QSAR) analysis employed in the pharmaceutical industry, this study marks the first time the technique has been extended to the problem of biomaterials discovery/design. Quantitative predictions of cellular response to six polymers (untested prior to model building) concurred with experiment within 15.8% on average. This performance compares quite favorably with the overall variation in experimental values for the library of polyarylates. Examination of the PLS 'loadings' reveals those structure-based features most associated with variations in the polymer performance properties, thereby providing direct guidance to the synthetic chemist in biomaterials design.

Highly chlorinated PCBs inhibit the human xenobiotic response mediated by the steroid and xenobiotic receptor (SXR).

Polychlorinated biphenyls (PCBs) are a family of persistent organic contaminants suspected to cause adverse effects in wildlife and humans. In rodents, PCBs bind to the aryl hydrocarbon (AhR) and pregnane X receptors (PXR) inducing the expression of catabolic cytochrome p450 enzymes of the CYP1A and 3A families. We found that certain highly chlorinated PCBs are potent activators of rodent PXR but antagonize its human ortholog, the steroid and xenobiotic receptor (SXR), inhibiting target gene induction. Thus, exposure to PCBs may blunt the human xenobiotic response, inhibiting the detoxification of steroids, bioactive dietary compounds, and xenobiotics normally mediated by SXR. The antagonistic PCBs are among the most stable and abundant in human tissues. These findings have important implications for understanding the biologic effects of PCB exposure and the use of animal models to predict the attendant risk

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu

Requirement of Gamma-Carboxyglutamic Acid Modification and Phosphatidylserine Binding for the Activation of Tyro3, Axl, and Mertk Receptors by Growth Arrest-Specific 6

The Tyro3, Axl, and Mertk (TAM) receptors are homologous type I receptor tyrosine kinases that have critical functions in the clearance of apoptotic cells in multicellular organisms. TAMs are activated by their endogenous ligands, growth arrest-specific 6 (Gas6), and protein S (Pros1), that function as bridging molecules between externalized phosphatidylserine (PS) on apoptotic cells and the TAM ectodomains. However, the molecular mechanisms by which Gas6/Pros1 promote TAM activation remains elusive. Using TAM/IFNγR1 reporter cell lines to monitor functional TAM activity, we found that Gas6 activity was exquisitely dependent on vitamin K-mediated γ-carboxylation, whereby replacing vitamin K with anticoagulant warfarin, or by substituting glutamic acid residues involved in PS binding, completely abrogated Gas6 activity as a TAM ligand. Furthermore, using domain and point mutagenesis, Gas6 activity also required both an intact Gla domain and intact EGF-like domains, suggesting these domains function cooperatively in order to achieve TAM activation. Despite the requirement of γ-carboxylation and the functional Gla domain, non-γ-carboxylated Gas6 and Gla deletion/EGF-like domain deletion mutants still retained their ability to bind TAMs and acted as blocking decoy ligands. Finally, we found that distinct sources of PS-positive cells/vesicles (including apoptotic cells, calcium-induced stressed cells, and exosomes) bound Gas6 and acted as cell-derived or exosome-derived ligands to activate TAMs. Taken together, our findings indicate that PS is indispensable for TAM activation by Gas6, and by inference, provides new perspectives on how PS, regulates TAM receptors and efferocytosis

Self-assembled cationic amphiphiles as antimicrobial peptides mimics: Role of hydrophobicity, linkage type, and assembly state

Inspired by high promise using naturally occurring antimicrobial peptides (AMPs) to treat infections caused by antimicrobial-resistant bacteria, cationic amphiphiles (CAms) were strategically designed as synthetic mimics to overcome associated limitations, including high manufacture cost and low metabolic stability. CAms with facially amphiphilic conformation were expected to demonstrate membrane-lytic properties and thus reduce tendency of resistance development. By systematically tuning the hydrophobicity, CAms with optimized compositions exhibited potent broad-spectrum antimicrobial activity (with minimum inhibitory concentrations in low μg/mL range) as well as negligible hemolytic activity. Electron microscope images revealed the morphological and ultrastructure changes of bacterial membranes induced by CAm treatment and validated their membrane-disrupting mechanism. Additionally, an all-atom molecular dynamics simulation was employed to understand the CAm-membrane interaction on molecular level. This study shows that these CAms can serve as viable scaffolds for designing next generation of AMP mimics as antimicrobial alternatives to combat drug-resistant pathogens