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Research Projects

Come talk to us about how CODA technology might benefit your research project.

Computationally Optimized DNA Assembly of Synthetic Genes

GOAL: To develop the computational algorithms and the accompanying biological methods for the design and synthesis of self-assembling DNA sequences.
COLLABORATOR: Rick Lathrop, Bren School of Information and Computer Sciences
FUNDING: IGB/CBRL seed funding; NSF Information Technology Research (ITR) grant
PUBLICATION: Larsen LSZ, Wassman CD, Hatfield GW, Lathrop RH; Computationally optimised DNA assembly of synthetic genes. International Journal of Bioinformatics Research and Applications;4(3):324-36 (2008).

CODA Assembly of Gene Libraries

GOAL:To expand CODA technology to design complex wholly defined gene libraries for protein engineering and drug discovery.
COLLABORATOR: She-pin Hung
FUNDING: Phase I NIH/STTR Grant sub award from CODA Genomics, Inc., Phase II STTR Grant subaward from Verdezyne, Inc., Carlsbad, CA
PATENT: Lathrop, R.H. and Hatfield, G.W. "Method for producing a synthetic gene or other DNA. " U.S. Patent no. 7,262,031. Issued August 28, 2007.

Computationally Optimized DNA Assembly of Synthetic Human Collagen Genes

GOAL: To develop the computational algorithms and the accompanying biological methods for the design and synthesis of self-assembling DNA sequences with repeating amino acid sequence repeats.
COLLABORATORS: Szu Wong and Nancy DaSilva, Department of Chemical Engineering and Materials Science
FUNDING: IGB/CBRL seed funding; NIH
PUBLICATION: Chan SW, Hung SP, Raman SK, Hatfield GW, Lathrop RH, Da Silva NA, Wang SW. Recombinant human collagen and biomimetic variants using a de novo gene optimized for modular assembly. Biomacromolecules;11(6):1460-9 (2010).

Metabolically Engineering Yeast for Biofuels

GOAL: To exploit CODA technology for the engineering of yeast to utilize biomass sugars for the production of transportation fuels and petrochemical replacements.
COLLABORATORS: Suzanne Sandmeyer, Department of Biological Chemistry, Nancy DaSilva, Department of Chemical Engineering and Materials Science
FUNDING: UC Discovery grant, NSF
PUBLICATION:Fang F, Salmon K, Shen MW, Aeling KA, Ito E, Irwin B, TRan UP, Hatfield GW, Da Silva NA, Sandmeyer S. A vector set for systematic metabolic engineering in Saccharomyces cerevisiae. Yeast 2011 Feb: 28(2): 123-36.

Small Molecule Reactivation of Mutant p53 Proteins

GOAL: To develop algorithms to predict how function can be restored to p53 mutant proteins found in association with nearly half of all human cancers. This information is used to design anti-cancer drugs.
COLLABORATORS: Peter Kaiser, Department of Biological Chemistry; Rick Lathrop, Department of Information and Computer Sciences; Richard Chamberlin, ; Department of Chemistry; Hartmut Luecke and Melanie Cocco, Dept. Molecular Biology and Biochemistry; Rommie Amaro, Department of Pharmaceutical Sciences.
FUNDING: IGB/CBRL seed funding; NIH (NCI)
PUBLICATION: Baronio R, Danziger SA, Hall LV, Salmon K, Hatfield GW, Lathrop RH, Kaiser P. All-codon scanning identifies p53 cancer rescue mutations. Nucleic Acids Res. 2010 Jun 25.
PUBLICATION: Danziger SA, Baronio R, Ho L, Hall L, Salmon K, Hatfield GW, Kaiser P, Lathrop RH. Predicting positive p53 cancer rescue regions using Most Informative Positive (MIP) active learning. PLoS Comput Biol. 5(9) 2009.
PUBLICATION: Demir O, Baronio R, Salehi F, Wassman CD, Hall L, Hatfield GW, Chamberlin R, Kaiser P, Lathrop RH, Amaro RE. Ensemble-Based Computational Approach Discriminates Functional Activity of p53 Cancer and Rescue Mutants. PLoS Comput Biol. 2011 7(10):e1002238. Epub 2011.
PUBLICATION: Wassman CD, Baronio R, Demir O, Wallentine BD, Chen CK, Hall LV, Salehi F, Lin DW, Chung BP, Hatfield GW, Chamberlin RA, Luecke H, Lathrop RH, Kaiser P, Amaro RE. Computational identification of a transiently open L1/S3 pocket for reactivation or mutant p53, Nature Commun, 2013:4, 1407.