faculty

David Baker

dabaker@uw.edu

University of Washington, 

Biophysical and Structural Biology

Protein structure prediction and design

Faculty Contact Information

Building: MolES Room: 442 Box: 351655 Phone: 206-543-1295 https://www.bakerlab.org/

Lab Information

Location: Institute for Protein Design Building: MolES Room: 4th floor Box: 351655 http://www.ipd.uw.edu/

Accepting Students For:

Rotation, Autumn
Rotation, Spring
Rotation, Summer
Rotation, Winter

Publications

Protein structure determination using metagenome sequence data.

Ovchinnikov S, Park H, Varghese N, Huang PS, Pavlopoulos GA, Kim DE, Kamisetty H, Kyrpides NC, Baker D.

Science (New York, N.Y.). 2017; 355(6322):294-298. NIHMSID: NIHMS869064

PubMed [journal]
PMID:
28104891
PMCID:
PMC5493203

Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules.

Park H, Bradley P, Greisen P Jr, Liu Y, Mulligan VK, Kim DE, Baker D, DiMaio F.

Journal of chemical theory and computation. 2016; 12(12):6201-6212. NIHMSID: NIHMS867713

PubMed [journal]
PMID:
27766851
PMCID:
PMC5515585

Structural insights into SAM domain-mediated tankyrase oligomerization.

DaRosa PA, Ovchinnikov S, Xu W, Klevit RE.

Protein science : a publication of the Protein Society. 2016; 25(9):1744-52.

PubMed [journal]
PMID:
27328430
PMCID:
PMC5338228

Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11.

Ovchinnikov S, Park H, Kim DE, Liu Y, Wang RY, Baker D.

Proteins. 2016; 84 Suppl 1:181-8. NIHMSID: HHMIMS867706

PubMed [journal]
PMID:
26857542
PMCID:
PMC5490372

Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta.

Ovchinnikov S, Kim DE, Wang RY, Liu Y, DiMaio F, Baker D.

Proteins. 2016; 84 Suppl 1:67-75. NIHMSID: HHMIMS866792

PubMed [journal]
PMID:
26677056
PMCID:
PMC5490371

Research Summary

The goal of current research in our laboratory is to develop an improved model of intra and intermolecular interactions and to apply this improved model to the prediction and design of macromolecular structures and interactions using the Rosetta computer program. At the core of Rosetta are the physical model of macromolecular interactions and algorithms for finding the lowest energy structure for an amino acid sequence (protein structure prediction) or a protein-protein complex and for finding the lowest energy amino acid sequence for a protein or protein-protein complex (protein design).