SBIR/STTR Research Award

Accurate protein folding software to predict ligand induced conformational changes in G protein coupled receptors

Award identifier 7371e6c088ca2bbf2426e6f70f0255859c5ae0d1a3429e2ac102ea20e36fb678Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,302,341

Program and phase

SBIR · Phase II – Direct to Phase II

Award year

2016

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
DNASTAR, INC.
Proposal award date
2016-09-01
Contract end date
2019-06-30
UEI
MM8CFNUNTBL7
Solicitation number
PAR15-288
Topic code
100

Research abstract

Abstract In humans and animals G protein coupled receptors GPCRs are embedded on cell surfaces and function as key regulators of physiological events by transmitting signals from extracellular stimulants across the cell membrane into the cell Impaired or abnormal GPCR function can result in disordered physiological processes causing a broad and diverse range of diseases For this reason GPCRs are targeted for therapeutic intervention by over of the FDA approved drugs on the market as well as many of those in development today However biomedical studies of GPCRs are hampered by a lack of atomic structures due to the difficulty of experimentally determining membrane protein structures Thus far drug discovery efforts have gone without the benefit of software tools that can accurately model the D structures of GPCRs at the atomic level Such tools if they existed could provide an in depth understanding of how new drugs will interact with GPCRs and support the ability to predict their therapeutic benefit Here we propose to advance GPCR drug discovery by developing highly accurate software tools built on the success of the iterative threading assembly refinement I TASSER algorithm for protein structure prediction This proposal seeks to develop new computational methodologies for the accurate comprehensive and more powerful generation of atomic level GPCR models The aims of the project focus on developing more accurate and effective GPCR structure predictions through better modeling of the challenging loop domains which play important but often poorly understood roles in GPCR function and of the overall structural changes induced by drug or ligand binding which controls GPCR signal transmission into the cell In particular overall predictive capability will be improved by incorporating new concerted loop modeling and transmembrane helix packing methods into full chain GPCR structure predictions and also by introducing ligand binding interactions into the fully flexible ligand GPCR complex structure assembly simulations when constructing the structure of a ligand bound to its receptor Additionally we will replace software dependencies that impede the commercial distribution of this GPCR structure prediction tool thereby accelerating pharmaceutical structure based drug design The project goal is to deliver advanced GPCR structure prediction software that is powerful accurate and easy to use for both academic and commercial use which will accelerate GPCR drug discovery by enabling for the first time detailed and accurate GPCR structure predictions G protein coupled receptors GPCRs are the largest family of proteins targeted in drug discovery and have been and will continue to be invaluable targets for treating human diseases Understanding the structure of GPCRs and conformational changes that occur upon binding to a ligand are critical requirements for performing further research on this important family of proteins Current approaches for determining GPCR structures are slow expensive and for computer simulated approaches inaccurate In this project we propose to advance computational tools enabling drug discovery and development by creating an efficient software pipeline that models the D structure of GPCRs and explores the macromolecular dynamics of GPCRs bound to any ligand or any drug candidate molecule at a level of accuracy required by pharmaceutical researchers The resulting computer simulated models will support major advancements in drug discovery for human health animal health and related research

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

31 SBIR/STTR records share this UEI (1983–2023). Reported award amounts total $23,638,372. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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