SBIR/STTR Research Award

Development of a Novel Membrane Protein Solubilization/Stabilization Screen

Award identifier 7e8317e4becf1b4d1e9e470d815a364a292f9870d1c2205de7c69b0bba275cfcAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$153,004

Program and phase

STTR · Phase I

Award year

2015

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
SOLUBLE THERAPEUTICS, INC
Proposal award date
2015-04-03
Contract end date
2015-10-02
UEI
Not reported
Solicitation number
PA14-072
Topic code
100

Research abstract

DESCRIPTION provided by applicant The increasing output of new integral membrane protein IMP structures is partially due to the availability of an increasing number of chemical variables such as detergents detergent like molecules lipids and solubilizing stabilizing additives It is clear that specific combinations and concentrations of these different variables are often necessary to improve IMP solubility stability and crystallization For each IMP studied researchers typically explore via a trial and error approach many of these chemical variables However there is limited understanding of the importance and effect of specific combinations concentrations of these chemical variables on IMP extraction solubilization stabilization purification and crystallization We propose to use our novel technology and approach high throughput self interaction chromatography HSC combined with an incomplete factorial screen and artificial neural network analysis to discover new formulations that improve optimize IMP solubility and physical stability IMP homogeneity This phase proposal will perform a pilot study on seven different IMPs including the chemokine receptor CCR cystic fibrosis transmembrane regulator protein CCR epithelial sodium channel ENaC acid sensing ion channel ASIC P glycoprotein Pgp bacteriorhodopsin BR and ferric yersiniabactin uptake receptor FIP The HSC approach involves rapid experimental determination of second viral coefficient values B values for an incomplete factorial of the total possible number of chemical combinations and concentrations for each IMP This is followed by input and analysis via an artificial neural network ANN program that once andquot trainedandquot produces B value predictions for a complete factorial of possible chemical combinations and concentrations Chemical conditions associated with the most positive B value predictions suggesting improved solubility and physical stability are then experimentally validated via HSC measurements followed by evaluation of the IMPandapos s stability folding via differential scanning calorimetry Western gels CD and when available bio assays solubility and stability in several of these solutions It is possible that the proposed comprehensive analysis of chemical variables will result in new combinations and or concentrations that may become useful andquot cocktailsandquot to be included in screening solubility and stability new IMPs within the same class of IMPs However the major goal of the proposed research is to demonstrate the value of the HSC technology and approach to determine novel and improved solubilization stabilization solutions PUBLIC HEALTH RELEVANCE Researchers typically explore a variety of detergents and detergent lipid combinations in attempts to enable isolation purification of integral membrane proteins IMPs to support biological drug discovery and structural biology studies IMPs important proteins involved in human disease are the targets of more than of all drugs currently under development The inability to express solubilize and purify homogeneous preparations represents a major bottleneck in IMP research adversely affecting drug development pipeline This proposal involves use of a novel technology and experimental approach to determine novel combinations and concentrations of existing detergents and additives that can improve the solubility stability and crystallization of IMPs

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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