SBIR/STTR Research Award

Fluorescence Intensity-Based Scoring of Macromolecule Crystallization Plates

Award identifier d7bba6ff5aefca94fbdf96b3d77befc43cf5cac8009e4eeb48d89d58328363f5Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$100,000

Program and phase

STTR · Phase I

Award year

2010

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
iXpressGenes, Inc.
Proposal award date
Not reported
Contract end date
Not reported
UEI
TSJKJXX5GNN8
Solicitation number
PHS2010-2
Topic code
NIGMS

Research abstract

DESCRIPTION (provided by applicant): Crystallization, followed by subsequent structure determination, is a major step in understanding the structure-function relationship of macromolecules. Understanding macromolecule structure has become a key part in the development of new pharmaceuticals, and is a major area of NIH research. Crystallization however is also the rate limiting step, despite technological efforts to automate the set-up and crystallization data acquisition processes. The major objectives of the proposed effort are two fold. First is the implementation of a low cost epifluorescence and transmission microscopy system for the automated documentation of macromolecule crystallization plate outcomes. Second is the development of software for the rapid scoring of the images of the crystallization screen outcomes obtained by the microscopy system. The goals of the scoring process in this work are the rapid identification of likely crystals based upon the image pixel intensity due to the fluorescence from trace fluorescently labeled macromolecules (lt 0.5% of the molecules labeled with fluorescent probe), and the graduated scoring of precipitation outcomes that reflects the experimentally determined propensity of those outcomes to be optimized to crystallization conditions. Experimentally, trace fluorescently labeled protein will be subjected to crystallization screens and the outcomes periodically imaged. Intensity-based image analysis will be carried out using the software developed for this effort. Precipitated conditions which show high scores based on the image analysis will be subjected to optimization screening, and we propose there will be a correlation between the scores obtained and subsequent crystallization. Previous research has shown that fluorescence can be a powerful aid in finding and identifying crystals in screening plates (Judge et al., 2005; Forsythe et al., 2006; Groves et al., 2007; Pusey et al., 2008). Crystallization gives the most densely packed state for a protein, and therefore trace fluorescently labeled protein will have the greatest fluorescence intensity relative to clear or precipitated outcomes. The probe, being covalently attached, serves as a reporter to the protein's response to the solution conditions. Some precipitates showed 'bright spots' of fluorescence, and these conditions could subsequently be optimized to crystallization conditions (Pusey et al., 2008). It is further proposed that intensity-based scoring of precipitation outcomes may be used to better discriminate between non-productive and potentially productive precipitation results. Preliminary tests indicate that fluorescence intensity-based crystallization screen scoring should be very fast, with processing times likely to be 5 seconds per image. The capabilities to be developed are necessary for the subsequent introduction and sale of crystallization screening kits that have a balanced incomplete factorial (IF) approach to searching 'precipitation space' during the screening process. This relies upon accurate scoring of the outcomes, which is time consuming and expensive in labor if done by hand. Larger laboratories or research groups can afford the efforts and equipment needed to develop automated crystallization plate image documentation and scoring systems. Smaller groups cannot. Affordable IF implementation is seen as advantageous to improved crystallization and to our business long range development efforts. PUBLIC HEALTH RELEVANCE: Successful crystallization and X-ray data analysis provides important three-dimensional information on the macromolecules structure-function relationship. Many proteins that are potential drug targets or key components in diseases are only available in trace quantities, or are difficult to obtain. This proposal is to expand the data returned during protein crystallization process and the information that can be derived from it, by putting a powerful but affordable results documentation and analysis tool into the hands of crystallization laboratories.

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

9 SBIR/STTR records share this UEI (2006–2017). Reported award amounts total $4,039,932. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, Department of Defense, National Science Foundation

Agency intelligence

Department of Health and Human Services

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