Noble metal-based nanomaterials have shown promise as potential enzyme mimetics, but the facet effect and underlying molecular mechanisms are largely unknown. Herein, with a combined experimental and theoretical approach, we unveil that palladium (Pd) nanocrystals exhibit facet-dependent oxidase and peroxidase-like activities that endow them with excellent antibacterial properties via generation of reactive oxygen species. The antibacterial efficiency of Pd nanocrystals against Gram-positive bacteria is consistent with the extent of their enzyme-like activity, that is {100}-faceted Pd cubes with higher activities kill bacteria more effectively than {111}-faceted Pd octahedrons. Surprisingly, a reverse trend of antibacterial activity is observed against Gram-negative bacteria, with Pd octahedrons displaying stronger penetration into bacterial membranes than Pd nanocubes, thereby exerting higher antibacterial activity than the latter. Our findings provide a deeper understanding of facet-dependent enzyme-like activities and might advance the development of noble metal-based nanomaterials with both enhanced and targeted antibacterial activities.

Vanadium compounds have been primarily investigated as potential therapeutic agents for the treatment of various major health issues, including cancer, atherosclerosis, and diabetes. The translation of vanadium-based compounds into clinical trials and ultimately into disease treatments remains hampered by the absence of a basic pharmacological and metabolic comprehension of such compounds. In this review, we examine the development of vanadium-containing compounds in biological systems regarding the role of the physiological environment, dosage, intracellular interactions, metabolic transformations, modulation of signaling pathways, toxicology, and transport and tissue distribution as well as therapeutic implications. From our point of view, the toxicological and pharmacological aspects in animal models and humans are not understood completely, and thus, we introduced them in a physiological environment and dosage context. Different transport proteins in blood plasma and mechanistic transport determinants are discussed. Furthermore, an overview of different vanadium species and the role of physiological factors (i.e., pH, redox conditions, concentration, and so on) are considered. Mechanistic specifications about different signaling pathways are discussed, particularly the phosphatases and kinases that are modulated dynamically by vanadium compounds because until now, the focus only has been on protein tyrosine phosphatase 1B as a vanadium target. Particular emphasis is laid on the therapeutic ability of vanadium-based compounds and their role for the treatment of diabetes mellitus, specifically on that of vanadate- and polioxovanadate-containing compounds. We aim at shedding light on the prevailing gaps between primary scientific data and information from animal models and human studies.

Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its use in biomedical engineering for biopolymer materials has only recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: (A) Computer-aided design (CAD/CAM) utilizes specialized software to design and model biopolymers for various biomedical applications. This technology allows researchers to create precise three-dimensional models of biopolymers, taking into account their chemical, structural, and functional properties. These models can be used to enhance the structure of biopolymers and improve their effectiveness in specific medical applications. (B) Finite element analysis, a computational technique used to analyze and solve problems in engineering and physics. This approach divides the physical domain into small finite elements with simple geometric shapes. This computational technique enables the study and understanding of the mechanical and structural behavior of biopolymers in biomedical environments. (C) Molecular dynamics (MD) simulations involve using advanced computational techniques to study the behavior of biopolymers at the molecular and atomic levels. These simulations are fundamental for better understanding biological processes at the molecular level. Studying the wide-ranging uses of MD simulations in biopolymers involves examining the structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton’s equations of motion for all-atom systems, producing spatial trajectories for each atom. This provides valuable insights into properties such as water absorption on biopolymer surfaces and interactions with solid surfaces, which are crucial for assessing biomaterials. This review provides a comprehensive overview of the various applications of MD simulations in biopolymers. Additionally, it highlights the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.

Tumor necrosis factor (TNF) receptor 1 (TNFR1) plays a pivotal role in mediating TNF induced downstream signaling and regulating inflammatory response. Recent studies have suggested that TNFR1 activation involves conformational rearrangements of preligand assembled receptor dimers and targeting receptor conformational dynamics is a viable strategy to modulate TNFR1 signaling. Here, we used a combination of biophysical, biochemical, and cellular assays, as well as molecular dynamics simulation to show that an anti-inflammatory peptide (FKCRRWQWRMKK), which we termed FKC, inhibits TNFR1 activation allosterically by altering the conformational states of the receptor dimer without blocking receptor–ligand interaction or disrupting receptor dimerization. We also demonstrated the efficacy of FKC by showing that the peptide inhibits TNFR1 signaling in HEK293 cells and attenuates inflammation in mice with intraperitoneal TNF injection. Mechanistically, we found that FKC binds to TNFR1 cysteine-rich domains (CRD2/3) and perturbs the conformational dynamics required for receptor activation. Importantly, FKC increases the frequency in the opening of both CRD2/3 and CRD4 in the receptor dimer, as well as induces a conformational opening in the cytosolic regions of the receptor. This results in an inhibitory conformational state that impedes the recruitment of downstream signaling molecules. Together, these data provide evidence on the feasibility of targeting TNFR1 conformationally active region and open new avenues for receptor-specific inhibition of TNFR1 signaling.