SBIR/STTR Research Award

Reliable model building for cryo-EM

Award identifier 04de20f5a5149e3543902924e328b640d1abc12d296f5aa61d77a76ee41d560eAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,719,666

Program and phase

SBIR · Phase II

Award year

2022

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
LIGO ANALYTICS INC
Proposal award date
2022-05-01
Contract end date
2024-04-30
UEI
H3WXH47J27H7
Solicitation number
PA21-259
Topic code
400

Research abstract

Project Abstract Atomic models generated by experimental structural biology are used to understand cellular processes at the molecular level, and also for rational design of drugs and treatments. Cryogenic electron microscopy single particle reconstruction (cryo-EM SPR) generates such atomic models based on interpretation of maps of Coulomb potential that are obtained by averaging many thousands of weak images, with each image containing projection snapshots of individual macromolecules suspended in a thin layer of ice. Consequently, cryo-EM maps represent averages of structural states and frequently have limited and uneven quality resulting from both flexibility of particles used in cryo-EM SPR as well as their non-random distributions in ice called preferred orientation. Building and rebuilding structural models in maps that are low quality due to lack of detail (resolution) or having sampling and reconstruction problems is a challenge. In this proposal, we will address these challenges by developing and implementing methods for automatic and comprehensive model building and validation with carefully designed feedback loops to experimental data analysis. The initial and intermediate models generated by our model building methods will aid cryo-EM SPR projects by stabilizing convergence of computations at all steps of reconstruction, but without introducing bias, with bias removal and quantification being addressed explicitly. Aim 1 will focus on methods that will use ab initio predicted models or experimental models to improve cryo-EM SPR so that they can be used without introducing bias. In Aim 2, a new weighting of information for refinement and validation of the structural models will be developed and implemented to account for uneven quality of information in cryo-EM SPR. Aim 3 will focus on developing and implementing methods for directly coupling 2D classification to model building. Finally, Aim 4 will target analysis and modeling of internal motions to guide the structural interpretation and to improve the resolution of reconstructions. The results will be incorporated into the commercially distributed suite cryoEMMA. The competitive advantage of these approaches arises from their ability to provide highly informative 3D reconstructions in the presence of severe preferred orientation and for single particle signal-to-noise lower than in the current approaches.

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

8 SBIR/STTR records share this UEI (2019–2025). Reported award amounts total $6,581,517. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services, Department of Energy

Agency intelligence

Department of Health and Human Services

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