Virtual Screening Compound Libraries / Descriptors, Fingerprints and QSPR Modeling / Pharmacophore Modeling / Template-based Docking / Compound Design

The course covers the suite of MOE applications which can be applied to small-molecule virtual screening. Topics include the preparation of small molecule databases for virtual screening, filtering databases based on substructure matching and property values, building QSAR/QSPR models and fingerprint similarity models as database filters, pharmacophore query creation and searching, and small-molecule docking. These tools are used in conjunction to present a complete virtual screening workflow. The creation of de novo structures using the MOE Scaffold Replacement and MOE Medchem transformation applications is also covered.

Protein Annotation / Protein Patches / Virtual Mutagenesis / Antibody Homology Modeling / Protein Properties / Developability

The workshop covers the application of computational tools for modeling the structures of antibodies, for humanization, and for optimization of properties to enhance developability. Examples will include the identification of glycosylation sites and analysis of correlated pairs using a specialized antibody database. The calculation of protein properties and their optimization to facilitate developability as a product will also be covered.

Macromolecular Repository / 3D Query Searching / Pocket Similarity / Display Electron Density / Central Repository / Specialized Protein Databases

PSILO® is a database system that provides an easily accessible, consolidated repository for macromolecular and protein-ligand structural information. The course will describe the application of PSILO® for mining data from macromolecular and protein-ligand structures. Approaches to query generation and search result navigation in PSILO will be covered in detail; for example, 3D contact searching and protein pocket similarity searching.

MOE databases / Calculated Descriptors / Fingerprints / QSAR Modeling / Binary QSAR / Similarity Searching / Consensus Modeling

The course will introduce cheminformatics applications using the MOE software. The topics covered include MOE database manipulation, importing/exporting data to various formats (SDF, SMILES), molecular descriptor calculation, data analysis and visualization, QSAR and binary-QSAR modeling, fingerprint-based similarity searching, clustering, diverse subset selection and consensus modeling.

Homology Modeling / Protein Properties Calculations / QSAR/QSPR Modeling / Protein Patch Analysis

The course will cover a typical protein/biologics solubility prediction workflow. First, homology models will be generated for a series of Adnectin sequences. Protein properties will then be calculated for the modeled Adnectins, and the correlation between different properties and experimental solubility data will be investigated. Next, QPSR models will be generated to predict solubility based on the calculated protein properties. Finally, Protein Patch Analysis will be used visualize the differences between structures with varying solubility.

Structure Preparation / Protein-Peptide Interaction Analysis / Conformational Searching / Protein-Peptide Docking / Protein-Ligand Interaction Fingerprints

The course will cover methods for protein-peptide interaction analysis, and protein-peptide docking. Conformational searching of peptide structures will also be discussed, and a method for identifying contact points using Protein-Ligand Interaction Fingerprints (PLIFs) will be described.

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.