Computer-aided nanodrug discovery: recent progress and future prospects

Nanodrugs, which utilise nanomaterials in disease prevention and therapy, have attracted considerable interest since their initial conceptualisation in the 1990s. Substantial efforts have been made to develop nanodrugs for overcoming the limitations of conventional drugs, such as low targeting efficacy, high dosage and toxicity, and potential drug resistance. Despite the significant progress that has been made in nanodrug discovery, the precise design or screening of nanomaterials with desired biomedical functions prior to experimentation remains a significant challenge. This is particularly the case with regard to personalised precision nanodrugs, which require the simultaneous optimisation of the structures, compositions, and surface functionalities of nanodrugs. The development of powerful computer clusters and algorithms has made it possible to overcome this challenge through in silico methods, which provide a comprehensive understanding of the medical functions of nanodrugs in relation to their physicochemical properties. In addition, machine learning techniques have been widely employed in nanodrug research, significantly accelerating the understanding of bio-nano interactions and the development of nanodrugs. This review will present a summary of the computational advances in nanodrug discovery, focusing on the understanding of how the key interfacial interactions, namely, surface adsorption, supramolecular recognition, surface catalysis, and chemical conversion, affect the therapeutic efficacy of nanodrugs. Furthermore, this review will discuss the challenges and opportunities in computer-aided nanodrug discovery, with particular emphasis on the integrated "computation + machine learning + experimentation" strategy that can potentially accelerate the discovery of precision nanodrugs.

Unravelling pH/pKa influence on pH-responsive drug carriers: Insights from ibuprofen-silica interactions and comparative analysis with carbon nanotubes, sulfasalazine, and alendronate

This study employs density functional theory to explore the interaction between ibuprofen (IBU) and silica, emphasizing the influence of the trimethylsilyl (TMS) functional group for designing pH-responsive drug carriers. The surface (S) and drug (D) molecules' neutral (0) or deprotonated (-1) states were taken into consideration during the investigation. The likelihood of these states was determined based on the pKa values and the desired pH conditions. To calculate the pH-dependent interaction energy (EintpH), four different situations have been identified: S0D0, S0D-1, S-1D0, and S-1D-1.The electrostatic component of interaction energy aligns favorably with its theoretical value in both the Debye-Hückel and Grahame models. The investigation has gathered first-hand experimental data on the drug loading and release of pH-responsive mesoporous silica nanoparticles. Effective drug loading was observed in the acidic environment of the stomach (pH 2-5), followed by a release in the slightly basic to neutral pH of the small intestine (pH 7.4), These findings align with existing literature. The results revealed horizontal drug adherence on silica surfaces, improving binding capabilities. Comparisons were made with combinations involving carboxylated carbon nanotubes and ibuprofen, silica, and sulfasalazine, and silica and alendronate, exploring drug loading/release dynamics associated with positive/negative interaction energies. The investigation, supported by experimental data, contributes valuable insights into pH-responsive mesoporous silica nanoparticles, offering new design possibilities for drug carriers.

Theoretical insights and implications of pH-dependent drug delivery systems using silica and carbon nanotube

In this paper we have studied the density functional theory of four drugs ibuprofen, alendronate, Sulfasalazine and paracetamol with quartz, propylamine, trimethylamine functionalized quartz and carboxyl modified carbon nanotube. The attractive and repulsive interaction energies between drugs and quartz is obtained at various pH values. The attractive and repulsive energies are well correlated with experimental drug loading and releasing behavior by mesoporous silica nanoparticles. Further, a theoretical model is developed that accounts the electrostatic interaction between silica and drug and the model can predict the drug loading and releasing behavior by silica nanoparticles at various pH values. Sulfasalazine can be taken orally and loaded with trimethyl ammonium functionalized mesoporous silica nanoparticles, which keeps the drug in tact with the carrier in the acidic environment of the stomach and releases it into the neutral or basic medium of the small intestine. Alendronate may be loaded and released from propylamine functionalized mesoporous silica nanoparticles in the ranges of 1-5 and > 8, respectively. Ibuprofen is absorbed in an acidic environment and released in basic conditions for carboxyl modified carbon nanotube. The loading and releasing pH ranges for paracetamol in trimethylammonium functionalized mesoporous silica nanoparticles are 4-8 and >8, respectively. We also convert the pH-dependent variant of the diffusion-controlled Higuchi equation. We have changed the original Higuchi equation to produce the pH-dependent variation by incorporating the Nernst-Planck equation into Flick's first law. The updated equation could be used to forecast when medication particles with varying release times will emerge from a nanoparticles matrix.

Effects of the Goethite Surface Hydration Microstructure on the Adsorption of the Collectors Dodecylamine and Sodium Oleate

Dodecylamine (DDA) and sodium oleate (OL) are commonly used collectors in the reverse flotation and the direct flotation of goethite. However, the flotation mechanisms of DDA and OL on the goethite surface remain unclear. In this study, the first-principles density functional theory calculations were used to reveal the role of the hydration of the goethite surface and its effects on flotation reagents from a microscopic perspective. The calculation results showed that DDA was adsorbed on the surface of goethite by hydrogen bonds in the absence of hydration. However, the existence of the hydration microstructure hindered the formation of hydrogen bonds and made it difficult for DDA to be adsorbed on the goethite surface. In the OL system, oleate ions are chemically adsorbed on the surface Fe sites of goethite in the absence of hydration, while in the presence of hydration, the oleate ions were adsorbed on the H-terminal hydration surface of goethite by hydrogen bonds. This work sheds new light on the roles of the hydration microstructure and the adsorption mechanism of the flotation reagent on the oxide minerals.