Cloud / AWS / HPC / High-Throughput Screening / Large Scale Calculations / SLURM / Amazon Cluster

Running MOE on the AWS cloud might appear intimidating. It involves: installing the server and software, configuring a workload manager, data preparation, data transfer, job submission and data retrieval. In this webinar we will start from a newly created AWS account and show how easy it is to install an elastic compute cluster ready for MOE. Next we will connect the AWS cluster to the MOE HPC infrastructure to submit jobs from different applications (Dock, Protein Design, Ensemble Protein Properties, etc.) right from the graphical user interface of your local MOE installation. We will monitor the jobs and retrieve the results once the calculations have been completed. In the last part of the webinar we then install a single instance of MOE on AWS and use the GUI via the browser.

Protein Alignments and Superposition / Loop and Linker Modeling / Homology Modeling / Protein- Protein Docking

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

Docking / Pharmacophore Modeling / Fragment-Based Design / Scaffold Replacement / Protein-Ligand Interaction Fingerprints (PLIF)

This workshop will cover some advanced workflows for structure-based design in drug discovery projects. The application of pharmacophores in the context of protein-ligand docking and scaffold replacement will be included, as will the generation and analysis of protein-ligand interaction fingerprints (PLIF). Participants will therefore experience a broad range of computational tools that can be brought to bear for lead generation and optimization.

Scaffold Replacement / Fragment Linking / Ligand Growing / R-Group Screening / Medicinal Chemistry Transformations / Combinatorial Fragment Libraries / Pharmacophore Models / Fragment Databases

Fragment-based drug design (FBDD) is a key approach in the discovery of high-quality drug candidates. As a compliment to biophysical FBDD methods, insilico FBDD uses structure-based approaches to rapidly design and screen large libraries of virtual compounds, allowing for the exploration of a much larger chemical space. The webinar will describe insilico FBDD methods ranging from combinatorial fragment design to scaffold-hopping in the receptor active site, along with approaches for fragment linking and growing. A method for generating a series of closely related derivatives through the reaction-based Combinatorial Library and Medicinal Chemistry Transformations applications in the MOE software will be presented. The use of pharmacophore models and 2D/3D descriptors to guide insilico FBDD processes will also be discussed.

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.

Solvent Analysis / 3D-RISM / Lead Optimization / Water Placement

The investigation of water molecule placements, both real and potential, around a protein-ligand complex can provide possible routes for enhancing ligand affinity. For example, calculations using the 3D-RISM method on a crystallographically determined complex enable the identification of water molecules whose displacement by a modified ligand may enhance binding. The theory behind the method, its application and validation will be presented.

Structure Preparation / Sidechain Rotamer Exploration / Electron Density Maps / X-Ray / CryoEM / Solvent Analysis with 3D-RISM

The course will cover methods for evaluating, analyzing and refining protein models derived from electron density data. Topics related to protein structure preparation and side-chain conformational analysis and placement will be discussed. Visualization and interpretation of electron density maps (X-ray/CryoEM) for assessing protein models will be described. The 3D-RISM method for predicting and refining the placement of solvent molecules in protein models will also be presented.

Macromolecular repository / 3D query searching / Pocket similarity / Display electron density / Central repository / Specialized protein databases

PSILO® is a web-based platform for the deposition and analysis of macromolecular structural information. The workshop will describe the application of PSILO® for mining biomolecular data. 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. The PSILO and MOE platforms are tightly integrated, and the ability to perform PSILO search queries directly from within MOE will also be described.