Molecular Dynamics Simulations of a Catalytic Multivalent Peptide-Nanoparticle Complex

Transition-Metal-Oxide-Based Nanozymes for Antitumor Applications

Transition metal oxide (TMO)-based nanozymes have appeared as hopeful tools for antitumor applications due to their unique catalytic properties and ability to modulate the tumor microenvironment (TME). The purpose of this review is to provide an overview of the latest progress made in the field of TMO-based nanozymes, focusing on their enzymatic activities and participating metal ions. These nanozymes exhibit catalase (CAT)-, peroxidase (POD)-, superoxide dismutase (SOD)-, oxidase (OXD)-, and glutathione oxidase (GSH-OXD)-like activities, enabling them to regulate reactive oxygen species (ROS) levels and glutathione (GSH) concentrations within the TME. Widely studied transition metals in TMO-based nanozymes include Fe, Mn, Cu, Ce, and the hybrid multimetallic oxides, which are also summarized. The review highlights several innovative nanozyme designs and their multifunctional capabilities. Despite the significant progress in TMO-based nanozymes, challenges such as long-term biosafety, targeting precision, catalytic mechanisms, and theoretical supports remain to be addressed, and these are also discussed. This review contributes to the summary and understanding of the rapid development of TMO-based nanozymes, which holds great promise for advancing nanomedicine and improving cancer treatment.

The effect of ligands on the size distribution of copper nanoclusters: Insights from molecular dynamics simulations

Controlling the size distribution in the nucleation of copper particles is crucial for achieving nanocrystals with desired physical and chemical properties. However, their synthesis involves a complex system of solvents, ligands, and copper precursors with intertwining effects on the size of the nanoclusters. We combine molecular dynamics simulations and density functional theory calculations to provide insights into the nucleation mechanism in the presence of a triphenyl phosphite ligand. We identify the crucial role of the strength of the metal-phosphine interaction in inhibiting the cluster's growth. We demonstrate computationally several practical routes to fine-tune the interaction strength by modifying the side groups of the additive. Our work provides molecular insights into the complex nucleation process of protected copper nanocrystals, which can assist in controlling their size distribution and, eventually, their morphology.

Deconstructing Electrostatics of Functionalized Metal Nanoparticles from Molecular Dynamics Simulations

Gold nanoparticles (NPs) with different surface functionalizations can selectively interact with specific proteins, allowing a wide range of possible applications in biotechnology and biomedicine. To prevent their tendency to aggregate and to modulate their interaction with charged biomolecules or substrates (e.g., for biosensing applications), they can be functionalized with charged groups, introducing a mutual interaction which can be modulated by changing the ionic strength of the solvent. In silico modeling of these systems is often addressed with low-resolution models, which must account for these effects in the, often implicit, solvent representation. Here, we present a systematic conformational dynamic characterization of ligand-coated gold nanoparticles with different sizes, charges, and functionalizations by means of atomistic molecular dynamics simulations. Based on these, we deconstruct their electrostatic properties and propose a general representation of their average-long-range interactions extendable to different sizes, charges, and ionic strengths. This study clarifies in detail the role of the different features of the NP (charge, size, structure) and of the ionic strength in determining the details of the interparticle interaction and represents the first step toward a general strategy for the parametrization of NP coarse-grained models able to account for varying ionic strengths.

Application of Molecular Dynamics Simulations to Determine Interactions between Canary Seed (Phalaris canariensis L.) Bioactive Peptides and Skin-Aging Enzymes

Food bioactive peptides are well recognized for their health benefits such as antimicrobial, antioxidant, and antihypertensive benefits, among others. Their drug-like behavior has led to their potential use in targeting skin-related aging factors like the inhibition of enzymes related with the skin-aging process. In this study, canary seed peptides (CSP) after simulated gastrointestinal digestion (<3 kDa) were fractioned by RP-HPLC and their enzyme-inhibition activity towards elastase and tyrosinase was evaluated in vitro. CSP inhibited elastase (IC50 = 6.2 mg/mL) and tyrosinase (IC50 = 6.1 mg/mL), while the hydrophobic fraction-VI (0.2 mg/mL) showed the highest inhibition towards elastase (93%) and tyrosinase (67%). The peptide fraction with the highest inhibition was further characterized by a multilevel in silico workflow, including physicochemical descriptor calculations, antioxidant activity predictions, and molecular dynamics-ensemble docking towards elastase and tyrosinase. To gain insights into the skin permeation process during molecular dynamics simulations, based on their docking scores, five peptides (GGWH, VPPH, EGLEPNHRVE, FLPH, and RPVNKYTPPQ) were identified to have favorable intermolecular interactions, such as hydrogen bonding of polar residues (W, H, and K) to lipid polar groups and 2-3 Å van der Waals close contact of hydrophobic aliphatic residues (P, V, and L). These interactions can play a critical role for the passive insertion of peptides into stratum corneum model skin-membranes, suggesting a promising application of CSP for skin-aging treatments.

Understanding Molecular Aggregation of Ligand-Protected Atomically-Precise Metal Nanoclusters

Monolayer-protected atomically precise nanoclusters (MPCs) are an important class of molecules due to their unique structural features and diverse applications, including bioimaging, sensors, and drug carriers. Understanding the atomistic and dynamical details of their self-assembly process is crucial for designing system-specific applications. Here, we applied molecular dynamics and on-the-fly probability-based enhanced sampling simulations to study the aggregation of Au₂₅(pMBA)₁₈ MPCs in aqueous and methanol solutions. The MPCs interact via both hydrogen bonds and π-stacks between the aromatic ligands to form stable dimers, oligomers, and crystals. The dimerization free energy profiles reveal a pivotal role of the ligand charged state and solvent mediating the molecular aggregation. Furthermore, MPCs' ligands exhibit suppressed conformational flexibility in the solid phase due to facile intercluster hydrogen bonds and π-stacks. Our work provides unprecedented molecular-level dynamical details of the aggregation process and conformational dynamics of MPCs ligands in solution and crystalline phases.

The Conformational Dynamics of the Ligands Determines the Electronic Circular Dichroism of the Chiral Au38(SC2H4Ph)24 Cluster

Effects of the conformational dynamics of 2-PET protective ligands on the electronic circular dichroism (ECD) of the chiral Au₃₈(SC₂H₄Ph)₂₄ cluster are investigated. We adopt a computational protocol in which ECD spectra are calculated via the first principle polTDDFT approach on a series of conformations extracted from MD simulations by using Essential Dynamics (ED) analysis, and then properly weighted to predict the final spectrum. We find that the experimental spectral features are well reproduced, whereas significant discrepancies arise when the spectrum is calculated using the experimental X-ray structure. This result unambiguously demonstrates the need to account for the conformational effects in the ECD modeling of chiral nanoclusters. The present procedure proved to be able of capturing the essential conformational features of the dynamic Au₃₈(SC₂H₄Ph)₂₄ system, opening the possibility to model the ECD of soluble chiral nanoclusters in a realistic way.

Role of Ionic Strength in the Formation of Stable Supramolecular Nanoparticle-Protein Conjugates for Biosensing

Monolayer-protected gold nanoparticles (AuNPs) exhibit distinct physical and chemical properties depending on the nature of the ligand chemistry. A commonly employed NP monolayer comprises hydrophobic molecules linked to a shell of PEG and terminated with functional end group, which can be charged or neutral. Different layers of the ligand shell can also interact in different manners with proteins, expanding the range of possible applications of these inorganic nanoparticles. AuNP-fluorescent Green Fluorescent Protein (GFP) conjugates are gaining increasing attention in sensing applications. Experimentally, their stability is observed to be maintained at low ionic strength conditions, but not at physiologically relevant conditions of higher ionic strength, limiting their applications in the field of biosensors. While a significant amount of fundamental work has been done to quantify electrostatic interactions of colloidal nanoparticle at the nanoscale, a theoretical description of the ion distribution around AuNPs still remains relatively unexplored. We perform extensive atomistic simulations of two oppositely charged monolayer-protected AuNPs interacting with fluorescent supercharged GFPs co-engineered to have complementary charges. These simulations were run at different ionic strengths to disclose the role of the ionic environment on AuNP–GFP binding. The results highlight the capability of both AuNPs to intercalate ions and water molecules within the gold–sulfur inner shell and the different tendency of ligands to bend inward allowing the protein to bind not only with the terminal ligands but also the hydrophobic alkyl chains. Different binding stability is observed in the two investigated cases as a function of the ligand chemistry.

Molecular Recognition by Gold Nanoparticle-Based Receptors as Defined through Surface Morphology and Pockets Fingerprint

Ligand shell-protected gold nanoparticles can form nanoreceptors that recognize and bind to specific molecules in solution, with numerous potential innovative applications in science and industry. At this stage, the challenge is to rationally design such nanoreceptors to optimize their performance and boost their further development. Toward this aim, we have developed a new computational tool, Nanotron. This allows the analysis of molecular dynamics simulations of ligand shell-protected nanoparticles to define their exact surface morphology and pocket fingerprints of binding cavities in the coating monolayer. Importantly, from dissecting the well-characterized pairing formed by the guest salicylate molecule and specific host nanoreceptors, our work reveals that guest binding at such nanoreceptors occurs via preformed deep pockets in the host. Upon the interaction with the guest, such pockets undergo an induced-fit-like structural optimization for best host-guest fitting. Our findings and methodological advancement will accelerate the rational design of new-generation nanoreceptors.