MOE Workshop Series

North America

SAN FRANCISCO Area
November 16, 2017

Location: Seaport Conference Center
459 Seaport Ct., Redwood City, CA, 94063, United States
MAP
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.


For questions, please contact:
Raul Alvarez
Senior Marketing Manager