News & Highlights: A recent collabaration between YRC researcher John Yates and Martin W. Hetzer applied proteomics to examine protein turnover in cells of the rat central nervous system. They found that extremely long-lived proteins associated with chromatin and the nuclear pore complex did not turn over, potentially exposing these proteins to harmful metabolites and accumulation of damage over time. Read more about their findings in the journal Science to learn more. [Read Article]
News & Highlights: YRC Researchers Michael MacCoss and William Stafford Noble have published a new algorithm, dubbed Barista, for identifying proteins in complex biological mixtures. Instead of subdividing the task into separate peptide and protein identification tasks, Barista applies a machine learning approach to identify proteins from source spectra as a single optimization problem. Read their publications in Mol. Cell Proteomics to learn more. [Read Article]
News & Highlights: YRC researcher Stan Fields has used protein mass spectrometry to identify 870 unique sites of ubiquitin attachment on 438 different proteins in the budding yeast Saccharomyces cerevisiae. The analysis was based on the increase in molecular mass of a tryptic peptide carrying two additional glycine residues from the ubiquitin moiety. Read his paper in Proteomics to learn more. [Read Article]
News & Highlights: Hutchinson-Gilford progeria syndrome (HGPS) is a rare and fatal disease characterized by premature aging. In their recent collaboration, YRC researcher John Yates and collaborator Juan Carlos Izpisua Belmonte found induced pluripotent stem cells from HGPS patients lacked molecular characteristics associated with the disease, which were restored upon differentiation. See their paper in Nature to learn more. [Read Article]
News & Highlights: YRC researcher Stan Fields used the model organism Saccharomyces cerevisiae to probe the effects of nutritionally acquired metabolites on statins, a cholesterol-lowering drug widely prescribed to prevent heart disease. He found that copper and zinc ions impair the effect of statins by upregulating genes related to sterol production. Please read his paper in Molecular BioSystems to learn more. [Read Article]
News & Highlights: YRC researchers David Baker and Stan Fields have developed new technology for examining how a protein's sequence affects its function. This new technology is large-scale and may be applied to many in vitro or in vivo protein assays, providing a general means for studying the functional consequences of protein variation. Please read their paper in Nature Methods to learn more. [Read Article]
News & Highlights: The YRC collaborated with Sue Biggins at the Fred Hutchinson Cancer Research Center in Seattle to examine centromeres, whose proper function is critical to prevent conditions associated with cancer and some birth defects. This work, performed in yeast, was recently published in Molecular Cell, where Dr. Biggins proposes a new pathway for the regulation of centromeric function. [Read Article]
News & Highlights: Multidimensional protein identification technology (MudPIT) developed by the YRC was used in a recent collaboration with David Drubin at the University of California, Berkeley, to examine the assembly of actin networks in yeast. In his recent paper in Current Biology, Dr. Drubin describes the nucleation and assembly of these large protein complexes, and how MudPIT was used to characterize their composition. [Read Article]

Structure Prediction and Design


[Click Image to Enlarge]

Disembodied "Hot Spot" residue map of Influenza hemagglutinin depicting amino acids docked to the surface of the protein--a first step in designing binders to disrupt function.
The structures of many biological assemblies are not readily amenable to traditional x-ray crystallographic structure determination methods because they cannot be crystallized. Most assemblies are also too large for conventional NMR structure determination methods. Lower resolution methods can provide valuable structural information, but deriving accurate all atom models from such data is a significant challenge. We are developing computational methods for generating reliable models from limited experimental data. Types of experimental data include: distance constraints provided by MS-crosslinking (described above), distance constraints provided by FRET (described above) and cryo-electron microscopy data. NMR data and x-ray crystallographic data can also be incorporated when available.
We are also developing methodology for computationally designing proteins that specifically bind to an arbitrarily chosen protein surface patch. This is an unsolved problem with very broad potential applications in molecular cell biology, therapeutics, and diagnostics. Given a target surface patch on a protein of known structure, we begin by docking disembodied amino acid sidechains against the surface to identify crevices and pockets where favorable sidechain-target protein interactions can be made. Next, we search through a large set of stable protein scaffolds for one that can position these "hotspot" interacting residues in the proper orientation for binding, while at the same time having global shape complementarity with the target protein. Finally, we use the standard Rosetta (for a description of Rosetta, click here) protein design methodology to optimize the remaining residues at the interface to maximize the predicted target protein binding affinity. We are looking for collaborations to design specific binding partners to proteins of known structure.