SPRD: a surface plasmon resonance database of common factors for better experimental planning

Abstract

Background Surface plasmon resonance is a label-free biophysical technique that is widely used in investigating biomolecular interactions, including protein-protein, protein-DNA, and protein-small molecule binding. Surface plasmon resonance is a very powerful tool in different stages of small molecule drug development and antibody characterization. Both academic institutions and pharmaceutical industry extensively utilize this method for screening and validation studies involving direct molecular interactions. In most applications of the surface plasmon resonance technology, one of the studied molecules is immobilized on a microchip, while the second molecule is delivered through a microfluidic system over the immobilized molecules. Changes in total mass on the chip surface is recorded in real time as an indicator of the molecular interactions. Main body Quality and accuracy of the surface plasmon resonance data depend on experimental variables, including buffer composition, type of sensor chip, coupling chemistry of molecules on the sensor surface, and surface regeneration conditions. These technical details are generally included in materials and methods sections of published manuscripts and are not easily accessible using the common internet browser search engines or PubMed. Herein, we introduce a surface plasmon resonance database, www.sprdatabase.info that contains technical details extracted from 5140 publications with surface plasmon resonance data. We also provide an analysis of experimental conditions preferred by different laboratories. These experimental variables can be searched within the database and help future users of this technology to design better experiments. Conclusion Amine coupling and CM5 chips were the most common methods used for immobilizing proteins in surface plasmon resonance experiments. However, number of different chips, capture methods and buffer conditions were used by multiple investigators. We predict that the database will significantly help the scientific community using this technology and hope that users will provide feedback to improve and expand the database indefinitely. Publicly available information in the database can save a great amount of time and resources by assisting initial optimization and troubleshooting of surface plasmon resonance experiments.

Validation of plasmonic-based biosensors for rapid and sensitive detection of rabbit hemorrhagic and foot-and-mouth disease viruses in biological samples

“…In this work, we have approached these issues in a comprehensive manner, by preparing and comparing different biosensors for their analytical potential and technical limits at detecting viral antigens or intact viruses in biological samples and at screening panels of MAbs. In the first biosensor prepared, the RHDV2 6S subunit was immobilized to the sensorchip by amine coupling, the most handly and widely used procedure for ligand immobilization [21]. Dealing with a raw liver homogenate as starting material, a heterogeneous surface was obtained that hampered the determination of the stoichiometry of the antibody/antigen interaction.…”

A monoamine oxidase B inhibitor ethyl ferulate suppresses microglia-mediated neuroinflammation and alleviates ischemic brain injury

“…Prediction progress on the interaction of protein-ligand was performed according to the tutorial. The affinity of Protein-ligand interaction was analyzed by surface plasmon resonance (SPR) technology, a label-free biophysical technology widely used in biomolecular interaction investigation including protein-ligand interaction ( Tiwari et al, 2021 ), performing by BetterWays technology (Guangzhou, China).…”

Hyaluronan nanoscale clustering and Hyaluronan synthase 2 expression are linked to the invasion of child fibroblasts and infantile fibrosarcoma in vitro and in vivo

“…Raw mRNA sequencing reads were obtained from the sequencing read archive (accession code SRP131149) and processed using the bcbio workflow ( https://bcbio-nextgen.readthedocs.io/en/latest/ ) 25 . The transcripts from the human transcriptome (version GRCh37) were quantified using the salmon tool (version 0.9.1), followed by analysis in R (version 4.0.1) using the tximport package (version 1.161), and DESeq2 (version 1.28.1) 26 , 27 , to analyse differential expression, generate p-values and statistics for downstream analysis via a generalised linear model 28 .…”