Session TOE. There are 4 abstracts in this session.



Session: TECHNOLOGY: NEW DEVELOPMENTS IN STRUCTURAL PROTEOMICS, time: 3:00 PM - 3:25 PM

Pending

Jim Bruce

Pending
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Session: TECHNOLOGY: NEW DEVELOPMENTS IN STRUCTURAL PROTEOMICS, time: 3:25 PM - 3:50 PM

Next-generation antibody proteomics: technologies, curiosity-driven science and drug therapeutics

Yi Shi

Antibodies are among the most widely used biologics for basic research and have been the major driving force for disease diagnosis and therapeutics. Despite the importance, high-quality antibodies remain very sparse. Camelid VHH single-chain antibodies (nanobodies (Nbs)) are compelling new class of antibodies that are characterized by their small size, ease of bioengineering and production, superior solubility and thermo-stability, as well as low toxicity. Although Nbs are considered promising next generation agents for biomedical research and drug therapeutics, reliable analysis of Nb proteomes remain challenging. Here we report the development of hybrid proteomics and informatics tools that enable in-depth, high-throughput identification, characterization and structural mapping of antigen-specific Nb repertoires. With our approach, thousands to tens of thousands of high-quality, antigen-specific Nb families can be confidently identified and characterized based on their physicochemical properties. A significant fraction has been demonstrated to be outstanding binders that obtain ultrahigh affinity and molecular specificity. In addition, by integrative structural proteomics approaches, we have systematically investigated the structural basis and molecular underpinnings of antigen-antibody interactions, and have revealed the exceptional diversity and surprising structural versatility of humoral immunity. Finally, we will briefly discuss our efforts towards developing novel Nb therapy. We envision that these methods and stories of our exploratory journey, from discovery of novel biomolecules to drug therapeutics- all guided by mass spectrometry - will benefit proteomics research.
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Session: TECHNOLOGY: NEW DEVELOPMENTS IN STRUCTURAL PROTEOMICS, time: 3:50 PM - 4:05 PM

Optimizing a proteome scale measurement of protein fold stability.

Ji Sun Stella Park; Hsien-Jung Lavender Lin; Nathan Zuniga; Kim Wagstaff; John Price
Brigham Young University, Provo, UT

Age-related diseases, such as neurodegenerative disorders, heart disease, and cancer, are increasing with the average lifespan of people. Understanding the mechanisms of aging that contribute to the development of the diseases will eventually lead to treatment of diseases. Aging is directly related to the homeostasis of proteins (proteostasis), where loss of proteostasis becomes more profound as we age. Interventions that reduce the aging rate preserve proteostasis. We want to measure the fold stability as a metric of quality of each protein found in the body. The assay will be used to compare the abnormally functioning protein’s stability and quality to the one found in the assay to see how we can improve its functions back to normal. Our method consists of creating a denature curve. Data collected by denaturing proteins at different concentration and incubation time of denaturant Guanidine chloride (GdmCl) will give a denature midpoint of each protein. The midpoint is where the ratio between folded and denatured protein is at 1:1 and the stability of each protein will be determined by the location of the midpoint on the denature curve. To make the denature curve we are using different modifications to target amino acids to measure how much of the protein is denatured at each concentration. We tested a variety of amino acid modifiers for efficiency in labeling amino acids during denaturation. The results of these tests are compared to identify an optimal labeling method that efficiently and reproducibly measured amino acid accessibility and accurately reported protein fold stability.

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Session: TECHNOLOGY: NEW DEVELOPMENTS IN STRUCTURAL PROTEOMICS, time: 4:05 PM - 4:10 PM

Visualizing the Cancer Conformational Landscape with Covalent Protein Painting

Casimir T. Bamberger; Jolene Dietrich; Salvadore Martinèz-Bartholomé; John Yates
Scripps Research Institutes, La Jolla, CA

Because protein-protein interactions and protein conformations change during tumorigenesis, there may be cancer-specific structural changes that hold promise for the development of a novel class of anti-cancer drugs based on structural alterations rather than protein abundance.  To scan a proteome for aberrant protein folds we developed “covalent protein painting” (CPP).  CPP labels solvent exposed lysine residues in proteins in vivo with two isotope-defined methyl groups and subsequently labels solvent excluded lysine residues with a second, isotopically distinct set of methyl groups.  Subsequent bottom-up proteomics with mass spectrometry is used to identify lysine residues and quantify the relative proportion of protein molecules in which a lysine residue was inaccessible. We compared the breast cancer cell line MCF10A to MCF10A-H1045R, an isogenic cell line in which a single tumorigenic mutation in the catalytic subunit of the phosphatidyl inositol kinase p110a, or PI3KCA(H1045R), was inserted.  2,821 lysine sites in 1,566 distinct protein groups were detected and compared between the two cell lines.  We identified 24 significantly altered lysine sites in different proteins, several of which suggested altered dynamics of the cytoskeleton.  Next, we extended the number of different tumor cell lines measured with CPP to all 60 NCI cancer cell lines and quantified > 8,000 lysine sites in > 3,000 proteins.  Data analysis revealed a complex and mostly redundant relationship between 461 protein sequence-altering somatic mutations in all NCI60 cells and the conformational changes in the proteome they induced, which was limited to < 100 lysine sites in the current dataset.  Finally, we identified 49 lysine sites that are potentially predictive of the cytotoxicity of 300 different small molecules.  These lysine sites are further evaluated as conformational biomarkers to predict drug efficacy or as novel targets to develop cancer conformational landscape specific anti-cancer drugs.

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