The effect of chitosan and PEG polymers on stabilization of GF-17 structure: A molecular dynamics study

Therapeutic Peptides Are Preferentially Solubilized in Specific Microenvironments within PEG-PLGA Polymer Nanoparticles

Polymeric nanoparticles are a highly promising drug delivery formulation. However, a lack of understanding of the molecular mechanisms that underlie their drug solubilization and controlled release capabilities has hindered the efficient clinical translation of such technologies. Polyethylene glycol-poly(lactic-co-glycolic) acid (PEG-PLGA) nanoparticles have been widely studied as cancer drug delivery vehicles. In this letter, we use unbiased coarse-grained molecular dynamics simulations to model the self-assembly of a PEG-PLGA nanoparticle and its solubulization of the anticancer peptide, EEK, with good agreement with previously reported experimental structural data. We applied unsupervised machine learning techniques to quantify the conformations that polymers adopt at various locations within the nanoparticle. We find that the local microenvironments formed by the various polymer conformations promote preferential EEK solubilization within specific regions of the NP. This demonstrates that these microenvironments are key in controlling drug storage locations within nanoparticles, supporting the rational design of nanoparticles for therapeutic applications.

Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities

The covalent modification of proteins with polymers is a well-established method for improving the pharmacokinetic properties of therapeutically valuable biologics. The conjugated polymer chains of the resulting hybrid represent highly flexible macromolecular structures. As the dynamics of such systems remain rather elusive for established experimental techniques from the field of protein structure elucidation, molecular dynamics simulations have proven as a valuable tool for studying such conjugates at an atomistic level, thereby complementing experimental studies. With a focus on new developments, this review aims to provide researchers from the polymer bioconjugation field with a concise and up to date overview of such approaches. After introducing basic principles of molecular dynamics simulations, as well as methods for and potential pitfalls in modeling bioconjugates, the review illustrates how these computational techniques have contributed to the understanding of bioconjugates and bioconjugation strategies in the recent past and how they may lead to a more rational design of novel bioconjugates in the future.

Water-responsive supercontractile polymer films for bioelectronic interfaces

Connecting different electronic devices is usually straightforward because they have paired, standardized interfaces, in which the shapes and sizes match each other perfectly. Tissue-electronics interfaces, however, cannot be standardized, because tissues are soft1-3 and have arbitrary shapes and sizes4-6. Shape-adaptive wrapping and covering around irregularly sized and shaped objects have been achieved using heat-shrink films because they can contract largely and rapidly when heated7. However, these materials are unsuitable for biological applications because they are usually much harder than tissues and contract at temperatures higher than 90 °C (refs. 8,9). Therefore, it is challenging to prepare stimuli-responsive films with large and rapid contractions for which the stimuli and mechanical properties are compatible with vulnerable tissues and electronic integration processes. Here, inspired by spider silk10-12, we designed water-responsive supercontractile polymer films composed of poly(ethylene oxide) and poly(ethylene glycol)-α-cyclodextrin inclusion complex, which are initially dry, flexible and stable under ambient conditions, contract by more than 50% of their original length within seconds (about 30% per second) after wetting and become soft (about 100 kPa) and stretchable (around 600%) hydrogel thin films thereafter. This supercontraction is attributed to the aligned microporous hierarchical structures of the films, which also facilitate electronic integration. We used this film to fabricate shape-adaptive electrode arrays that simplify the implantation procedure through supercontraction and conformally wrap around nerves, muscles and hearts of different sizes when wetted for in vivo nerve stimulation and electrophysiological signal recording. This study demonstrates that this water-responsive material can play an important part in shaping the next-generation tissue-electronics interfaces as well as broadening the biomedical application of shape-adaptive materials.

Drug cross-linking electrospun fiber for effective infected wound healing

The management of infected wounds is still an intractable challenge in clinic. Development of antibacterial wound dressing is of great practical significance for wound management. Herein, a natural-derived antibacterial drug, tannic acid (TA), was incorporated into the electrospun polyvinyl alcohol (PVA) fiber (TA/PVA fiber, 952 ± 40 nm in diameter). TA worked as a cross-linker via hydrogen bonding with PVA to improve the physicochemical properties of the fiber and to reach a sustained drug release (88% release of drug at 48 h). Improved mechanical property (0.8-1.2 MPa) and computational simulation validated the formation of the hydrogen bonds between TA and PVA. Moreover, the antibacterial and anti-inflammatory characteristics of TA laid the foundation for the application of TA/PVA fiber in repairing infected wounds. Meanwhile, in vitro studies proved the high hemocompatibility and cytocompatibility of TA/PVA fiber. Further in vivo animal investigation showed that the TA/PVA fiber promoted the repair of infected wound by inhibiting the bacterial growth, promoting granulation formation, and collagen matrix deposition, accelerating angiogenesis, and inducing M2 macrophage polarization within 14 days. All the data demonstrated that the TA cross-linked fiber would be a potent dressing for bacteria-infected wound healing.

A Bayesian approach to estimate the diffusion coefficient of Rhodamine 6G in breast cancer spheroids

Multicellular spheroids have emerged as a robust platform to model tumor growth and are widely used for studying drug sensitivity. Diffusion is the main mechanism for transporting nutrients and chemotherapeutic drugs into spheroids, since they are typically avascular. In this study, the Bayesian inference was used to solve the inverse problem of determining the light attenuation coefficient and diffusion coefficient of Rhodamine 6G (R6G) in breast cancer spheroids, as a mock drug for the tyrosine kinase inhibitor, Neratinib. Four types of breast cancer spheroids were formed and the diffusion coefficient was estimated assuming a linear relationship between the intensity and concentration. The mathematical model used for prediction is the solution to the diffusion problem in spherical coordinates, accounting for the light attenuation. The Gaussian likelihood was used to account for the error between the measurements and model predictions. The Markov Chain Monte Carlo algorithm (MCMC) was used to sample from the posterior. The posterior predictions for the diffusion and light attenuation coefficients were provided. The results indicate that the diffusion coefficient values do not significantly vary across a HER2+ breast cancer cell line as a function of transglutaminase 2 levels, even in the presence of fibroblast cells. However, we demonstrate that different diffusion coefficient values can be ascertained from tumorigenic compared to nontumorigenic spheroids and from nonmetastatic compared to post-metastatic breast cancer cells using this approach. We also report agreement between spheroid radius, attenuation coefficient, and subsequent diffusion coefficient to give evidence of cell packing in self-assembled spheroids. The methodology presented here will allow researchers to determine diffusion in spheroids to decouple transport and drug penetration changes from biological resistivity.

Atomic Scale Interactions between RNA and DNA Aptamers with the TNF-α Protein

Interest in the design and manufacture of RNA and DNA aptamers as apta-biosensors for the early diagnosis of blood infections and other inflammatory conditions has increased considerably in recent years. The practical utility of these aptamers depends on the detailed knowledge about the putative interactions with their target proteins. Therefore, understanding the aptamer-protein interactions at the atomic scale can offer significant insights into the optimal apta-biosensor design. In this study, we consider one RNA and one DNA aptamer that were previously used as apta-biosensors for detecting the infection biomarker protein TNF-α, as an example of a novel computational workflow for selecting the aptamer candidate with the highest binding strength to a target. We combine information from the binding free energy calculations, molecular docking, and molecular dynamics simulations to investigate the interactions of both aptamers with TNF-α. The results reveal that the RNA aptamer has a more stable structure relative to the DNA aptamer. Interaction of aptamers with TNF-α does not have any negative effect on its structure. The results of molecular docking and molecular dynamics simulations suggest that the RNA aptamer has a stronger interaction with the protein. Also, these findings illustrate that basic residues of TNF-α establish more atomic contacts with the aptamers compared to acidic or pH-neutral ones. Furthermore, binding energy calculations show that the interaction of the RNA aptamer with TNF-α is thermodynamically more favorable. In total, the findings of this study indicate that the RNA aptamer is a more suitable candidate for using as an apta-biosensor of TNF-α and, therefore, of greater potential use for the diagnosis of blood infections. Also, this study provides more information about aptamer-protein interactions and increases our understanding of this phenomenon.

Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery

In this review, we outline the growing role that molecular dynamics simulation is able to play as a design tool in drug delivery. We cover both the pharmaceutical and computational backgrounds, in a pedagogical fashion, as this review is designed to be equally accessible to pharmaceutical researchers interested in what this new computational tool is capable of and experts in molecular modeling who wish to pursue pharmaceutical applications as a context for their research. The field has become too broad for us to concisely describe all work that has been carried out; many comprehensive reviews on subtopics of this area are cited. We discuss the insight molecular dynamics modeling has provided in dissolution and solubility, however, the majority of the discussion is focused on nanomedicine: the development of nanoscale drug delivery vehicles. Here we focus on three areas where molecular dynamics modeling has had a particularly strong impact: (1) behavior in the bloodstream and protective polymer corona, (2) Drug loading and controlled release, and (3) Nanoparticle interaction with both model and biological membranes. We conclude with some thoughts on the role that molecular dynamics simulation can grow to play in the development of new drug delivery systems.

Molecular Simulations of PEGylated Biomolecules, Liposomes, and Nanoparticles for Drug Delivery Applications

Since the first polyethylene glycol (PEG)ylated protein was approved by the FDA in 1990, PEGylation has been successfully applied to develop drug delivery systems through experiments, but these experimental results are not always easy to interpret at the atomic level because of the limited resolution of experimental techniques. To determine the optimal size, structure, and density of PEG for drug delivery, the structure and dynamics of PEGylated drug carriers need to be understood close to the atomic scale, as can be done using molecular dynamics simulations, assuming that these simulations can be validated by successful comparisons to experiments. Starting with the development of all-atom and coarse-grained PEG models in 1990s, PEGylated drug carriers have been widely simulated. In particular, recent advances in computer performance and simulation methodologies have allowed for molecular simulations of large complexes of PEGylated drug carriers interacting with other molecules such as anticancer drugs, plasma proteins, membranes, and receptors, which makes it possible to interpret experimental observations at a nearly atomistic resolution, as well as help in the rational design of drug delivery systems for applications in nanomedicine. Here, simulation studies on the following PEGylated drug topics will be reviewed: proteins and peptides, liposomes, and nanoparticles such as dendrimers and carbon nanotubes.