Peptide-based electrochemical biosensor for matrix metalloproteinase-14 and protein-overexpressing cancer cells based on analyte-induced cleavage of peptide

Peptide-based self-assembled monolayers (SAMs): what peptides can do for SAMs and vice versa

Self-assembled monolayers (SAMs) represent highly ordered molecular materials with versatile biochemical features and multidisciplinary applications. Research on SAMs has made much progress since the early begginings of Au substrates and alkanethiols, and numerous examples of peptide-displaying SAMs can be found in the literature. Peptides, presenting increasing structural complexity, stimuli-responsiveness, and biological relevance, represent versatile functional components in SAMs-based platforms. This review examines the major findings and progress made on the use of peptide building blocks displayed as part of SAMs with specific functions, such as selective cell adhesion, migration and differentiation, biomolecular binding, advanced biosensing, molecular electronics, antimicrobial, osteointegrative and antifouling surfaces, among others. Peptide selection and design, functionalisation strategies, as well as structural and functional characteristics from selected examples are discussed. Additionally, advanced fabrication methods for dynamic peptide spatiotemporal presentation are presented, as well as a number of characterisation techniques. All together, these features and approaches enable the preparation and use of increasingly complex peptide-based SAMs to mimic and study biological processes, and provide convergent platforms for high throughput screening discovery and validation of promising therapeutics and technologies.

Protease detection in the biosensor era: A review

Proteases have been proposed as potential biomarkers for several pathological conditions including cancers, multiple sclerosis and cardiovascular diseases, due to their ability to break down the components of extracellular matrix and basement membrane. The development of protease biosensors opened up the possibility to investigate the proteolytic activity of dysregulated proteases with higher efficiency over the traditional detection assays due to their quick detection capability, high sensitivity and selectivity, simple instrumentation and cost-effective fabrication processes. In contrast to the recently published review papers that primarily focused on one specific class of proteases or one specific detection method, this review article presents different optical and electrochemical detection methods that can be used to design biosensors for all major protease families. The benefits and drawbacks of various transducer techniques integrated into protease biosensing platforms are analyzed and compared. The main focus is on activity-based biosensors that use peptides as biorecognition elements. The effects of nanomaterials on biosensor performance are also discussed. This review should help readers to select the biosensor that best fits their needs, and contribute to the further development of this research field. Protease biosensors may allow better comprehension of protease overexperession and potentially enable novel devices for point-of-care testing.

Evaluating the Catalytic Efficiency of the Human Membrane-type 1 Matrix Metalloproteinase (MMP-14) Using AuNP-Peptide Conjugates

Interactions of plasmonic nanocolloids such as gold nanoparticles and nanorods with proximal dye emitters result in efficient quenching of the dye photoluminescence (PL). This has become a popular strategy for developing analytical biosensors relying on this quenching process for signal transduction. Here, we report on the use of stable PEGylated gold nanoparticles, covalently coupled to dye-labeled peptides, as sensitive optically addressable sensors for determining the catalytic efficiency of the human matrix metalloproteinase-14 (MMP-14), a cancer biomarker. We exploit real-time dye PL recovery triggered by MMP-14 hydrolysis of the AuNP-peptide-dye to extract quantitative analysis of the proteolysis kinetics. Sub-nanomolar limit of detections for MMP-14 has been achieved using our hybrid bioconjugates. In addition, we have used theoretical considerations within a diffusion-collision framework to derive enzyme substrate hydrolysis and inhibition kinetics equations, which allowed us to describe the complexity and irregularity of enzymatic proteolysis of nanosurface-immobilized peptide substrates. Our findings offer a great strategy for the development of highly sensitive and stable biosensors for cancer detection and imaging.

Detecting the PEX Like Domain of Matrix Metalloproteinase-14 (MMP-14) with Therapeutic Conjugated CNTs

Matrix metalloproteinases (MMPs) are essential proteins acting directly in the breakdown of the extra cellular matrix and so in cancer invasion and metastasis. Given its impact on tumor angiogenesis, monitoring MMP-14 provides strategic insights on cancer severity and treatment. In this work, we report a new approach to improve the electrochemical interaction of the MMP-14 with the electrode surface while preserving high specificity. This is based on the detection of the hemopexin (PEX) domain of MMP-14, which has a greater availability with a stable and low-cost commercial molecule, as a recognition element. This molecule, called NSC-405020, is specific of the PEX domain of MMP-14 within the binding pocket. Through the covalent grafting of the NSC-405020 molecule on carbon nanotubes (CNTs), we were able to detect and quantify MMP-14 using electrochemical impedance spectroscopy with a linear range of detection of 10 ng⋅mL^-1 to 100 ng⋅mL^-1, and LOD of 7.5 ng⋅mL^-1. The specificity of the inhibitory small molecule was validated against the PEX domain of MMP-1. The inhibitor loaded CNTs system showed as a desirable candidate to become an alternative to the conventional recognition bioelements for the detection of MMP-14.

Novel approaches for rapid detection of COVID-19 during the pandemic: A review

The rapid spread of the SARS-CoV-2 virus that caused the COVID-19 disease, has highlighted our urgent need for sensitive, fast and accurate diagnostic technologies. In fact, one of the main challenges for flatting COVID-19 spread charts is the ability to accurately and rapidly identify asymptomatic cases that result in spreading the virus to close contacts. SARS-CoV-2 virus mutation is also relatively rapid, which makes the detection of COVID-19 diseases still crucial even after the vaccination. Conventional techniques, which are commercially available have focused on clinical manifestation, along with molecular and serological detection tools that can identify the SARS-CoV-2 virus however, owing to various disadvantages including low specificity and sensitivity, a quick, low cost and easy approach is needed for diagnosis of COVID-19. Scientists are now showing extensive interest in an effective portable and simple detection method to diagnose COVID-19. There are several novel methods and approaches that are considered viable advanced systems that can meet the demands. This study reviews the new approaches and sensing technologies that work on COVID-19 diagnosis for easy and successful detection of SARS-CoV-2 virus.

Peptide-Derived Biosensors and Their Applications in Tumor Immunology-Related Detection

Small-molecular targeting peptides possess features of biocompatibility, affinity, and specificity, which is widely applied in molecular recognition and detection. Moreover, peptides can be developed into highly ordered supramolecular assemblies with boosting binding affinities, diverse functions, and enhanced stabilities suitable for biosensors construction. In this Review, we summarize recent progress of peptide-based biosensors for precise detection, especially on tumor-related analysis, as well as further provide a brief overview of the progress in tumor immune-related detection. Also, we are looking forward to the prospective future of peptide-based biosensors.

Machine Learning-Reinforced Noninvasive Biosensors for Healthcare

The emergence and development of noninvasive biosensors largely facilitate the collection of physiological signals and the processing of health-related data. The utilization of appropriate machine learning algorithms improves the accuracy and efficiency of biosensors. Machine learning-reinforced biosensors are started to use in clinical practice, health monitoring, and food safety, bringing a digital revolution in healthcare. Herein, the recent advances in machine learning-reinforced noninvasive biosensors applied in healthcare are summarized. First, different types of noninvasive biosensors and physiological signals collected are categorized and summarized. Then machine learning algorithms adopted in subsequent data processing are introduced and their practical applications in biosensors are reviewed. Finally, the challenges faced by machine learning-reinforced biosensors are raised, including data privacy and adaptive learning capability, and their prospects in real-time monitoring, out-of-clinic diagnosis, and onsite food safety detection are proposed.

The Role of Peptides in the Design of Electrochemical Biosensors for Clinical Diagnostics

Peptides represent a promising class of biorecognition elements that can be coupled to electrochemical transducers. The benefits lie mainly in their stability and selectivity toward a target analyte. Furthermore, they can be synthesized rather easily and modified with specific functional groups, thus making them suitable for the development of novel architectures for biosensing platforms, as well as alternative labelling tools. Peptides have also been proposed as antibiofouling agents. Indeed, biofouling caused by the accumulation of biomolecules on electrode surfaces is one of the major issues and challenges to be addressed in the practical application of electrochemical biosensors. In this review, we summarise trends from the last three years in the design and development of electrochemical biosensors using synthetic peptides. The different roles of peptides in the design of electrochemical biosensors are described. The main procedures of selection and synthesis are discussed. Selected applications in clinical diagnostics are also described.

Peptide-based electrochemical biosensors utilized for protein detection

Proteins are generally detected as biomarkers for tracing or determining various disorders in organisms. Biomarker proteins can be tracked in samples with various origins and in different concentrations, revealing whether an organism is in a healthy or unhealthy state. In regard to detection, electrochemical biosensors are a potential fusion of electronics, chemistry, and biology, allowing for fast and early point-of-care detection from a biological sample with the advantages of high sensitivity, simple construction, and easy operation. Peptides present a promising approach as a biorecognition element when connected with electrochemical biosensors. The benefits of short peptides lie mainly in their good stability and selective affinity to a target analyte. Therefore, peptide-based electrochemical biosensors (PBEBs) represent an alternative approach for the detection of different protein biomarkers. This review provides a summary of the past decade of recently proposed PBEBs designed for protein detection, dividing them according to different protein types: (i) enzyme detection, including proteases and kinases; (ii) antibody detection; and (iii) other protein detection. According to these protein types, different sensing mechanisms are discussed, such as the peptide cleavage by a proteases, phosphorylation by kinases, presence of antibodies, and exploiting of affinities; furthermore, measurements are obtained by different electrochemical methods. A discussion and comparison of various constructions, modifications, immobilization strategies and different sensing techniques in terms of high sensitivity, selectivity, repeatability, and potential for practical application are presented.