Enhanced susceptibility of SARS-CoV-2 spike RBD protein assay targeted by cellular receptors ACE2 and CD147: Multivariate data analysis of multisine impedimetric response

Comparative assessment of different anti-CD147/Basigin 2 antibodies as a potential therapeutic anticancer target by molecular modeling and dynamic simulation

Cluster of differentiation 147 (CD147) is an attractive target for anticancer therapy since it is pivotal in developing and progressing several of malignant tumors in the context of its high expression levels. Although anti-CD147 antibodies by different laboratories are designed for the Ig-like domains of CD147, there is a demand to provide priority among these anti-CD147 antibodies for developing of therapeutic anti-CD147 antibody before experimental validations. This study uses molecular docking and dynamic simulation techniques to compare the binding modes and affinities of nine antibody models against the Ig-like domains of CD147. After obtaining the model antibodies by homology modeling via Robetta, we predicted the CDRs of nine antibodies and the epitopes of CD147 to reach more accurate results for antigen affinity in molecular docking. Next, from HADDOCK 2.4., we meticulously handpicked the most superior model clusters (Z-Score: - 2.5 to - 1.2) and identified that meplazumab had higher affinities according to the success rate as the percentage of a scoring scale. We achieved stable simulations of CD147-antibody interaction. Our outcomes hold hypothetical importance for further experimental cancer research on the design and development of the relevant model antibodies.

Central Countries' and Brazil's Contributions to Nanotechnology

Abstract:

Nanotechnology is a cornerstone of the scientific advances witnessed over the past few years. Nanotechnology applications are extensively broad, and an overview of the main trends worldwide can give an insight into the most researched areas and gaps to be covered. This document presents an overview of the trend topics of the three leading countries studying in this area, as well as Brazil for comparison. The data mining was made from the Scopus database and analyzed using the VOSviewer and Voyant Tools software. More than 44.000 indexed articles published from 2010 to 2020 revealed that the countries responsible for the highest number of published articles are The United States, China, and India, while Brazil is in the fifteenth position. Thematic global networks revealed that the standing-out research topics are health science, energy, wastewater treatment, and electronics. In a temporal observation, the primary topics of research are: India (2020), which was devoted to facing SARS-COV 2; Brazil (2019), which is developing promising strategies to combat cancer; China (2018), whit research on nanomedicine and triboelectric nanogenerators; the United States (2017) and the Global tendencies (2018) are also related to the development of triboelectric nanogenerators. The collected data are available on GitHub. This study demonstrates the innovative use of data-mining technologies to gain a comprehensive understanding of nanotechnology's contributions and trends and highlights the diverse priorities of nations in this cutting-edge field.

Molecular interactions between perlecan LG3 and the SARS-CoV-2 spike protein receptor binding domain

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused a global health crisis with significant clinical morbidity and mortality. While angiotensin-converting enzyme 2 (ACE2) is the primary receptor for viral entry, other cell surface and extracellular matrix proteins may also bind to the viral receptor binding domain (RBD) within the SARS-CoV-2 spike protein. Recent studies have implicated heparan sulfate proteoglycans, specifically perlecan LG3, in facilitating SARS-CoV-2 binding to ACE2. However, the role of perlecan LG3 in SARS-CoV-2 pathophysiology is not well understood. In this study, we investigated the binding interactions between the SARS-CoV-2 spike protein RBD and perlecan LG3 through molecular modeling simulations and surface plasmon resonance (SPR) experiments. Our results indicate stable binding between LG3 and SARS-CoV-2 spike protein RBD, which may potentially enhance RBD-ACE2 interactions. These findings shed light on the role of perlecan LG3 in SARS-CoV-2 infection and provide insight into SARS-CoV-2 pathophysiology and potential therapeutic strategy for COVID-19.

Discriminating macromolecular interactions based on an impedimetric fingerprint supported by multivariate data analysis for rapid and label-free Escherichia coli recognition in human urine

This manuscript presents a novel approach to address the challenges of electrode fouling and highly complex electrode nanoarchitecture, which are primary concerns for biosensors operating in real environments. The proposed approach utilizes multiparametric impedance discriminant analysis (MIDA) to obtain a fingerprint of the macromolecular interactions on flat glassy carbon surfaces, achieved through self-organized, drop-cast, receptor-functionalized Au nanocube (AuNC) patterns. Real-time monitoring is combined with singular value decomposition and partial least squares discriminant analysis, which enables selective identification of the analyte from raw impedance data, without the use of electric equivalent circuits. As a proof-of-concept, the authors demonstrate the ability to detect Escherichia coli in real human urine using an aptamer-based biosensor that targets RNA polymerase. This is significant, as uropathogenic E. coli is a difficult-to-treat pathogen that is responsible for the majority of hospital-acquired urinary tract infection cases. The proposed approach offers a limit of detection of 11.3 CFU/mL for the uropathogenic E. coli strain No. 57, an analytical range in all studied concentrations (up to 105 CFU/mL), without the use of antifouling strategies, yet not being specific vs other E.coli strain studied (BL21(DE3)). The MIDA approach allowed to identify negative overpotentials (-0.35 to -0.10 V vs Ag/AgCl) as most suitable for the analysis, offering over 80% sensitivity and accuracy, and the measurement was carried out in just 2 min. Moreover, this approach is scalable and can be applied to other biosensor platforms.

Identification of host receptors for viral entry and beyond: a perspective from the spike of SARS-CoV-2

Identification of the interaction between the host membrane receptor and viral receptor-binding domain (RBD) represents a crucial step for understanding viral pathophysiology and for developing drugs against pathogenic viruses. While all membrane receptors and carbohydrate chains could potentially be used as receptors for viruses, prioritized searches focus typically on membrane receptors that are known to have been used by the relatives of the pathogenic virus, e.g., ACE2 used as a receptor for SARS-CoV is a prioritized candidate receptor for SARS-CoV-2. An ideal receptor protein from a viral perspective is one that is highly expressed in epithelial cell surface of mammalian respiratory or digestive tracts, strongly conserved in evolution so many mammalian species can serve as potential hosts, and functionally important so that its expression cannot be readily downregulated by the host in response to the infection. Experimental confirmation of host receptors includes (1) infection studies with cell cultures/tissues/organs with or without candidate receptor expression, (2) experimental determination of protein structure of the complex between the putative viral RDB and the candidate host receptor, and (3) experiments with mutant candidate receptor or homologues of the candidate receptor in other species. Successful identification of the host receptor opens the door for mechanism-based development of candidate drugs and vaccines and facilitates the inference of what other animal species are vulnerable to the viral pathogen. I illustrate these approaches with research on identification of the receptor and co-factors for SARS-CoV-2.

Engineering boron and nitrogen codoped carbon nanoarchitectures to tailor molecularly imprinted polymers for PFOS determination

Per- and polyfluoroalkyl substances (PFAS) have gained significant attention as emerging contaminants due to their persistence, abundance, and adverse health effects. Consequently, the urgent need for ubiquitous and effective sensors capable of detecting and quantifying PFAS in complex environmental samples has become a priority. In this study, we present the development of an ultrasensitive molecularly imprinted polymer (MIP) electrochemical sensor tailored by chemically vapour-deposited boron and nitrogen codoped diamond-rich carbon nanoarchitectures for the selective determination of perfluorooctanesulfonic acid (PFOS). This approach allows for a multiscale reduction of MIP heterogeneities, leading to improved selectivity and sensitivity in PFOS detection. Interestingly, the peculiar carbon nanostructures induce a specific distribution of binding sites in the MIPs that exhibit a strong affinity for PFOS. The designed sensors demonstrated a low limit of detection (1.2 μg L^-1) and exhibited satisfactory selectivity and stability. To gain further insights into the molecular interactions between diamond-rich carbon surfaces, electropolymerised MIP, and the PFOS analyte, a set of density functional theory (DFT) calculations was performed. Validation of the sensor's performance was carried out by successfully determining PFOS concentrations in real complex samples, such as tap water and treated wastewater, with average recovery rates consistent with UHPLC-MS/MS results. These findings demonstrate the potential of MIP-supported diamond-rich carbon nanoarchitectures for water pollution monitoring, specifically targeting emerging contaminants. The proposed sensor design holds promise for the development of in situ PFOS monitoring devices operating under relevant environmental concentrations and conditions.

Texture or Linker? Competitive Patterning of Receptor Assembly toward Ultra-Sensitive Impedimetric Detection of Viral Species at Gold-Nanotextured Titanium Surfaces

In this work, we study the electrodes with a periodic matrix of gold particles pattered by titanium dimples and modified by 3-mercaptopropionic acid (MPA) followed by CD147 receptor grafting for specific impedimetric detection of SARS-CoV-2 viral spike proteins. The synergistic DFT and MM/MD modeling revealed that MPA adsorption geometries on the Au-Ti surface have preferential and stronger binding patterns through the carboxyl bond inducing an enhanced surface coverage with CD147. Control of bonding at the surface is essential for oriented receptor assembling and boosted sensitivity. The complex Au-Ti electrode texture along with optimized MPA concentration is a crucial parameter, enabling to reach the detection limit of ca. 3 ng mL-1. Scanning electrochemical microscopy imaging and quantum molecular modeling were performed to understand the electrochemical performance and specific assembly of MPA displaying a free stereo orientation and not disturbed by direct interactions with closely adjacent receptors. This significantly limits nonspecific interceptor reactions, strongly decreasing the detection of receptor-binding domain proteins by saturation of binding groups. This method has been demonstrated for detecting the SARS virus but can generally be applied to a variety of protein-antigen systems. Moreover, the raster of the pattern can be tuned using various anodizing processes at the titania surfaces.