The ProQuant® Platform
Our proteomics platform technology, ProQuant®, is a collection of proprietary and patented protocols designed to measure in an unbiased way as many aspects of the proteome as possible.
All of the ProQuant® protocols are based on conventional bottom-up proteomics. Samples can be purified proteins or complex biological samples such as serum or solid tissues. Processing can then remove some of the most abundant proteins (e.g. albumin and immunoglobulins from serum) or homogenise solid tissues before endoproteinase digestion. All of this work is performed in-house. The processed samples are analysed by LC-MS/MS by a trusted provider using our custom protocols. Raw MS data is then returned to RxCelerate for analysis using our proprietary workflows.
The ProQuant® Difference
Most commercial proteomics platforms focus solely on identifying as many proteins as possible. This often overlooks the practical relevance of results obtained. At RxCelerate, we take a different, more balanced, approach. ProQuant® is designed not only to look for depth of coverage, but for breadth (investigating as many aspects of the proteome as possible) and usability. We focus on delivering high-quality actionable data tailored to your project, not just theoretical performance metrics.
Proprietary Bioinformatic Tools
The analytical performance ProQuant® provides doesn’t just enable us to obtain good data on protein abundances. We have a range of proprietary bioinformatic tools to extract knowledge from these ultra-large, ultra-accurate datasets.
ANALYSE
Analyse specific modifications across all of the proteins in the samples.
Investigate
Investigate patterns of changes in classes of modifications.
Compare
Compare patterns of cleavage in different samples.
Look
Look for signals indicative of different proteoforms in sample groups.
A Deep Dive Into ProQuant®
The performance of the bottom-up proteomics methods we use has been optimised at every stage of the process, including sample preparation techniques, MS processes and data analytics.
For our unbiased PTM-focused approach using a traditional data-dependent acquisition (DDA) method, we modify how the MS collects data coming off the chromatography column. In typical samples, many peptides elute simultaneously, and the MS must balance MS1 survey scans with selecting abundant ions for fragmentation (MS2 scans). Even the fastest instruments face trade-offs, but our patented method manages this better than competitors, delivering superior data quality.
Additional gains come from optimised sample handling and MS data processing to maximise reproducibility. We also apply proprietary machine learning algorithms to improve peptide identification and reduce artifacts. Crucially, all steps are fully unsupervised, eliminating bias related to the biological question.
The Proof Is In The Data
During development of the first of our ProQuant® protocols, using a traditional DDA method, we benchmarked changes to the protocol using an in-house approach that gives a very practical insight into the quality of the data. Combining this approach with optimisations based on the detection and measurement of ions, rather than proteins, led to a DDA-based method with unmatched analytical performance.
In a complex protein mixture our patented DDA method has an analytical CV (including sample preparation) below 20% for just under half of all of the peptides identified in the samples; 10 times greater than the average of three competitor DDA approaches. Even comparing analysis of the same ProQuant®-optimised raw output files from the MS, we still identify 7x more peptides than the average of three competitors at this level of precision, reflecting the quality of our data analytics.
The same analysis at the protein level shows a similar picture. Although peptide-level errors can partially cancel out when aggregating to protein abundance, ProQuant® still identifies between two and ten times more proteins with a CV <20% compared with competitor DDA approaches. This reflects both improved estimates of peptide abundance and the ProQuant data analytics improving peptide identification.
Understanding The Choices: DIA or DDA
Data-independent acquisition (DIA) represents a major advance in proteomics, offering precision and accuracy that was previously only achievable with our ProQuant® DDA platform. While DIA brings significant potential, it also introduces complexity in data interpretation and constraints in bioinformatics. We work with our clients to determine when and how to apply DIA, DDA, or a combination of both, ensuring that the most appropriate method is used to address the specific biological question at hand.
RxCelerate offers a unique business model catering to both small molecules and biologics. We work with you to drive your asset through drug discovery, preclinical research and beyond.
Our combination of integrated teams and unique technologies allows RxCelerate to develop the optimal drug discovery strategy to deliver pharma-grade drug candidates quickly and at a fraction of the cost of traditional approaches.