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An integrated toolkit combining computational systems biology techniques with molecular dynamics simulations to delineate functionality of GPCRs

Award Number: R01LM013876
ORGANIZATION: NATIONAL LIBRARY OF MEDICINE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 07/05/2022
PERIOD OF PERFORMANCE END DATE: 03/31/2027

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An integrated toolkit combining computational systems biology techniques with molecular dynamics simulations to delineate functionality of GPCRs - Project Summary / Abstract In the last decade there has been an explosion of resolved high-resolution structures of G-protein coupled receptors (GPCRs) and their complexes with several G-proteins, collectively known as transducer proteins. GPCRs are dynamic proteins, and exist in multiple functional conformational states. Comparisons of three-dimensional structures of the inactive and active states of GPCRs have led to identification of residue pair distances that show distinct changes upon activation. Such residue pairs are known as “activation microswitches”. Molecular Dynamics (MD) simulations is an attractive tool for identifying (i) the residue pairs that are critical to GPCR activation, (ii) residue pairs involved in allosteric communication from the ligand binding site to the G protein coupling site, and (iii) residue pairs in the GPCR:G protein interfaces that contribute to their coupling strength and selectivity. While our ability to generate long time scale dynamics trajectories have increased exponentially, the results of MD simulations have largely been analyzed using prior knowledge of the GPCRs. There is a critical need for adopting the unbiased, data-driven, systems biology tools to analyze long time scale MD trajectories data to mine knowledge on the residue motions that provide information on allosteric communication network in GPCRs. Our overarching goal in this grant is to apply Bayesian Network (BN) modeling, an interpretable machine learning methodology, to the MD simulation trajectories data on GPCR:G protein complexes in order to identify the residues in various GPCR structural regions that contribute to ligand selectivity. Network-centered approaches have not been used, so far, to analyze high-dimensional residue pairs MD simulation data. BN modeling, in particular, has attractive properties (interpretability, probabilistic nature of the data representation, statistical validation, tools for topology comparison and analysis) that presently deployed secondary MD simulation data analysis methods, such as principal component analysis (PCA) of residue pairs, lack. We propose to use BN modeling with large scale MD trajectories (multiple short and multiple long trajectories) of inactive state GPCRs and fully active state GPCR:G protein complexes to (i) identify the activation microswitches, the residue pairs that show large scale conformational changes upon activation, and (ii) outline the residue network involved in the allosteric communication from the agonist binding site to the G-protein coupling sites. We will also (iii) identify the residues in the GPCR:G protein interface that contribute to selectivity in coupling to specific family of G proteins (Gs, Gi and Gq). In aim 2, we will (iv) dissect time-correlated events using BN series and dynamic BN (DBN) models to delineate and scrutinize the residue networks that lead to large scale transitions. Importantly, the deliverables will include an unprecedented “toolkit” (algorithms + software) incorporating system biology tools for analyzing MD simulation trajectories data that are generalizable to any protein complexes.


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	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	000	4	2/12/2026	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2025 ( Subtotal = $374,000 )
2025	2025	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	001	4	6/26/2025	NON-COMPETING CONTINUATION	$37,400
2025	2025	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	000	4	3/11/2025	NON-COMPETING CONTINUATION	$336,600
														Subtotal = $374,000

Issue Date FY: 2024 ( Subtotal = $374,000 )
2024	2024	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	001	3	5/8/2024	NON-COMPETING CONTINUATION	$37,400
2024	2024	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	000	3	3/22/2024	NON-COMPETING CONTINUATION	$336,600
														Subtotal = $374,000

Issue Date FY: 2023 ( Subtotal = $374,000 )
2023	2023	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	000	2	3/14/2023	NON-COMPETING CONTINUATION	$374,000
														Subtotal = $374,000

Issue Date FY: 2022 ( Subtotal = $374,000 )
2022	2022	BECKMAN RESEARCH INSTITUTE OF THE CITY OF HOPE	1500 DUARTE RD	DUARTE	CA	91010	LOS ANGELES	USA	Medical Library Assistance	000	1	7/5/2022	NEW	$374,000
														Subtotal = $374,000

Grand Total All Awards = $1,496,000

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An integrated toolkit combining computational systems biology techniques with molecular dynamics simulations to delineate functionality of GPCRs

Award Number: R01LM013876

ORGANIZATION: NATIONAL LIBRARY OF MEDICINE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 07/05/2022

PERIOD OF PERFORMANCE END DATE: 03/31/2027

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