Tuesday, January 27, 2026 1/27/2026

Designing selective kinase inhibitors via deep learning

Award Number: R01GM141513
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: 02/01/2022
PERIOD OF PERFORMANCE END DATE: 11/30/2026

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Designing selective kinase inhibitors via deep learning - PROJECT SUMMARY/ABSTRACT Modern cancer biology leans heavily on kinase inhibitors as a means to probe the consequences of deactivating a particular kinase, but the majority of commonly-used chemical probes are not sufficiently target- selective for robust interpretation of the observed phenotypes. By assembling large panels of kinases (corresponding to much of the human kinome), it has become possible to determine the selectivity for a given probe: however, these experiments are expensive and impractical to perform at high throughput. We have recently developed a new computational approach for rapidly and accurately building 3D structural models of individual inhibitor/kinase complexes. Aim 1 of this project entails applying deep learning to build models for predicting the binding affinity of individual inhibitor/kinase pairs, using 3D structural descriptors derived from the corresponding inhibitor/kinase complexes. Aim 2 of this project will build very large computational libraries of novel chemical matter, enriched in compounds with 3D properties that complement kinase binding sites. We will first use the tools developed in Aim 1 to re-evaluate the selectivity of chemical probes that are widely used by cell biologists, thus informing on which ones are useful tools and which ones should be deprecated. To provide a replacement for the outdated chemical probes, we will computationally screen the libraries of Aim 2 for more selective compounds, focusing first on CDK kinases and several kinases that represent therapeutic vulnerabilities in GIST. We will synthesize the top-scoring computational hits, and characterize them using an escalation of biochemical assays, proteomic kinome profiling, structural biology, and cellular assays. If successful, this project will deliver new chemical probes for several hitherto unaddressed (“orphan”) kinases, to serve as chemical tools and as starting point for drug development. Equally importantly though, completion of this project will provide a robust and validated approach for designing potent and selective kinase inhibitors, to be subsequently applied for developing new high-quality probes against each of the 500 human kinases.


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: 2026 ( Subtotal = $0 )
2026	2025	THE INSTITUTE FOR CANCER RESEARCH	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	000	4	10/27/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $549,557 )
2025	2025	THE INSTITUTE FOR CANCER RESEARCH	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	000	4	11/21/2024	NON-COMPETING CONTINUATION	$494,601
2025	2025	THE INSTITUTE FOR CANCER RESEARCH	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	001	4	8/8/2025	NON-COMPETING CONTINUATION	$54,956
														Subtotal = $549,557

Issue Date FY: 2024 ( Subtotal = $549,557 )
2024	2024	THE INSTITUTE FOR CANCER RESEARCH	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	001	3	6/18/2024	NON-COMPETING CONTINUATION	$54,956
2024	2024	THE INSTITUTE FOR CANCER RESEARCH	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	000	3	11/9/2023	NON-COMPETING CONTINUATION	$494,601
2024	2024	THE INSTITUTE FOR CANCER RESEARCH	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	002	3	7/9/2024	NON-COMPETING CONTINUATION	$0
														Subtotal = $549,557

Issue Date FY: 2023 ( Subtotal = $730,834 )
2023	2023	INSTITUTE FOR CANCER RESEARCH, THE	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	000	2	11/21/2022	NON-COMPETING CONTINUATION	$494,601
2023	2023	INSTITUTE FOR CANCER RESEARCH, THE	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	002	2	8/14/2023	SUPPLEMENT FOR EXPANSION	$181,277
2023	2023	INSTITUTE FOR CANCER RESEARCH, THE	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	001	2	2/27/2023	NON-COMPETING CONTINUATION	$54,956
														Subtotal = $730,834

Issue Date FY: 2022 ( Subtotal = $549,557 )
2022	2022	INSTITUTE FOR CANCER RESEARCH, THE	333 COTTMAN AVE	PHILADELPHIA	PA	19111	PHILADELPHIA	USA	Biomedical Research and Research Training	000	1	1/18/2022	NEW	$549,557
														Subtotal = $549,557

Grand Total All Awards = $2,379,505

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Designing selective kinase inhibitors via deep learning

Award Number: R01GM141513

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: 02/01/2022

PERIOD OF PERFORMANCE END DATE: 11/30/2026

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