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.
Structure preparation / Non-natural amino acids / Protein Design / Conformational searching / Distance restraints / Peptide-Protein docking / Protein-Ligand Interaction Fingerprints (PLIFs)
This workshop focuses on methods for analyzing and optimizing peptide-protein interactions in the binding site. Participants will learn peptide-protein structure preparation, peptide sequence optimization using both natural and non-natural amino acids, and perform conformational analysis. Peptide-protein docking will be demonstrated, along with tools for analyzing protein-ligand interactions to assess contact points. Advanced conformational searching techniques using distance restraints will also be described.
Alignments and superposition / Loop and linker modeling / Protein-Protein docking / Protein-Ligand Interaction Fingerprints (PLIFs) / Epitope analysis / Homology modeling / Solubility analysis / QSAR modeling / 2D hot spot mapping
This workshop covers essential methods for aligning protein sequences, superposing structures, loop modeling, building fusion protein models, and conducting protein-protein docking. Participants will learn techniques for grafting and refining antibody CDR loops, as well as using a knowledge-based approach to scFv fusion protein modeling with the Linker Modeler application. The session will also cover protein-protein docking of an antibody to an antigen and epitope mapping. Finally, the workshop will guide participants through a complete workflow for generating a QSAR model to predict and analyze protein/biologics solubility.
Antibody structure prediction / Conformational ensembles / Descriptor calculations / Property prediction / Developability / Cloud computing
Predicting potential liabilities such as aggregation or viscosity is a key step in monoclonal antibody development. Computational property prediction methods are routinely used in the selection and optimization of candidate antibodies. High-quality property prediction involves prediction of ensembles of 3D structures at specified pH to reduce sensitivity to single conformational states. We will present 3dpredict/Ab, a solution that enables ensemble-based predictions of antibody developability descriptors and putative liabilities. 3dpredict/Ab allows for out-of-the-box SaaS automation and integration of such complex simulations of hundreds or thousands of sequences, making them accessible and efficient.
Protein-ligand interactions / Protein-ligand docking / Pharmacophore modeling / Template-based docking / Scaffold replacement / R-group exploration / Bioisosteric transformations / Ligand properties / PLIFs
This workshop presents common molecular modeling and design techniques for identifying, optimizing, and prioritizing small-molecule drug candidates. The workshop begins by describing structure preparation and pocket analysis to understand key protein-ligand interactions. Participants will explore template-based docking of congeneric series and pharmacophore-guide docking (to preserve key interactions) to predict how small molecules bind to a protein target. This workshop also presents a series of de novo fragment-based drug design applications, focusing on scaffold hopping and fragment growing methods to generate novel compound ideas, optimize structures in the pocket, and score them. It also discusses the use of molecular descriptors, protein-ligand interaction fingerprints (PLIFs), and pharmacophore models to guide the drug design process. Finally, a method for generating closely related analogs through bioisosteric replacements is presented.
PSILO / Central macromolecular repository / 3D Query searching / Pocket similarity / MOE-project / Project search / Organizing and centralizing project data / Protein family modeling
This workshop covers the searching and analysis of structural data in PSILO®, as well as the organization and mining of structural families using MOE-Project. Participants will learn to consolidate macromolecular and protein-ligand structural data, generate and navigate advanced queries, and streamline analysis with 3D contact and protein pocket similarity searches. The session also covers organizing structure-based drug design projects, aligning protein families, configuring MOE-Project databases, and using Protein-Ligand Interaction Fingerprints (PLIF) analysis to compare ligand binding modes. Attendees will gain practical skills for efficient structural data mining and project management.
MOEsaic / Matched Molecular Pairs / R-group analysis / Similarity and substructure searching / Multi-parameter optimization / Free-Wilson analysis / Combinatorial Library Enumeration / Multi-component reactions sketch / Reagent catalogs filtering
This workshop explores some essential ligand-based methods for guiding drug discovery projects. Participants will learn how to efficiently use MOEsaic to perform SAR analyses of compound datasets, using approaches such as R-group profiling and matched molecular pairs (MMP) analysis, to identify relationships within chemical series. The session highlights computational strategies for extracting meaningful insights from structure-activity data to support informed decision-making in drug design. The workshop also introduces the CLE application as a powerful tool for streamlining the search of available reagent catalogs using multi-component chemical reactions. It demonstrates how to apply a reaction both as a query and as a transformation to efficiently enumerate all possible product combinations. The session covers methods for inspecting, filtering, and exporting reagents and products, including catalog IDs, for synthesis.