Molecular dynamics simulation of drug delivery across the cell membrane by applying gold nanoparticle carrier: Flutamide as hydrophobic and glutathione as hydrophilic drugs as the case studies

In silico description of the adsorption of cell signaling pathway proteins ovalbumin, glutathione, LC3, TLR4, ASC PYCARD, PI3K and NF-Kβ on 7.0 nm gold nanoparticles: obtaining their Lennard-Jones-like potentials through docking and molecular mechanics

The impact of vaccination on the world's population is difficult to calculate. For developing different types of vaccines, adjuvants are substances added to vaccines to increase the magnitude and durability of the immune response and the effectiveness of the vaccine. This work explores the potential use of spherical gold nanoparticles (AuNPs) as adjuvants. Thus, we employed docking techniques and molecular mechanics to describe how a AuNP 7.0 nm in diameter interacts with cell signaling pathway proteins. Initially, we used X-ray crystallization data of the proteins ovalbumin, glutathione, LC3, TLR4, ASC PYCARD, PI3K, and NF-Kβ to study the adsorption with an AuNP through molecular docking. Therefore, interaction energies were obtained for the AuNP complexes and individual proteins, as well as the AuNP and OVA complex (AuNP@OVA) with each cellular protein, respectively. Results showed that AuNPs had the highest affinity for OVA individually, followed by glutathione, ASC PYCARD domain, LC3, PI3K, NF-Kβ, and TLR4. Furthermore, when evaluating the AuNP@OVA complex, glutathione showed a greater affinity with more potent interaction energy when compared to the other studied systems.

Investigation of the effects of porosity and volume fraction on the atomic behavior of cancer cells and microvascular cells of 3DN5 and 5OTF macromolecular structures during hematogenous metastasis using the molecular dynamics method

BACKGROUND AND OBJECTIVE

The molecular dynamics (MD) simulation is a powerful tool for researching how cancer patients are treated. The efficiency of many factors may be predicted using this approach in great detail and with atomic accuracy.

METHODS

The MD simulation method was used to investigate the impact of porosity and the number of cancer cells on the atomic behavior of cancer cells during the hematogenous spread. In order to examine the stability of simulated structures, temperature and potential energy (PE) values are used. To evaluate how cell structure has changed, physical parameters such as gyration radius, interaction force, and interaction energy are also used.

RESULTS

The findings demonstrate that the samples' gyration radius, interaction energy, and interaction force rose from 41.33 Å, -551.38 kcal/mol, and -207.10 kcal/mol Å to 49.49, -535.94 kcal/mol, and -190.05 kcal/mol Å, respectively, when the porosity grew from 0% to 5%. Also, the interaction energy and force in the samples fell from -551.38 kcal/mol and -207.10 kcal/mol to -588.03 kcal/mol and -237.81 kcal/mol Å, and the amount of gyration radius reduced from 41.33 to 37.14 Å as the number of cancer cells rose from 1 to 5 molecules. The strength and stability of the simulated samples will improve when the radius of gyration is decreased.

CONCLUSIONS

Therefore, high accumulation of cancer cells will make them resistant to atomic collapse. It is expected that the results of this simulation should be used to optimize cancer treatment processes further.

How can machine learning and multiscale modeling benefit ocular drug development?

The eyes possess sophisticated physiological structures, diverse disease targets, limited drug delivery space, distinctive barriers, and complicated biomechanical processes, requiring a more in-depth understanding of the interactions between drug delivery systems and biological systems for ocular formulation development. However, the tiny size of the eyes makes sampling difficult and invasive studies costly and ethically constrained. Developing ocular formulations following conventional trial-and-error formulation and manufacturing process screening procedures is inefficient. Along with the popularity of computational pharmaceutics, non-invasive in silico modeling & simulation offer new opportunities for the paradigm shift of ocular formulation development. The current work first systematically reviews the theoretical underpinnings, advanced applications, and unique advantages of data-driven machine learning and multiscale simulation approaches represented by molecular simulation, mathematical modeling, and pharmacokinetic (PK)/pharmacodynamic (PD) modeling for ocular drug development. Following this, a new computer-driven framework for rational pharmaceutical formulation design is proposed, inspired by the potential of in silico explorations in understanding drug delivery details and facilitating drug formulation design. Lastly, to promote the paradigm shift, integrated in silico methodologies were highlighted, and discussions on data challenges, model practicality, personalized modeling, regulatory science, interdisciplinary collaboration, and talent training were conducted in detail with a view to achieving more efficient objective-oriented pharmaceutical formulation design.

Current Trends and Changes in Use of Membrane Molecular Dynamics Simulations within Academia and the Pharmaceutical Industry

There has been an almost exponential increase in the use of molecular dynamics simulations in basic research and industry over the last 5 years, with almost a doubling in the number of publications each year. Many of these are focused on neurological membranes, and biological membranes in general, applied to the medical industry. A smaller portion have utilized membrane simulations to answer more basic questions related to the function of specific proteins, chemicals or biological processes. This review covers some newer studies, alongside studies from the last two decades, to determine changes in the field. Some of these are basic, while others are more profound, such as multi-component embedded membrane machinery. It is clear that many facets of the discipline remain the same, while the focus on and uses of the technology are broadening in scope and utilization as a general research tool. Analysis of recent literature provides an overview of the current methodologies, covers some of the recent trends or advances and tries to make predictions of the overall path membrane molecular dynamics will follow in the coming years. In general, the overview presented is geared towards the general scientific community, who may wish to introduce the use of these methodologies in light of these changes, making molecular dynamic simulations more feasible for general scientific or medical research.