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 #
1U01GM094665-01
Application #
8153580
Study Section
Special Emphasis Panel (ZGM1-CBB-0 (BC))
Project Start
2010-09-30
Project End
2015-06-30
Budget Start
2010-09-30
Budget End
2011-06-30
Support Year
1
Fiscal Year
2010
Total Cost
$973,155
Indirect Cost
Name
Albert Einstein College of Medicine
Department
Type
DUNS #
110521739
City
Bronx
State
NY
Country
United States
Zip Code
10461
Ingram, Jessica R; Blomberg, Olga S; Rashidian, Mohammad et al. (2018) Anti-CTLA-4 therapy requires an Fc domain for efficacy. Proc Natl Acad Sci U S A 115:3912-3917
Lázár-Molnár, Eszter; Scandiuzzi, Lisa; Basu, Indranil et al. (2017) Structure-guided development of a high-affinity human Programmed Cell Death-1: Implications for tumor immunotherapy. EBioMedicine 17:30-44
Samanta, Dibyendu; Guo, Haisu; Rubinstein, Rotem et al. (2017) Structural, mutational and biophysical studies reveal a canonical mode of molecular recognition between immune receptor TIGIT and nectin-2. Mol Immunol 81:151-159
Liu, Weifeng; Ramagopal, Udupi; Cheng, Huiyong et al. (2016) Crystal Structure of the Complex of Human FasL and Its Decoy Receptor DcR3. Structure 24:2016-2023
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
Jeon, Hyungjun; Vigdorovich, Vladimir; Garrett-Thomson, Sarah C et al. (2014) Structure and cancer immunotherapy of the B7 family member B7x. Cell Rep 9:1089-98
Liu, Weifeng; Zhan, Chenyang; Cheng, Huiyong et al. (2014) Mechanistic basis for functional promiscuity in the TNF and TNF receptor superfamilies: structure of the LIGHT:DcR3 assembly. Structure 22:1252-1262
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
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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