PSILO / AlphaFold Structures / Macromolecular Repository / Visualization / Pocket Similarity / Project Family / Family Management

MOE Project Families represent a uniquely powerful tool in structure-based drug design. Derived from a carefully curated multi-sequence alignment and a reference file of 3D protein structures that highlights critical structural motifs, these families represent a source of structural insight for drug discovery efforts. When MOE protein families are hosted on the web-based macromolecular structural analysis and visualization platform, PSILO, these ‘PSILO families’ are automatically updated to include recently deposited structures. Following the adoption of a federated database architecture, this enables the seamless integration of both experimental and in silico structures from across the public domain and proprietary sources into PSILO families in a fully automated fashion. Moreover, following a tightened integration between MOE and PSILO, it is now possible to consume PSILO Families directly in MOE - ensuring an evergreen source of protein structural data which is readily available to all via the MOE client application. In this webinar we will briefly introduce PSILO and the creation and maintenance of PSILO Families. We will briefly review the federated database architecture, highlighting how it enables the inclusion of multiple sources (e.g. RCSB, AlphaFold) into the PSILO Family process. Finally, we will demonstrate how to connect MOE and PSILO to enable PSILO functionality directly from within the MOE client, including the surfacing of PSILO Families.

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 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.

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).

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.

SAR Analysis / Pharmacophores / Psychedelics / Virtual Screening

Psychedelic compounds are powerful substances that alter cognitive and sensory functions. Psilocybin (magic mushrooms), mescaline (peyote cactus) and Lysergic acid diethylamide (LSD) are tryptamine- and phenethylamine-based classical psychedelic compounds which primarily act as agonists and partial agonists against the serotonin 5-HT2A receptors. The overall hallucinogenic properties of psychedelic compounds are highly sensitive to structural features of the compounds and subject to cross-reactivity with monoaminergic receptors. To probe the SAR space of serotonergic hallucinogens, we have applied matched molecular pairs analysis in conjunction with conformational analysis to determine key pharmacophoric elements that contribute to agonist/partial agonist behavior.

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.