Designing antibacterial materials through simulation and theory

Antibacterial materials have a wide range of potential applications in bio-antimicrobial, environmental antimicrobial, and food antimicrobial fields due to their intrinsic antimicrobial properties, which can circumvent the development of drug resistance in bacteria. Understanding the intricate mechanisms and intrinsic nature of diverse antibacterial materials is significant for the formulation of guidelines for the design of materials with rapid and efficacious antimicrobial action and a high degree of biomedical material safety. Herein, this review highlights the recent advances in investigating antimicrobial mechanisms of different antibacterial materials with a particular focus on tailored computer simulations and theoretical analysis. From the view of structure and function, we summarize the characteristics and mechanisms of different antibacterial materials, introduce the latest advances of new antibacterial materials, and discuss the design concept and development direction of new materials. In addition, we underscore the significance of employing simulation and theoretical methodologies to elucidate the intrinsic antimicrobial mechanisms, which is crucial for a comprehensive comprehension of the control strategies, safer biomedical applications, and the management of health and environmental concerns associated with antibacterial materials. This review could potentially stimulate further endeavors in fundamental research and facilitate the extensive utilization of computational and theoretical approaches in the design of novel functional nanomaterials.

2D Nanomaterials and Their Drug Conjugates for Phototherapy and Magnetic Hyperthermia Therapy of Cancer and Infections

Photothermal therapy (PTT) and magnetic hyperthermia therapy (MHT) using 2D nanomaterials (2DnMat) have recently emerged as promising alternative treatments for cancer and bacterial infections, both important global health challenges. The present review intends to provide not only a comprehensive overview, but also an integrative approach of the state-of-the-art knowledge on 2DnMat for PTT and MHT of cancer and infections. High surface area, high extinction coefficient in near-infra-red (NIR) region, responsiveness to external stimuli like magnetic fields, and the endless possibilities of surface functionalization, make 2DnMat ideal platforms for PTT and MHT. Most of these materials are biocompatible with mammalian cells, presenting some cytotoxicity against bacteria. However, each material must be comprehensively characterized physiochemically and biologically, since small variations can have significant biological impact. Highly efficient and selective in vitro and in vivo PTTs for the treatment of cancer and infections are reported, using a wide range of 2DnMat concentrations and incubation times. MHT is described to be more effective against bacterial infections than against cancer therapy. Despite the promising results attained, some challenges remain, such as improving 2DnMat conjugation with drugs, understanding their in vivo biodegradation, and refining the evaluation criteria to measure PTT or MHT effects.

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation

Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.

Molecular insights into the resistance of phospholipid heads to the membrane penetration of graphene nanosheets

The interaction between nanomaterials and phospholipid membranes underlies many emerging biological applications. To what extent hydrophilic phospholipid heads shield the bilayer from the integration of hydrophobic nanomaterials remains unclear, and this open question contains important insights for understanding biological membrane physics. Here, we present molecular dynamics (MD) simulations to clarify the resistance of phospholipid heads to the membrane penetration of graphene nanosheets. With 130 simulation trials, we observed that ∼22% graphene nanosheets penetrate the POPC bilayer. Sharp corners of the nanosheets should have a lower energy barrier than nanosheet edges, but interestingly, the membrane penetration mainly starts from the edge-approaching orientation. We thoroughly analyzed the pentration pathway and propulsion, indicating that the membrane penetration of graphene nanosheets is dominated by the joint effects of nanosheet edges and corners. Furthermore, the molecular origin of the resistance is clarified by evaluating the bilayers of different phospholipids, which successfully correlates the penetration resistance of phospholipid heads with the correlated motions of neighboring phospholipids for the first time. These results are expected to inspire future studies on the dynamic behavior of phospholipids, bio-nano interfaces, and design of biological nanomaterials.

The reversal of drug resistance by two-dimensional titanium carbide Ti2 C (2D Ti2C) in non-small-cell lung cancer via the depletion of intracellular antioxidant reserves

Background

Chemoresistance is a major barrier limiting the therapeutic efficacy of late stage non‐small cell lung cancer (NSCLC). In this study, we sought to use two‐dimensional titanium carbide (2D Ti₂C) to reverse cisplatin resistance in NSCLC.

Methods

We first achieved favorable properties as a potential anti‐tumor agent. We then compared cell viability and cisplatin uptake in chemoresistant NSCLC cells before and after the use of 2D Ti₂C. Afterwards, we explored the effects of 2D Ti₂C on intracellular antioxidant reserves, followed by evaluating the subsequent changes in the expression of core drug resistance genes. Finally, we confirmed the tumor inhibitory effect and bio‐safety of 2D Ti₂C in a drug‐resistant lung cancer model in nude mice.

Results

Due to the properties of thin layer, large specific surface area, and abundant reactive groups on the surface, 2D Ti₂C can deplete the antioxidant reserve systems such as the glutathione redox buffer system, γ‐glutamylcysteine synthetase (γ‐GCS), glutathione peroxidase (GPx), glutathione‐S‐transferase‐Pi (GST‐π), and metallothionein (MT), thereby increasing the intracellular accumulation of cisplatin and decreasing the expression of drug resistance genes.

Conclusions

2D Ti₂C can reverse NSCLC chemoresistance both in vitro and in vivo, suggesting that it may potentially become a novel and effective means to treat chemoresistant NSCLC in the clinic.

De Novo Design of Entropy-Driven Polymers Resistant to Bacterial Attachment via Multicomponent Reactions

Nonbactericidal polymers that prevent bacterial attachment are important for public health, environmental protection, and avoiding the generation of superbugs. Here, inspired by the physical bactericidal process of carbon nanotubes and graphene derivatives, we develop nonbactericidal polymers resistant to bacterial attachment by using multicomponent reactions (MCRs) to introduce molecular "needles" (rigid aliphatic chains) and molecular "razors" (multicomponent structures) into polymer side chains. Computer simulation reveals the occurrence of spontaneous entropy-driven interactions between the bacterial bilayers and the "needles" and "razors" in polymer structures and provides guidance for the optimization of this type of polymers for enhanced resistibility to bacterial attachment. The blending of the optimized polymer with commercially available polyurethane produces a film with remarkably superior stability of the resistance to bacterial adhesion after wear compared with that of commercial mobile phone shells made by the Sharklet technology. This proof-of-concept study explores entropy-driven polymers resistant to bacterial attachment via a combination of MCRs, computer simulation, and polymer chemistry, paving the way for the de novo design of nonbactericidal polymers to prevent bacterial contamination.

Mild adsorption of carbon nitride (C3N3) nanosheet on a cellular membrane reveals its suitable biocompatibility

Recently, the novel hole-containing carbon nitride C₃N₃ nanomaterial was successfully synthesized, featuring outstanding and unique mechanical and electrical properties. However, to fully exploit this nanomaterial in biomedical applications, information regarding its biocompatibility is necessary. Herein, by using all-atom molecular dynamics simulations, we evaluate the interactions between a C₃N₃ nanosheet and a critical cellular component, that is, a lipid membrane bilayer. Our results indicate that the C₃N₃ nanosheet is able to interact with the lipid bilayer surface without affecting the membrane's structural integrity. Moreover, our results showed that the C₃N₃ nanosheet is adsorbed on the surface of the lipid bilayer without inflicting any structural damage to the membrane, regardless of the conditions of the system (that is, with and without restrains in the C₃N₃ nanosheet). Also, we found that both energy contributions, namely vdW and Coulomb energies, conjointly mediated the C₃N₃ adsorption process. In comparison and as expected, pristine graphene significantly disturbed the membrane structure. Perpendicularly-oriented-sheet simulations described the significance of the surface charges of the C₃N₃ nanosheet in prohibiting its insertion into the membrane. Detailed analysis indicated that the electrostatic attraction between the pores in the C₃N₃ structure and the lipid head amino groups stabilized the interaction restricting the insertion of the C₃N₃ structure deeper into the membrane. Our results suggested the importance of the negatively charged C₃N₃ pores when interacting with lipid membranes. Our findings shed light on the potential compatibility of C₃N₃ with biomembranes and its underlying molecular mechanism, which might provide a useful foundation for the future exploration of this 2D nanomaterial in biomedical applications.

Machine-Learning-Based Approach to Decode the Influence of Nanomaterial Properties on Their Interaction with Cells

In an in vitro nanotoxicity system, cell-nanoparticle (NP) interaction leads to the surface adsorption, uptake, and changes into nuclei/cell phenotype and chemistry, as an indicator of oxidative stress, genotoxicity, and carcinogenicity. Different types of nanomaterials and their chemical composition or "corona" have been widely studied in context with nanotoxicology. However, rare reports are available, which delineate the details of the cell shape index (CSI) and nuclear area factors (NAFs) as a descriptor of the type of nanomaterials. In this paper, we propose a machine-learning-based graph modeling and correlation-establishing approach using tight junction protein ZO-1-mediated alteration in the cell/nuclei phenotype to quantify and propose it as indices of cell-NP interactions. We believe that the phenotypic variation (CSI and NAF) in the epithelial cell is governed by the physicochemical descriptors (e.g., shape, size, zeta potential, concentration, diffusion coefficients, polydispersity, and so on) of the different classes of nanomaterials, which critically determines the intracellular uptake or cell membrane interactions when exposed to the epithelial cells at sub-lethal concentrations. The intrinsic and extrinsic physicochemical properties of the representative nanomaterials (NMs) were measured using optical (dynamic light scattering, NP tracking analysis) methods to create a set of nanodescriptors contributing to cell-NM interactions via phenotype adjustments. We used correlation function as a machine-learning algorithm to successfully predict cell and nuclei shapes and polarity functions as phenotypic markers for five different classes of nanomaterials studied herein this report. The CSI and NAF as nanodescriptors can be used as intuitive cell phenotypic parameters to define the safety of nanomaterials extensively used in consumer products and nanomedicine.

Entropy at Bio-Nano Interfaces

Entropy, one of the central concepts of thermodynamics, can be a predominant contribution to structural formation and transition. Although it is well-known that diverse forces and energies can significantly contribute to the structures and activities at bio-nano interfaces, the potential entropic contribution remains less well understood. Therefore, this review article seeks to provide a conceptual framework demonstrating that entropy can be exploited to shape the physicochemical properties of bio-nano interfaces and thereby regulate the structures, responses, and functions of biological systems. We introduce the typical types of entropy that matter at bio-nano interfaces. Moreover, some key characteristics featuring entropy at bio-nano interfaces, such as the difference between entropic force and energetic interaction and the associated implications for biomimetic research, are discussed. We expect that this review could stimulate further effort in the fundamental research of entropy in biology and in the biological applications of entropic effects in designer biomaterials.

Diffusive transport of nanoscale objects through cell membranes: a computational perspective

Diffusion is an essential and fundamental means of transport of substances on cell membranes, and the dynamics of biomembranes plays a crucial role in the regulation of numerous cellular processes. The understanding of the complex mechanisms and the nature of particle diffusion have a bearing on establishing guidelines for the design of efficient transport materials and unique therapeutic approaches. Herein, this review article highlights the most recent advances in investigating diffusion dynamics of nanoscale objects on biological membranes, focusing on the approaches of tailored computer simulations and theoretical analysis. Due to the presence of the complicated and heterogeneous environment on native cell membranes, the diffusive transport behaviors of nanoparticles exhibit unique and variable characteristics. The general aspects and basic theories of normal diffusion and anomalous diffusion have been introduced. In addition, the influence of a series of external and internal factors on the diffusion behaviors is discussed, including particle size, membrane curvature, particle-membrane interactions or particle-inclusion, and the crowding degree of membranes. Finally, we seek to identify open problems in the existing experimental, simulation, and theoretical research studies, and to propose challenges for future development.

Do biomedical engineers dream of graphene sheets?

During the past few years, graphene has outstandingly emerged as a key nanomaterial for boosting the performance of commercial, industrial and scientific related technologies. The popularity of this novel nanomaterial in biomedical engineering is due to its excellent biological, electronic, optical and thermal properties that, as a whole, surpass the features of commonly used biomaterials and consequently open a wide range of applications so far within the reach of science fiction. In this minireview, the potential of graphene and its based materials in the expanding biomedical field is highlighted with focus on groundbreaking diagnostic, monitoring and therapeutic strategies. Some of the major challenges related to the synthesis and safety of graphene-based materials are also briefly discussed because of their critical importance in bringing this class of carbon materials closer to the clinic.

Transport of a graphene nanosheet sandwiched inside cell membranes

The transport of nanoparticles at bio-nano interfaces is essential for many cellular responses and biomedical applications. How two-dimensional nanomaterials, such as graphene and transition-metal dichalcogenides, diffuse along the cell membrane is, however, unknown, posing an urgent and important issue to promote their applications in the biomedical area. Here, we show that the transport of graphene oxides (GOs) sandwiched inside cell membranes varies from Brownian to Lévy and even directional dynamics. Specifically, experiments evidence sandwiched graphene-cell membrane superstructures in different cells. Combined simulations and analysis identify a sandwiched GO-induced pore in cell membrane leaflets, spanning unstable, metastable, and stable states. An analytical model that rationalizes the regimes of these membrane-pore states fits simulations quantitatively, resulting in a mechanistic interpretation of the emergence of Lévy and directional dynamics. We finally demonstrate the applicability of sandwiched GOs in enhanced efficiency of membrane-specific drug delivery. Our findings inform approaches to programming intramembrane transport of two-dimensional nanomaterials toward advantageous biomedical applications.

Graphene quantum dot assisted translocation of drugs into a cell membrane

Graphene quantum dots (GQDs) are increasingly being recognized as anti-cancer drug carriers, e.g., doxorubicin delivery, in many experiments. In this work, the structure, thermodynamics and dynamic properties of model drugs (doxorubicin and deoxyadenosine) translocating into a POPC lipid membrane with the assistance of GQDs were investigated via MD simulation and free energy calculation. The simulation results imply that GQD19 can facilitate the permeation of model drugs into the lipid membrane on the nanosecond timescale with less deformation of the cell membrane structure. More importantly, free energy calculations further revealed that the translocation free energy of doxorubicin or deoxyadenosine permeating into the lipid bilayer could be significantly reduced with the assistance of GQD19. Our results suggest that GQDs with appropriate size may assist in the drug delivery process by reducing the translocation free energy permeating into the biomembrane. These results may promote the molecular design and application of GQD-based drug delivery systems.

Modeling Interactions between Liposomes and Hydrophobic Nanosheets

2D nanomaterials could cause structural disruption and cytotoxic effects to cells, which greatly challenges their promising biomedical applications including biosensing, bioimaging, and drug delivery. Here, the physical and mechanical interaction between lipid liposomes and hydrophobic nanosheets is studied utilizing coarse-grained (CG) molecular dynamics (MD) simulations. The simulations reveal a variety of characteristic interaction morphologies that depend on the size and the orientation of nanosheets. Dynamic and thermodynamic analyses on the morphologic evolution provide insights into molecular motions such as "nanosheet rotation," "lipid extraction," "lipid flip-flop," and "lipid spreading." Driven by these molecular motions, hydrophobic nanosheets cause morphologic changes of liposomes. The lipid bilayer structure can be corrugated, and the overall liposome sphere can be split or collapsed by large nanosheets. In addition, nanosheets embedded into lipid bilayers greatly weaken the fluidity of lipids, and this effect can be cumulatively enhanced as nanosheets continuously intrude. These results could facilitate molecular-level understanding on the cytotoxicity of nanomaterials, and help future nanotoxicology studies associating computational modeling with experiments.

Cellular Signaling Pathways Activated by Functional Graphene Nanomaterials

The paper reviews the network of cellular signaling pathways activated by Functional Graphene Nanomaterials (FGN) designed as a platform for multi-targeted therapy or scaffold in tissue engineering. Cells communicate with each other through a molecular device called signalosome. It is a transient co-cluster of signal transducers and transmembrane receptors activated following the binding of transmembrane receptors to extracellular signals. Signalosomes are thus efficient and sensitive signal-responding devices that amplify incoming signals and convert them into robust responses that can be relayed from the plasma membrane to the nucleus or other target sites within the cell. The review describes the state-of-the-art biomedical applications of FGN focusing the attention on the cell/FGN interactions and signalosome activation.

Functionalization Pattern of Graphene Oxide Sheets Controls Entry or Produces Lipid Turmoil in Phospholipid Membranes

Molecular dynamics, coarse-grained to the level of hydrophobic and hydrophilic interactions, shows that graphene oxide sheets, GOSs, can pierce through the phospholipid membrane and navigate the double layer only if the hydrophilic groups are randomly dispersed in the structure. Their behavior resembles that found in similar calculations for pristine graphene sheets. If the oxidation is located at the edge of the sheets, GOSs hover over the membrane and trigger a major reorganization of the lipids. The reorganization is the largest when the radius of the edge-functionalized sheet is similar to the length of the lipophilic chain of the lipids. In the reorganization, the heads of the lipid chains form dynamical structures that pictorially resemble the swirl of water flowing down a drain. All effects maximize the interaction between hydrophobic moieties on the one hand and lipophilic fragments on the other and are accompanied by a large number of lipid flip-flops. Possible biological consequences are discussed.