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Engineering Enzymes for Improved Stability and Retained Function via Rapid Design-Build-Test-Learn Cycles integrating AI/Physics based predictions with Cell-free Protein Synthesis Experimental Testing

Award Number: R15GM155803
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/01/2024
PERIOD OF PERFORMANCE END DATE: 07/31/2027

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Engineering Enzymes for Improved Stability and Retained Function via Rapid Design-Build-Test-Learn Cycles integrating AI/Physics based predictions with Cell-free Protein Synthesis Experimental Testing - Abstract The transformative breakthrough of Google DeepMind’s AlphaFold2 on the reliability of sequence to protein structure prediction, demonstrated the power of machine learning approaches in advancing the study and engineering of proteins. Currently a number of inverse protein folding neural network models employ different objective functions in the design of proteins which come with trade-offs and can lead to adversarial sequence predictions. This project seeks to apply a different objective function to overcome limitations of current inverse protein folding models with the specific goal of predicting mutations that will increase the stability of therapeutic and diagnostic proteins. Additionally, AI- and Physics-based Simulation filters are integrated to enable the prediction of sequences that increase stability and retain function. It is hypothesized that by combining these AI tools with the experimental cell-free protein synthesis and stability/activity assays, rapid design-build-test-learn cycles can be performed to create AI models tuned specifically for the target protein. This technology is directly applied to the highly sensitive diagnostic reporter protein NanoLuc and the promising cancer therapeutic Onconase to expand their utility through enhanced stability.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $448,723 )
2024	2024	BRIGHAM YOUNG UNIVERSITY	A-153 ASB	PROVO	UT	84602	UTAH	USA	Biomedical Research and Research Training	000	1	7/25/2024	NEW	$448,723
														Subtotal = $448,723

Grand Total All Awards = $448,723

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Engineering Enzymes for Improved Stability and Retained Function via Rapid Design-Build-Test-Learn Cycles integrating AI/Physics based predictions with Cell-free Protein Synthesis Experimental Testing

Award Number: R15GM155803

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/01/2024

PERIOD OF PERFORMANCE END DATE: 07/31/2027

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