Pharmacophore Modeling / Pharmacophore Consensus / Flexible Alignments / Pharmacophore Searching / Protein-Ligand Interaction Fingerprints (PLIF)

The course describes the application of pharmacophores in drug discovery projects and encompasses a range of topics from pharmacophore query generation to pharmacophore refinement and searching of structural databases. A new approach based on Extended Hückel Theory (EHT) for producing pharmacophore models with encoded interaction energies in the context of ligand-based and structure-based projects will be described. The generation and analysis of protein-ligand interaction fingerprints (PLIF) will be presented along with the application of PLIF for producing pharmacophore queries.

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.

High-Throughput Docking / HPC / SAR Analysis / NMR Spectral Modeling / QM/MM / Molecular Dynamics

The latest release of MOE contains some key upgrades to its comprehensive package of applications for computational small molecule drug discovery. MOE’s docking application has been speeded up and efficiently parallelized, and is now able to take full advantage of HPC and Cloud architectures for high-throughput experiments. MOEsaic, for analyzing and mining small molecule SAR data, now enjoys enhanced prediction capabilities, suggesting compounds that may have more desirable properties given the available data, and sharing MOEsaic projects among teams has been made easier. These new developments, along with others involving MOE’s NMR spectral modeling application, molecular dynamics, a new QM/MM capability, and some user interface enhancements, will be described in this webinar.

Antibody Modeling / Antibody Properties / Developability / Protein Liability / HPC / Protein Family Databases

Improvements in structure and property predictions of proteins and antibodies continue in the new release of MOE. The IMGT scheme for antibody sequence annotation has been implemented, and the antibody modeler application has been enhanced in a number of ways, including its ability to use HPC resources. Conformational ensemble averaging in antibody structures is now used to calculate more accurate descriptors, which may be used to derive more robust models for protein liability and other developability-related properties for biological therapeutics. This webinar will cover these capabilities, along with introducing some new protein family databases.

Inputting Multiple Sequence Data / Mutation Frequencies / Targeted Mutant Libraries / Protein Engineering

Computational techniques for optimizing the affinity of a potential therapeutic protein or antibody are described. Experimental results from phage display may be read into MOE and analyzed to identify promising mutation sites and specific mutations, which can then be explored further individually and in correlation to yield potential new leads with enhanced efficacy. Workflows for these procedures will be described and demonstrated.

Structure Preparation / Force Field / Solvation / AMBER / NAMD / Visualization / Player

Setting up a Molecular Dynamics simulation starting from a protein PDB structure can be challenging. It involves: data preparation, force field parameterization, running protocols and trajectory analysis/visualization. MOE provides a streamlined interface which allows for easy setup, execution and visualization of MD trajectories via AMBER, NAMD or the internal MD engine. In this webinar, the complete workflow to run MD simulations will be introduced.

Structure Preparation / Protein Binding Site Visualization / Template-Based Docking / Covalent Docking / Pharmacophores / Protein-Ligand Interaction Fingerprints (PLIF) / Multiple Processor Calculations

Advanced docking workflows encountered in drug discovery projects will be described, which include a range of related topics from the application of pharmacophore constraints in docking to the analysis of protein-ligand interaction fingerprints (PLIF) generated from docked poses. Examples include: (1) general docking with applied pharmacophore constraints, (2) template-based docking using a scaffold or fragment to guide placement, and (3) covalent docking to generate, rank and score ligands that are covalently bound to a protein/receptor. Leveraging multiple processing capacity 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.

Scaffold Replacement / Fragment Linking / R-Group Screening / Medicinal Chemistry Transformations / Fragment Libraries / Pharmacophore Models

Fragment-based drug design (FBDD) is a key approach in the discovery of high-quality drug candidates. As a complement to biophysical FBDD methods, in silico 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 describes in silico FBDD methods ranging from scaffold-hopping to fragment linking and growing in the receptor active site. A method for generating a series of closely related derivatives through rule-based medicinal chemistry transformations is presented. The use of pharmacophore models and 2D/3D descriptors to guide in silico FBDD processes is also discussed.

Protein Alignments and Superposition / Loop and Linker Modeling / Homology Modeling / Protein- Protein Docking / Protein Solubility Analysis / 2D Hot Spot Mapping / PLIF / Biologics QSAR Modeling

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. A QSAR model for predicting and analyzing protein/biologics solubility will be described.

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 the molecular surfaces and visualizing protein-protein interactions in 3D and 2D. Antibody properties will be evaluated using specialized calculated protein property descriptors and analyzing protein patches. The application of protein engineering tools for homology modeling and conducting property optimization of antibodies in the context of developability will be studied. Antibody optimization examples will include identification of glycosylation sites and analysis of correlated pairs using a specialized antibody database. An approach for humanizing antibody homology models will be discussed. All the steps necessary for producing and assessing antibody homology models will be described.

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.

Protein Engineering / Protein Properties / Developability / Hot Spot Analysis

The workshop 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 the molecular surfaces and visualizing protein-protein interactions in 3D and 2D. Antibody properties will be evaluated using specialized calculated protein property descriptors and analyzing protein patches.

Protein-Protein Docking / Molecular Surfaces / Protein Patches / Interaction Fingerprints / Clustering / Epitope Analysis

The MOE Protein docking application is used to map epitopes and other protein-protein interfaces (PPI). This automatically calculates a PPI fingerprint for each pose. The poses are clustered using the fingerprint, and epitope residues are identified from the top ranking clusters. The poses can then be annotated in the MOE Window, for browsing through all the top epitopes.

Activity Data Mining / SAR / Matched Molecular Pairs / R-group Analysis / R-group Profiling / Free-Wilson Analysis / Compound Suggestions

Matched Molecular Pair analysis on an activity data set enables finding activity cliffs and bioisosteres, providing insight on parts of a molecule that must remain fixed or which can be varied to advance a campaign. If activity against multiple related targets is present, selectivity information can also be gleaned. Analyzing and profiling the functional groups present in a data set can point up useful routes to improving properties such as those relevant for DMPK. This webinar will demonstrate MOEsaic, which enables these analyses in a browser interface which is easy to use and interpret, and which takes analysis one step further by suggesting potential new compounds, not present in the original data sets, which are most likely to display desirable activity and property profiles.

Molecular Fingerprints / Consensus Models / Pharmacophore Elucidation / 3D Query Generation

Different reverse fingerprints can be combined to produce a more robust identification of important molecular motifs. This webinar covers the basics of combining fingerprints using consensus model theory, and demonstrates it application to motif detection and pharmacophore query generation.