Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review.

In the rapidly evolving landscape of nanomedicine, aptamers have emerged as powerful molecular tools, demonstrating immense potential in targeted therapeutics, diagnostics, and drug delivery systems. This paper explores the computational features of aptamers in nanomedicine, highlighting their advantages over antibodies, including selectivity, low immunogenicity, and a simple production process. A comprehensive overview of the aptamer development process, specifically the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) process, sheds light on the intricate methodologies behind aptamer selection. The historical evolution of aptamers and their diverse applications in nanomedicine are discussed, emphasizing their pivotal role in targeted drug delivery, precision medicine and therapeutics. Furthermore, we explore the integration of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), Internet of Medical Things (IoMT), and nanotechnology in aptameric development, illustrating how these cutting-edge technologies are revolutionizing the selection and optimization of aptamers for tailored biomedical applications. This paper also discusses challenges in computational methods for advancing aptamers, including reliable prediction models, extensive data analysis, and multiomics data incorporation. It also addresses ethical concerns and restrictions related to AI and IoT use in aptamer research. The paper examines progress in computer simulations for nanomedicine. By elucidating the importance of aptamers, understanding their superiority over antibodies, and exploring the historical context and challenges, this review serves as a valuable resource for researchers and practitioners aiming to harness the full potential of aptamers in the rapidly evolving field of nanomedicine.

FRET Based Biosensor: Principle Applications Recent Advances and Challenges.

Förster resonance energy transfer (FRET)-based biosensors are being fabricated for specific detection of biomolecules or changes in the microenvironment. FRET is a non-radiative transfer of energy from an excited donor fluorophore molecule to a nearby acceptor fluorophore molecule. In a FRET-based biosensor, the donor and acceptor molecules are typically fluorescent proteins or fluorescent nanomaterials such as quantum dots (QDs) or small molecules that are engineered to be in close proximity to each other. When the biomolecule of interest is present, it can cause a change in the distance between the donor and acceptor, leading to a change in the efficiency of FRET and a corresponding change in the fluorescence intensity of the acceptor. This change in fluorescence can be used to detect and quantify the biomolecule of interest. FRET-based biosensors have a wide range of applications, including in the fields of biochemistry, cell biology, and drug discovery. This review article provides a substantial approach on the FRET-based biosensor, principle, applications such as point-of-need diagnosis, wearable, single molecular FRET (smFRET), hard water, ions, pH, tissue-based sensors, immunosensors, and aptasensor. Recent advances such as artificial intelligence (AI) and Internet of Things (IoT) are used for this type of sensor and challenges.

In silico study of interaction of (ZnO)12 nanocluster to glucose oxidase-FAD in absence and presence of glucose.

Diabetes mellitus is one of the foremost global concerns, as it has impacted millions of lives. Therefore, there is an urgent need to develop a technology for continuous glucose monitoring in vivo. In the current study, we employed computational methods such as docking, MD simulations, and MM/GBSA, to obtain molecular insights into the interaction between (ZnO)12 nanocluster and glucose oxidase (GOx) that cannot be obtained through experiments alone. For this, theoretical modeling of the 3D cage-like (ZnO)12 nanocluster in ground state configuration was performed. Further docking of (ZnO)12 nanocluster with GOx molecule was carried out to find the nano-bio-interaction of (ZnO)12-GOx complex. To understand the whole interaction and dynamics of (ZnO)12-GOx-FAD-with and without glucose, we performed MD simulation and MM/GBSA analysis of (ZnO)12-GOx-FAD complex and glucose-(ZnO)12-GOx-FAD complex separately. The interaction was found to be stable, and the binding energy of (ZnO)12 to GOx-FAD increases in the presence of glucose by 6 kcal mol-1. This may be helpful in nano probing of the interaction of GOx with glucose. It can help in making a device like fluorescence resonance energy transfer (FRET) based nano-biosensor to monitor the glucose level in pre and post diabetic patient.Communicated by Ramaswamy H. Sarma.

Nanomaterial-Based Electrochemical Nanodiagnostics for Human and Gut Metabolites Diagnostics: Recent Advances and Challenges.

Metabolites are the intermediatory products of metabolic processes catalyzed by numerous enzymes found inside the cells. Detecting clinically relevant metabolites is important to understand their physiological and biological functions along with the evolving medical diagnostics. Rapid advances in detecting the tiny metabolites such as biomarkers that signify disease hallmarks have an immense need for high-performance identifying techniques. Low concentrations are found in biological fluids because the metabolites are difficult to dissolve in an aqueous medium. Therefore, the selective and sensitive study of metabolites as biomarkers in biological fluids is problematic. The different non-electrochemical and conventional methods need a long time of analysis, long sampling, high maintenance costs, and costly instrumentation. Hence, employing electrochemical techniques in clinical examination could efficiently meet the requirements of fully automated, inexpensive, specific, and quick means of biomarker detection. The electrochemical methods are broadly utilized in several emerging and established technologies, and electrochemical biosensors are employed to detect different metabolites. This review describes the advancement in electrochemical sensors developed for clinically associated human metabolites, including glucose, lactose, uric acid, urea, cholesterol, etc., and gut metabolites such as TMAO, TMA, and indole derivatives. Different sensing techniques are evaluated for their potential to achieve relevant degrees of multiplexing, specificity, and sensitivity limits. Moreover, we have also focused on the opportunities and remaining challenges for integrating the electrochemical sensor into the point-of-care (POC) devices.