SBIR/STTR Research Award

Innovative glycan-specific reagents to accelerate the detection of disease biomarkers

Award identifier 40879fd71148545a088ad1299316ee06a9e91b88c4362123aa0b6dc04c2a04e8Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$313,827

Program and phase

SBIR · Phase I

Award year

2025

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
LECTENZ BIO, INC.
Proposal award date
2025-07-18
Contract end date
2026-07-17
UEI
JTGCK219C6F4
Solicitation number
PAR24-131
Topic code
300

Research abstract

PROJECT SUMMARY Glycans have several distinct properties that make them excellent targets for disease biomarkers. Firstly, because the structures of cell surface glycans are determined by a complex enzymatic pathway within the cell, any alteration to this homeostasis, such as from disease, may result in aberrant protein glycosylation. Thus, specific glycan structures that are not present, or are in low amounts, in normal states proliferate in disease states, such as cancer. Secondly, their location on cell surfaces makes them readily accessible to detection reagents. Thirdly, any change in cellular glycosylation machinery may impact a large number of glycoproteins, offering many potential glycan-related biomarkers per diseased cell. To effectively employ and discover glycan disease markers a wider range of highly-specific reagents are urgently needed. The monosaccharide mannose has been identified in many disease markers, but is difficult to detect specifically within the context of other glycans with existing reagents. Using structurally-guided mutagenesis, we will convert an α-mannosidase enzyme into a high affinity reagent for the detection of high mannose glycans that are known biomarkers for a number of cancers. Such engineered lectin-like reagents derived from enzymes are called “Lectenz®”, and have several advantages over lectins and antibodies. The principal advantages of an engineered Lectenz® over an antibody are that the Lectenz® is specific to the carbohydrate sequence, but, in contrast to antibodies, will recognize that sequence in a broad range of glycans. Further, in contrast to carbohydrate reagents based on plant lectins, engineered Lectenz® are derived from enzymes that have exquisite substrate specificities and low toxicities. Additional advantages of Lectenz® include precise definition of specificity, tunable binding properties, and ease of recombinant expression, enabling their potential use in affinity purification, western blotting, in situ histological staining, and in vivo imaging. We will generate mannose-binding Lectenz® that can bind high mannose glycans with high specificity. Glycosylation detection is essential in fully characterizing and exploiting glycans as markers of specific disease states, and yet current reagents have broad specificity.

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

18 SBIR/STTR records share this UEI (2009–2025). Reported award amounts total $14,474,759. 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

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.