There is no cost to attend but pre-registration is required as seats are limited. Registrations will be processed and accepted first-come, first-served. No previous MOE software experience is required to attend.
Peptide Complex Preparation / Protein-Peptide Interaction Analysis / Surfaces and Maps / Peptide Sequence Optimization / Non-Natural Amino Acids / Conformational Searching / Peptide-Protein Docking / Protein-Peptide Interaction Fingerprints
MOE databases / Molecular Descriptors / Sorting and Coloring Plots / Clustering | Diverse Subset Selection / QSAR Modeling / Binary QSAR / Substructure Searching / Molecular Fingerprints / Similarity Searching
Protein Alignments and Superposition / Loop and Linker Modeling / Homology Modeling / Protein-Protein Docking / Epitope Analysis / Protein Properties / Protein Solubility Prediction / Protein Patches (2D and 3D) / Biologics QSAR/QSPR Modeling
Scaffold Hopping / Fragment Linking / Ligand Growing / R-Group Screening / Bioisosteric Transformations / Pharmacophore Modeling / Fragment Databases
Pharmacophore Modeling / Docking / Fragment-Based Design / Scaffold Replacement / R-Group Screening / Project Search / Protein-Ligand Interaction Fingerprints (PLIF)
The course describes advanced SBDD workflows in drug discovery projects and encompasses a range of topics from pharmacophore query generation to protein-ligand interaction fingerprints. More specifically, the course 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).
MOE databases / Calculated Descriptors / Fingerprints / QSAR Modeling / Binary QSAR / Similarity Searching / Consensus Modeling
The course will introduce the cheminformatics applications included in MOE, based within its Database Viewer (DBV). Using a dataset of logBB (blood-brain barrier permeation) values, we will import/export data from/to various formats (SDF, SMILES etc.), calculate molecular descriptors, analyse and visualize data, and create QSAR and binary-QSAR models. We will then perform fingerprint-based similarity searching, clustering, diverse subset selection and consensus modeling.
Structure Preparation / Non-natural Amino Acids / Conformational Searching / Distance Restraints / Peptide-Protein Docking / Protein-Ligand Interaction Fingerprints
The course covers methods for analyzing and optimizing peptide-protein interactions in the active site. Topics related to peptide-protein structure preparation, peptide sequence optimization using natural and non-natural acids and conformational analysis will be discussed. Peptide-protein docking and protein-ligand interactions to analyze contact points will be described. The course will also cover advanced conformational searching using distance restraints.
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 molecular surfaces and visualizing protein-protein contacts in 3D. Antibody properties will be evaluated using specialized calculated protein property descriptors and analyzing protein patches. The application of protein engineering tools for affinity and property optimization of antibodies in the context of developability will be studied. Antibody homology modeling optimization examples will include identification of glycosylation sites and their selective modification using a specialized MOE Project antibody database. All the steps necessary for high throughput antibody homology modeling workflow from sequence to structure to property calculations for developability analysis will be described.
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 and the reaction based combinatorial builder will be presented. The use of pharmacophores and 2D/3D descriptors to guide drug design processes will also be discussed.