Antibodies play a critical role in the immune system for recognition of foreign intruders. Because of their excellent affinity and specificity, they hav also been exploited as therapeutic molecules and biotechnological components for sensing and assembly. Structures of antibodies in complex with their antigens can yield insight into biological phenomena or drug and disease mechanisms. However, structures of antibodies and antibody-antigen complexes can be difficult, time consuming, and expensive to determine. The proposed research focuses on the computational prediction of the structure of antibodies and antibody-antigen complexes. Computational approaches are particularly important because the repertoire of antibodies in a human patient is far too large for complete structural characterization by experiment. Prior work has isolated the most critical challenges: most of the antibodies in the human repertoire have hypervariable CDR H3 loops longer than that which is predictable using current loop methods;backbone conformational uncertainty and flexibility confound current docking methods;and no current method can quantitatively predict antibody-antigen binding affinities from structure. Thus, the first three aims of the project are to (1) develop new methods to predict the structure of long CDR H3 loops using statistics to identify likely ? turns, (2) develop flexible backbone docking routines using an expanded ensemble approach with a conformational web, and (3) develop methods to quantitatively predict protein-protein binding affinity using improved electrostatics treatments. Finally, the fourth aim will be to (4) use existng and proposed methods to predict structures of antibodies and antibody-antigen complexes for entire polyclonal antibody repertoires. Structures will be predicted for antibody repertoires determined from bone marrow plasma cells of mice immunized against ovalbumin (a food allergen) and enzyme C1s (a therapeutic target for autoimmune diseases and transplant tolerance). Ultimately, these studies will yield insights into immunology, molecular recognition, and design of protein-protein interfaces and vaccines.

Public Health Relevance

Antibodies play a critical role in the immune system for recognition of foreign intruders, and are excellent therapeutic molecules because of their high affinity and specificity. This project investigates computational approaches to determine the three-dimensional structures of antibodies alone and in complex with their target antigens, including specific applications relevant to food allergies and a treatment for transplant rejection autoimmune disorders and inflammatory diseases.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Macromolecular Structure and Function D Study Section (MSFD)
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Preusch, Peter C
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Johns Hopkins University
Engineering (All Types)
Schools of Engineering
United States
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Lensink, Marc F; Velankar, Sameer; Kryshtafovych, Andriy et al. (2016) Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment. Proteins 84 Suppl 1:323-48
DeKosky, Brandon J; Lungu, Oana I; Park, Daechan et al. (2016) Large-scale sequence and structural comparisons of human naive and antigen-experienced antibody repertoires. Proc Natl Acad Sci U S A 113:E2636-45
Kuroda, Daisuke; Gray, Jeffrey J (2016) Shape complementarity and hydrogen bond preferences in protein-protein interfaces: implications for antibody modeling and protein-protein docking. Bioinformatics 32:2451-6
Kuroda, Daisuke; Gray, Jeffrey J (2016) Pushing the Backbone in Protein-Protein Docking. Structure 24:1821-1829
Jiang, Qian; Arnold, Stacey; Heanue, Tiffany et al. (2015) Functional loss of semaphorin 3C and/or semaphorin 3D and their epistatic interaction with ret are critical to Hirschsprung disease liability. Am J Hum Genet 96:581-96
Koehler Leman, Julia; Ulmschneider, Martin B; Gray, Jeffrey J (2015) Computational modeling of membrane proteins. Proteins 83:1-24
Alford, Rebecca F; Koehler Leman, Julia; Weitzner, Brian D et al. (2015) An Integrated Framework Advancing Membrane Protein Modeling and Design. PLoS Comput Biol 11:e1004398
Porter, Justin R; Weitzner, Brian D; Lange, Oliver F (2015) A Framework to Simplify Combined Sampling Strategies in Rosetta. PLoS One 10:e0138220
Weitzner, Brian D; Dunbrack Jr, Roland L; Gray, Jeffrey J (2015) The origin of CDR H3 structural diversity. Structure 23:302-11
Weitzner, Brian D; Kuroda, Daisuke; Marze, Nicholas et al. (2014) Blind prediction performance of RosettaAntibody 3.0: grafting, relaxation, kinematic loop modeling, and full CDR optimization. Proteins 82:1611-23

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