Rational Optimization of Protein Solubility

Award Information
Agency: Department of Health and Human Services
Branch: N/A
Contract: 1R43GM069256-01
Agency Tracking Number: GM069256
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2003
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
XENCOR, INC.
XENCOR, INC., 111 W LEMON AVE, MONROVIA, CA, 91016
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 JOHN DESJARLAIS
 (626) 737-8077
 JRD@XENCOR.COM
Business Contact
 STEPHEN DOBERSTEIN
Phone: (626) 737-7046
Email: SDOBERSTEIN@XENCOR.COM
Research Institution
N/A
Abstract
DESCRIPTION (provided by applicant): Technologies that would enable the generation of soluble proteins for use as reagents in drug discovery efforts and as therapeutic entities represent a significant unmet need in drug discovery. One method for increasing solubility is the introduction of appropriate mutations. A general, robust, and efficient method for identifying mutations that will confer solubility to a protein of interest would have tremendous commercial value. This proposal seeks to employ an innovative technology, Protein Design Automation(r) (PDATM), to improve the solubility of an important protein therapeutic, interferon beta. Currently, interferon beta is the primary treatment for multiple sclerosis. However, interferon beta forms aggregates because of poor solubility, resulting in decreased efficacy and increased immunogenicity of this therapeutic. Furthermore, interferon beta forms inclusion bodies during expression in E. coli. The resulting high production costs thus hinder further development of improved variants. Interferon beta variants with improved solubility would have significant commercial potential and benefit patients through increased efficacy and decreased side effects. The research design strategy to achieve a soluble interferon beta variant includes performing rational protein design calculations, constructing a library of improved variants that are predicted to have improved solubility, identifying soluble variants with high throughput screening methods, and testing these improved variants for solubility and activity. After validation of this computational and experimental design strategy, long term aims of this proposal are to improve the solubility of additional protein therapeutics and to provide the service of solubility optimization to facilitate external drug discovery efforts.

* information listed above is at the time of submission.

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