Engineering Sensor Proteins

Merkx, Maarten; Smith, Bradley D.; Jewett, Michael C.

doi:10.1021/acssensors.9b02459

Cited by 17 publications

(8 citation statements)

References 27 publications

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“…Healthcare diagnostics, such as the quantitative detection of disease-related proteins, is a major application of supramolecular electrochemical biosensors ( Hewitt and Wilson, 2017 ; Merkx et al, 2019 ). As an alternative to PCR-based nucleic acid analysis techniques, an increasing number of studies apply electrochemical detection due to its rapid detection speed with high accuracy ( Espy et al, 2006 ; Song et al, 2016 ; Fu et al, 2018 ; Drame et al, 2020 ).…”

Section: Supramolecular Sensing With Electrochemical and Electrical Read-outsmentioning

confidence: 99%

Evolution of Supramolecular Systems Towards Next-Generation Biosensors

2021

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Supramolecular materials, which rely on dynamic non-covalent interactions, present a promising approach to advance the capabilities of currently available biosensors. The weak interactions between supramolecular monomers allow for adaptivity and responsiveness of supramolecular or self-assembling systems to external stimuli. In many cases, these characteristics improve the performance of recognition units, reporters, or signal transducers of biosensors. The facile methods for preparing supramolecular materials also allow for straightforward ways to combine them with other functional materials and create multicomponent sensors. To date, biosensors with supramolecular components are capable of not only detecting target analytes based on known ligand affinity or specific host-guest interactions, but can also be used for more complex structural detection such as chiral sensing. In this Review, we discuss the advancements in the area of biosensors, with a particular highlight on the designs of supramolecular materials employed in analytical applications over the years. We will first describe how different types of supramolecular components are currently used as recognition or reporter units for biosensors. The working mechanisms of detection and signal transduction by supramolecular systems will be presented, as well as the important hierarchical characteristics from the monomers to assemblies that contribute to selectivity and sensitivity. We will then examine how supramolecular materials are currently integrated in different types of biosensing platforms. Emerging trends and perspectives will be outlined, specifically for exploring new design and platforms that may bring supramolecular sensors a step closer towards practical use for multiplexed or differential sensing, higher throughput operations, real-time monitoring, reporting of biological function, as well as for environmental studies.

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Section: Supramolecular Sensing With Electrochemical and Electrical Read-outsmentioning

confidence: 99%

Evolution of Supramolecular Systems Towards Next-Generation Biosensors

2021

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“…For these biosensors, elements of protein biorecognition include recombinant antibodies, synthetic peptides, enzymes, and aptamers that are highly specific to the protein of interest (Figure 2B ). [ 59 ] These biorecognition elements are typically used within a surface‐immobilized assay, such as a DNA‐based assay with DNA‐DNA hybridization that transfers a conjugated protein to the electrode surface (Figure 2B′ ), an aptamer‐based assay with the aptamer‐binding protein driving the target to the electrode surface, or an immunoassay with surface antibody‐protein interactions on the electrode (Figure 2B″ ). However, all of these platforms are limited by a number of factors in their ability to accurately detect biomarkers, such as the binding affinity of the recognition molecule, signal instability in whole blood‐ particularly when a redox reporter is initially placed on the electrode surface; [ 60 ] and the low concentration of biomarkers in a small sample volume, which decreases the overall sensitivity of the assay.…”

Section: Poc Detection Of Biomarkersmentioning

confidence: 99%

Extracellular Biomarkers of Inner Ear Disease and Their Potential for Point‐of‐Care Diagnostics

et al. 2021

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Rapid diagnostic testing has become a mainstay of patient care, using easily obtained samples such as blood or urine to facilitate sample analysis at the point‐of‐care. These tests rely on the detection of disease or organ‐specific biomarkers that have been well characterized for a particular disorder. Currently, there is no rapid diagnostic test for hearing loss, which is one of the most prevalent sensory disorders in the world. In this review, potential biomarkers for inner ear‐related disorders, their detection, and quantification in bodily fluids are described. The authors discuss lesion‐specific changes in cell‐free deoxyribonucleic acids (DNAs), micro‐ribonucleic acids (microRNAs), proteins, and metabolites, in addition to recent biosensor advances that may facilitate rapid and precise detection of these molecules. Ultimately, these biomarkers may be used to provide accurate diagnostics regarding the site of damage in the inner ear, providing practical information for individualized therapy and assessment of treatment efficacy in the future.

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“…The ability to computationally engineer protein sequences has a wide range of applications from therapeutics (Fosgerau & Hoffmann, 2015;Khera & Maity, 2019), to vaccines (Li & Li, 2020;Liu et al, 2020;Malonis et al, 2020;X. Zhou et al, 2020), sensors (Karimzadeh et al, 2018;Merkx et al, 2019) or protein-based materials (Capezza et al, 2019;de la Rica & Matsui, 2010) and beyond that. While there has been progress towards designing protein folds, much improvement is needed for the redesign or de novo design of protein-protein interfaces (PPIs).…”

Section: Introductionmentioning

confidence: 99%

Deep learning of Protein Sequence Design of Protein-protein Interactions

Syrlybaeva

Strauch

2022

Preprint

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MotivationAs more data of experimentally determined protein structures is becoming available, data-driven models to describe protein sequence-structure relationship become more feasible. Within this space, the amino acid sequence design of protein-protein interactions has still been a rather challenging sub-problem with very low success rates - yet it is central for the most biological processes.ResultsWe developed an attention-based deep learning model inspired by algorithms used for image-caption assignments for sequence design of peptides or protein fragments. These interaction fragments are derived from and represent core parts of protein-protein interfaces. Our trained model allows the one-sided design of a given protein fragment which can be applicable for the redesign of protein-interfaces or the de novo design of new interactions fragments. Here we demonstrate its potential by recapitulating naturally occurring protein-protein interactions including antibody-antigen complexes. The designed interfaces capture essential native interactions with high prediction accuracy and have native-like binding affinities. It further does not need precise backbone location, making it an attractive tool for working with de novo design of protein-protein interactions.AvailabilityThe source code of the method is available at https://github.com/strauchlab/iNNterfaceDesignSupplementary informationSupplementary data are available at Bioinformatics online.

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Engineering Sensor Proteins

Cited by 17 publications

References 27 publications

Evolution of Supramolecular Systems Towards Next-Generation Biosensors

Evolution of Supramolecular Systems Towards Next-Generation Biosensors

Extracellular Biomarkers of Inner Ear Disease and Their Potential for Point‐of‐Care Diagnostics

Deep learning of Protein Sequence Design of Protein-protein Interactions

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