SBIR/STTR Research Award

An Automated Proteoform Characterization Control System

Award identifier a6fbfc163d2f34bccb49ccc4e7aab820409a01ea2d726bdc4909f524b9bc119aAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$202,005

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
PROTEINACEOUS, INC.
Proposal award date
2020-04-01
Contract end date
2020-09-30
UEI
J9L5HK2UVD38
Solicitation number
PA19-272
Topic code
400

Research abstract

ABSTRACT Current mass spectrometers have benefited from a technological revolution over recent years, with great increases to speed and resolution as well as significant improvements in fragmentation capabilities for biomolecule analyses. Proteomics results that were previously unthinkable only a few years ago are now routine and being performed by hundreds of laboratories across the world. However, despite these advancements and successes, the software systems guiding mass spectrometry data acquisition have not seen technology improvements on the same scale. As such, these new mass spectrometers have not yet reached their full potential, particularly for intact protein characterization where analytes are more varied than peptides and acquisition parameters are tougher to generalize. A software named AutoProt is being developed to automate the targeted characterization of proteoforms from a proteoform family. AutoProt controls the acquisition of mass spectrometry data, initiating a data-driven fragmentation routine when proteoforms-of-interest from a proteoform family are detected in survey scans. As each fragmentation data scan is collected, AutoProt matches experimental data to theoretical proteoform fragments and uses the corresponding results to make an informed decision on how to further characterize the proteoform. By using instant feedback, fragmentation settings are customized specifically and in real-time for each proteoform being analyzed, leading to better characterization results in less overall time. In Phase I, AutoProt will be further developed to handle the characterization of multiple proteoforms such as modified and truncated forms from the same proteoform family in the same acquisition run, enabling a wider assessment of the proteoforms present in a sample (e.g., all the proteoforms from the same UniProt gene accession after immunoprecipitation). A database will be integrated into AutoProt to store run data and allow sample characterization to be resumed for additional acquisition runs. Furthermore, the characterization routine will be made more robust in this grant through the collection of a large amount of fragmentation data on many proteoforms and then the distillation of that data into a general fragmentation model. AutoProt will then be able to broadly characterize proteoforms with different properties (e.g., molecular weight and fragmentation propensities). Lastly, AutoProt will be outfitted with report generation to automatically output experimental report files compatible with the proteoform data visualization tool, TDCollider. With these features in place, AutoProt will be a first-of-its-kind automated characterization software with first-class proteoform characterization abilities and acquisition-to-report capabilities, eliminating time- consuming set up of acquisition and processing for proteoform characterization data.PROJECT NARRATIVE This novel mass spectrometry acquisition software enables detailed analyses of disease-related proteoforms and extensive characterization of therapeutic proteins. The software will make top down mass spectrometry and the important proteoform information that it can uncover more accessible for a higher number of researchers to benefit from complete proteoform characterization data.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2019–2023). Reported award amounts total $4,081,199. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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