Identification of protein-protein interactions by surface plasmon resonance followed by mass spectrometry

2D material-based surface plasmon resonance biosensors for applications in different domains: an insight

The design of surface plasmon resonance (SPR) sensors has been greatly enhanced in recent years by the advancements in the production and integration of nanostructures, leading to more compact and efficient devices. There have been reports of novel SPR sensors having distinct nanostructures, either as signal amplification tags like gold nanoparticles (AuNPs) or as sensing substrate-like two-dimensional (2D) materials including graphene, transition metal dichalcogenides (TMDCs), MXene, black phosphorus (BP), metal-organic frameworks (MOFs), and antimonene. Such 2D-based SPR biosensors offer advantages over conventional sensors due to significant increases in their sensitivity with a good figure of merit and limit of detection (LOD). Due to their atomically thin structure, improved sensitivity, and sophisticated functionalization capabilities, 2D materials can open up new possibilities in the field of healthcare, particularly in point-of-care diagnostics, environmental and food monitoring, homeland security protection, clinical diagnosis and treatment, and flexible or transient bioelectronics. The present study articulates an in-depth analysis of the most recent developments in 2D material-based SPR sensor technology. Moreover, in-depth research of 2D materials, their integration with optoelectronic technology for a new sensing platform, and the predicted and experimental outcomes of various excitation approaches are highlighted, along with the principles of SPR biosensors. Furthermore, the review projects the potential prospects and future trends of these emerging materials-based SPR biosensors to advance in clinical diagnosis, healthcare biochemical, and biological applications.

Identifying and overcoming the sampling challenges in relative binding free energy calculations of a model protein:protein complex

Relative alchemical binding free energy calculations are routinely used in drug discovery projects to optimize the affinity of small molecules for their drug targets. Alchemical methods can also be used to estimate the impact of amino acid mutations on protein:protein binding affinities, but these calculations can involve sampling challenges due to the complex networks of protein and water interactions frequently present in protein:protein interfaces. We investigate these challenges by extending a GPU-accelerated opensource relative free energy calculation package (Perses) to predict the impact of amino acid mutations on protein:protein binding. Using the well-characterized model system barnase:barstar, we describe analyses for identifying and characterizing sampling problems in protein:protein relative free energy calculations. We find that mutations with sampling problems often involve charge-changes, and inadequate sampling can be attributed to slow degrees of freedom that are mutation-specific. We also explore the accuracy and efficiency of current state-of-the-art approaches-alchemical replica exchange and alchemical replica exchange with solute tempering-for overcoming relevant sampling problems. By employing sufficiently long simulations, we achieve accurate predictions (RMSE 1.61, 95% CI: [1.12, 2.11] kcal/mol), with 86% of estimates within 1 kcal/mol of the experimentally-determined relative binding free energies and 100% of predictions correctly classifying the sign of the changes in binding free energies. Ultimately, we provide a model workflow for applying protein mutation free energy calculations to protein:protein complexes, and importantly, catalog the sampling challenges associated with these types of alchemical transformations. Our free open-source package (Perses) is based on OpenMM and available at https://github.com/choderalab/perses .

Surface plasmon resonance analysis for detecting non-structural protein 1 of dengue virus in Indonesia

Dengue is an acute febrile disease caused by dengue virus (DENV) that is transmitted by Aedes sp., which causes serious health conditions in many countries. Non-structural protein 1 (NS1) is a co-factor for the RNA replication of this virus, which represents a new strategy for the identification of dengue. Prompt and accurate laboratory diagnosis of this infection is required to assist in patient triage and management, as well as prevent the spread of this infection. In the present study, we tested the potential of surface plasmon resonance (SPR) as a diagnostic tool for dengue infections. NS1 antigen protein was used as an analyte that targets anti-NS1 antibodies, with their interaction resulting in a change in the refractive index. In comparison to currently available gold-standard detection methods [enzyme-linked immunosorbent assay (ELISA) and reverse transcription polymerase chain reaction (RT-PCR)], SPR showed a similar sensitivity but greater efficiency and simplicity in terms of infection detection. Out of 26 samples collected from patients with dengue in Indonesia, SPR was able to correctly identify all 16 positively infected individuals at a lower concentration and a shorter period of time compared to ELISA and RT-PCR. This study revealed that SPR is a promising tool for DENV detection and potentially other diseases as well.

A convenient renewable surface plasmon resonance chip for relative quantification of genetically modified soybean in food and feed

The cultivation of genetically modified organisms (GMO) continues to expand worldwide. Still, many consumers express concerns about the use of GMO in food or feed, and many countries have legislated on labelling systems to indicate the presence of GMO in commercial products. To deal with the increased number of GMO events and to address related regulations, alternative detection methods for GMO inspection are required. In this work, a genosensor based on Surface Plasmon Resonance under continuous flow was developed for the detection and quantification of a genetically modified soybean (event GTS 40-3-2). In a single chip, the simultaneous detection of the event-specific and the taxon-specific samples were achieved, whose detection limits were 20 pM and 16 pM, respectively. The reproducibility was 1.4%, which supports the use of the chip as a reliable and cost-effective alternative to other DNA-based techniques. The results indicate that the proposed method is a versatile tool for GMO quantification in food and feed samples.

Noelin1 Affects Lateral Mobility of Synaptic AMPA Receptors

Lateral diffusion on the neuronal plasma membrane of the AMPA-type glutamate receptor (AMPAR) serves an important role in synaptic plasticity. We investigated the role of the secreted glycoprotein Noelin1 (Olfactomedin-1 or Pancortin) in AMPAR lateral mobility and its dependence on the extracellular matrix (ECM). We found that Noelin1 interacts with the AMPAR with high affinity, however, without affecting rise- and decay time and desensitization properties. Noelin1 co-localizes with synaptic and extra-synaptic AMPARs and is expressed at synapses in an activity-dependent manner. Single-particle tracking shows that Noelin1 reduces lateral mobility of both synaptic and extra-synaptic GluA1-containing receptors and affects short-term plasticity. While the ECM does not constrain the synaptic pool of AMPARs and acts only extrasynaptically, Noelin1 contributes to synaptic potentiation by limiting AMPAR mobility at synaptic sites. This is the first evidence for the role of a secreted AMPAR-interacting protein on mobility of GluA1-containing receptors and synaptic plasticity.

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Noelin1 interacts with high affinity to AMPA receptors (AMPARs)

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Noelin1 is secreted upon cellular stimulation

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(Extra)synaptic AMPAR mobility, but not channel properties, are affected by Noelin1

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Reducing synaptic AMPAR lateral mobility by Noelin1 limits synaptic plasticity

A RAGE-Targeted Antibody-Drug Conjugate: Surface Plasmon Resonance as a Platform for Accelerating Effective ADC Design and Development

Antibodies, antibody-like molecules, and therapeutics incorporating antibodies as a targeting moiety, such as antibody-drug conjugates, offer significant potential for the development of highly efficacious drugs against a wide range of disorders. Despite some success, truly harnessing the superior targeting properties of these molecules requires a platform from which to effectively identify the best candidates for drug development. To streamline the development of antibody-drug conjugates targeting gynecological cancers within our laboratory, we incorporated surface plasmon resonance analysis (Biacore™ T200) into our development toolkit. Antibodies, selected based on positive ELISA screens as suitable for development as antibody-drug conjugates, were evaluated using surface plasmon resonance to determine a wide range of characteristics including specificity, kinetics/affinity, the effect of linker binding, the impact of the drug to antibody ratio, and the effect of endosomal pH on antibody-antigen binding. Analysis revealed important kinetics data and information regarding the effect of conjugation and endosomal pH on our antibody candidates that correlated with cell toxicity and antibody internalization data. As well as explaining observations from cell-based assays regarding antibody-drug conjugate efficacies, these data also provide important information regarding intelligent antibody selection and antibody-drug conjugate design. This study demonstrates the application of surface plasmon resonance technology as a platform, where detailed information can be obtained, supporting the requirements for rapid and high-throughput screening that will enable enhanced antibody-drug conjugate development.

Aptamer selection by direct microfluidic recovery and surface plasmon resonance evaluation

A surface plasmon resonance (SPR)-based SELEX approach has been used to raise RNA aptamers against a structured RNA, derived from XBP1 pre-mRNA, that folds as two contiguous hairpins. Thanks to the design of the internal microfluidic cartridge of the instrument, the selection was performed during the dissociation phase of the SPR analysis by recovering the aptamer candidates directly from the target immobilized onto the sensor chip surface. The evaluation of the pools was performed by SPR, simultaneously, during the association phase, each time the amplified and transcribed candidates were injected over the immobilized target. SPR coupled with SELEX from the first to the last round allowed identifying RNA aptamers that formed highly stable loop-loop complexes (KD equal to 8nM) with the hairpin located on the 5' side of the target. High throughput sequencing of two key rounds confirmed the evolution observed by SPR and also revealed the selection of hairpins displaying a loop not fully complementary to the loop of its target. These candidates were selected mainly because they bound 79 times faster to the target than those having a complementary loop. SELEX coupled with SPR is expected to speed up the selection process because selection and evaluation are performed simultaneously.

Surface plasmon resonance: a versatile technique for biosensor applications

Surface plasmon resonance (SPR) is a label-free detection method which has emerged during the last two decades as a suitable and reliable platform in clinical analysis for biomolecular interactions. The technique makes it possible to measure interactions in real-time with high sensitivity and without the need of labels. This review article discusses a wide range of applications in optical-based sensors using either surface plasmon resonance (SPR) or surface plasmon resonance imaging (SPRI). Here we summarize the principles, provide examples, and illustrate the utility of SPR and SPRI through example applications from the biomedical, proteomics, genomics and bioengineering fields. In addition, SPR signal amplification strategies and surface functionalization are covered in the review.