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htrSPRanalysis: An open source R package for expedited analysis of high-throughput binding kinetics data
Janice M McCarthy1,2, Kan Li2,3, Georgia D Tomaras2,3,4,5,6
1Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, United States of America.
Plos Computational Biology
|July 31, 2026
Summary
A new R package, htrSPRanalysis, streamlines high-throughput surface plasmon resonance (SPR) data analysis. It enables efficient, automated kinetic analysis for large biomolecular screening panels, accelerating therapeutic antibody discovery.
Area of Science:
- Biophysics
- Computational Biology
- Immunology
Background:
- Surface Plasmon Resonance (SPR) is crucial for label-free detection of molecular binding kinetics, widely used in biophysical characterization.
- High-throughput SPR (HT-SPR) enables simultaneous analysis of hundreds of binding interactions, facilitating large-panel biomolecule screening.
- Current SPR analysis software often has limitations, including proprietary restrictions, low-throughput design, and labor-intensive user interactions.
Purpose of the Study:
- To introduce htrSPRanalysis, an open-source R package specifically designed for efficient high-throughput SPR binding kinetics data analysis.
- To address the limitations of existing software by providing automated and user-friendly tools for large-scale kinetic analysis.
- To accelerate the analysis process for therapeutic antibody discovery research.
Main Methods:
- Development of htrSPRanalysis, an R package leveraging multi-core computing for efficient sensorgram analysis.
- Implementation of automated procedures for determining optimal concentration ranges and dissociation windows for fitting.
- Inclusion of automated bulk shift detection and analysis output generation for all sensorgrams.
Main Results:
- htrSPRanalysis efficiently analyzes large numbers of sensorgrams with minimal user interaction.
- The package automates key fitting optimization steps, including concentration range selection and dissociation window determination.
- Automated generation of analysis output facilitates rapid data processing for large panels.
Conclusions:
- htrSPRanalysis significantly speeds up SPR binding kinetics data analysis for large biomolecular screening panels.
- Its high-throughput functionalities and automated optimization make it a valuable tool for therapeutic antibody discovery.
- The open-source nature and efficient design promote wider adoption and application in biophysical characterization.
