Molecular Graphics / Visual Effects / Publication-Quality Images

This webinar covers the advanced graphics capabilities of MOE. Topics include how to render molecular objects and surfaces, display property maps and grid, adjust the lighting, backgrounds and visual effects of an image, and how to produce publication-quality image files. Advanced topics include exporting to 3D printers and other embedded 3D file formats.

Pharmacophore Modeling / Docking / Fragment-based Design / Scaffold Replacement / R-Group Screening / Project Search / Protein-Ligand Interaction Fingerprints (PLIF)

The workshop describes SBDD workflows in drug discovery projects and encompasses a range of topics from pharmacophore query generation to protein-ligand interaction fingerprints. More specifically, the workshop will cover the application of pharmacophores in the context of protein-ligand docking, scaffold replacement and R-group screening. A method for querying a 3D project database will also be presented along with the generation and analysis of protein- ligand interaction fingerprints (PLIF).

Automated Pharmacophore Generation / Binding Site Analysis / Protein Ensembles

An automated approach to summarize pocket shapes and binding hot-spots from a collection of protein structures is presented. Pocket shapes are described using pocket volumes derived from Alpha Sites and molecular surfaces. Binding hot-spots are located using pharmacophore features generated by AutoPH4. Collections of pocket volumes and pharmacophores are analyzed using feature densities which map onto a universal grid the fraction of structures that possess a given feature at each point in space. Regions with high pharmacophore feature densities identify the most persistent interaction binding hot-spots over the collection of structures. Pocket volume densities detect and classify binding site regions into core pockets and sub-pocket regions. Fingerprints that represent pocket shape, sub-pocket presence and pharmacophore feature presence are derived and used to cluster and classify multiple protein structures using standard fingerprint clustering tools. Application of the method to fragment-based drug design, minor pocket detection, selectivity mapping, binding-mode classification and custom docking scoring function creation is presented.

Antibody Modeling / Developability / Liability / Aggregation

Antibody candidates often have poor biophysical properties and/or chemical liabilities that cause downstream developability issues. In this demonstration, we will model a mouse antibody and identify liability motifs using such as glycosylation PTM sites and we will propose statistically appropriate mutations. We will then model a panel of 14 IgG4 candidates and select one for improved developability in terms of aggregation and solubility using high-throughput antibody modeling and property calculations.

Molecular Surfaces and Maps / Ligand Interactions / Docking / Ligand Optimization / Ligand Selectivity / Protein Alignments and Superposition

The course covers MOE applications for interactive structure based design. Examples include active site visualization, protein-ligand contact analysis and ligand modification/optimization in the receptor pocket. Use of the docking module and its application to assess ligand flexibility will be discussed. A protocol for aligning and superposing protein complexes in the context of protein selectivity will be studied.

Scaffold Hopping / Fragment Linking / Ligand Growing / R-Group Screening / Medicinal Chemistry Transformations / Pharmacophores / Fragment Databases

The course will focus on fragment-based drug design tools in MOE. Combinatorial fragment design and scaffold replacement in the receptor active site will be covered in detail, along with approaches for fragment linking and growing. A method for generating a series of closely related derivatives through medicinal chemistry transformations will also be presented. Finally, the use of pharmacophores and 2D/3D descriptors to guide drug design processes will be discussed.

Protein Engineering / Protein Properties / Developability / Hot Spot Analysis / Antibody Modeling / Humanization / Molecular Surfaces

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.

Alignments and Superposition / Loop and Linker Modeling / Homology Modeling / Protein Docking / Solubility Analysis / 2D Hot Spot Mapping / Protein Ligand Interaction Fingerprints / QSAR Modeling

The course covers methods for aligning protein sequences, superpositioning structures, homology modeling fusion proteins and conducting protein-protein docking. In particular, an approach for aligning and superpositioning 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.