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

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44GM119985-01A1
Agency Tracking Number: R44GM119985
Amount: $1,302,341.00
Phase: Phase II
Program: SBIR
Awards Year: 2016
Solicitation Year: 2015
Solicitation Topic Code: 100
Solicitation Number: PAR15-288
Small Business Information
3801 REGENT ST STE G, Madison, WI, 53705-5204
DUNS: 130194947
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 (608) 237-3088
Business Contact
Phone: (608) 237-3082
Research Institution
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

* Information listed above is at the time of submission. *

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