SAN FRANCISCO Area
November 16, 2017
||Seaport Conference Center|
459 Seaport Ct., Redwood City, CA, 94063, United States
|Complimentary continental breakfast and lunch will be provided.|
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Antibody Modeling and Protein Engineering in MOE
The course covers approaches for structure-based antibody design and includes protein-protein interactions analysis, in silico protein engineering, affinity modeling and antibody homology modeling. The interaction of a co-crystallized antibody-antigen complex will be studied by generating and examining the molecular surfaces and visualizing protein-protein interactions in 3D and 2D. Antibody properties will be evaluated using specialized calculated protein property descriptors and analyzing protein patches. The application of protein engineering tools for homology modeling and conducting property optimization of antibodies in the context of developability will be studied. Antibody optimization examples will include identification of glycosylation sites and analysis of correlated pairs using a specialized antibody database. An approach for humanizing antibody homology models will be discussed. All the steps necessary for producing and assessing antibody homology models will be described.
Biologics: Protein Alignments, Modeling and Docking
The course covers methods for aligning protein sequences, superposing structures, homology modeling fusion proteins and conducting protein-protein docking. In particular, an approach for aligning and superposing multiple structures will be described for determining structural and surface protein variations in relation to protein property modulation. A method for grafting and refining antibody CDR loops as well as using a knowledge-based approach to scFv fusion protein modeling using the MOE linker application will be described. An approach to generate homology models of a murine antigen structure from a human template as well as protein-protein docking of an antibody to an antigen will be discussed. A QSAR model for predicting and analyzing protein/biologics solubility will be described.
Talk: Prediction of Protein-Protein Binding Sites and Epitope Mapping
Computer modeling of protein-protein interactions plays an increasingly
important role in studies of biologics. This work presents a method
for identifying important interaction sites in protein interfaces and
carrying out epitope mapping using the MOE software package. An
analysis is carried out of molecular properties mapped onto the protein
surface to determine patches which play a role in determining protein
properties and binding interactions. A robust first-principles docking
calculation is used to generate an ensemble of protein-protein poses
which sample the space of relative orientations. An interaction
fingerprint encoding the set of contacts between surface patches of
different types is used to generate pose clusters which are ranked by
ensemble free energy and used to extract the consensus interactions
which comprise the predicted epitope for each cluster. This
methodology can be combined with experimental data to bias pose
generation, cluster ranking, and epitope selection in an integrated
process to generate high-quality models. We present a case study in
which hydrogen-deuterium exchange data are used to extract the key
residue interactions from calculations performed on an ensemble of
homology models of the interacting chains.
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