The Immune Function Network (IFN), a consortium of immunologists, geneticists, computational biochemists, and high throughput structural biologists, is committed to the coordinated structural, in vitro biochemical and in vivo ftinctional analyses of the secreted molecules and ectodomains of cell surface molecules that control adaptive and innate immunity. These molecules are validated targets for immime-based therapies to treat a wide range of autoimmune diseases, infectious diseases and cancers, and are indeed therapeutics in their own right. The IFN, subscribes to a series of underlying principles: 1) target selection supports hypothesis-driven structural biology by identifying unique primary amino acid sequence signatures that predict unique structural features, which are in turn responsible for unique biological function;2) the high resolution structures of these molecules are exceptionally revealing as they inform on oligomeric state, valency, specificity and general architectural features, all of which are fundamental mechanistic contributors to immune function;3) these structures can be readily exploited by biochemical and computational approaches to guide the generation of molecules with specifically altered biochemical and biophysical properties;4) these "surgically-defined" mutants represent novel reagents that will lead to new mechanistic insights in in vitro cellbased assays and in vivo animal models of disease;5) the molecules predicted to be most informative will guide the generation of knock-in mouse models to provide in vivo structure-function relationships for innate and adaptive immunity. This "Atoms-to-Animals" approach represents the next step in the evolution of Structural Biology as it maximally leverages structural information and provides a comprehensive and powerful paradigm for the study of normal, pathological, and therapeutic immune responses.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01GM094665-05
Application #
8708899
Study Section
Special Emphasis Panel (ZGM1-CBB-0)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
5
Fiscal Year
2014
Total Cost
$144,274
Indirect Cost
$45,273
Name
Albert Einstein College of Medicine
Department
Type
DUNS #
110521739
City
Bronx
State
NY
Country
United States
Zip Code
10461
Liu, Weifeng; Vigdorovich, Vladimir; Zhan, Chenyang et al. (2015) Increased Heterologous Protein Expression in Drosophila S2 Cells for Massive Production of Immune Ligands/Receptors and Structural Analysis of Human HVEM. Mol Biotechnol 57:914-22
Samanta, Dibyendu; Almo, Steven C (2015) Nectin family of cell-adhesion molecules: structural and molecular aspects of function and specificity. Cell Mol Life Sci 72:645-58
Vallat, Brinda; Madrid-Aliste, Carlos; Fiser, Andras (2015) Modularity of Protein Folds as a Tool for Template-Free Modeling of Structures. PLoS Comput Biol 11:e1004419
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Yap, Eng-Hui; Rosche, Tyler; Almo, Steve et al. (2014) Functional clustering of immunoglobulin superfamily proteins with protein-protein interaction information calibrated hidden Markov model sequence profiles. J Mol Biol 426:945-61
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Khafizov, Kamil; Madrid-Aliste, Carlos; Almo, Steven C et al. (2014) Trends in structural coverage of the protein universe and the impact of the Protein Structure Initiative. Proc Natl Acad Sci U S A 111:3733-8
Lamont, Deanna; Mukherjee, Gayatri; Kumar, P Rajesh et al. (2014) Compensatory mechanisms allow undersized anchor-deficient class I MHC ligands to mediate pathogenic autoreactive T cell responses. J Immunol 193:2135-46
Padlan, Camille S; Malashkevich, Vladimir N; Almo, Steve C et al. (2014) An RNA aptamer possessing a novel monovalent cation-mediated fold inhibits lysozyme catalysis by inhibiting the binding of long natural substrates. RNA 20:447-61
Pujato, Mario; Kieken, Fabien; Skiles, Amanda A et al. (2014) Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes. Nucleic Acids Res 42:13500-12

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