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 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.

MOE project / specialized protein families / project search / Organizing and centralizing project data / protein family modeling

The course covers MOE-Project, the automatic protocol for organizing SBDD project data. Topics include preparing protein data, using a graphical interface to create a project database of aligned and superposed protein structures, applying the MOE Project Search panel to mine the project data and analysis of molecular interactions using Protein-Ligand Interaction Fingerprints (PLIF).

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.

MOE databases / Calculated Descriptors / Fingerprints / QSAR Modeling / Binary QSAR / Similarity Searching / Consensus Modeling

The course will introduce cheminformatics applications using the MOE software. The topics covered include MOE database manipulation, importing/exporting data to various formats (SDF, SMILES), molecular descriptor calculation, data analysis and visualization, QSAR and binary-QSAR modeling, fingerprint-based similarity searching, clustering, diverse subset selection and consensus modeling.

MOE Databases / Descriptors / Fingerprints / QSPR Modeling / Pharmacophore Modeling / Template-Forced Docking / Scaffold Replacement / MedChem Transformations

The course covers the suite of MOE applications which can be applied to small-molecule virtual screening. Topics include the preparation of small molecule databases for virtual screening, filtering databases based on substructure matching and property values, building QSAR/QSPR models and fingerprint similarity models as database filters, pharmacophore query creation and searching, and small-molecule docking. These tools are used in conjunction to present a complete virtual screening workflow. The creation of de novo structures using the MOE Scaffold Replacement and MOE Medchem transformation applications is also covered.

PROTAC / Targeted Protein Degradation / Ternary Complexes / Protein-Protein Docking

Bifunctional small molecules known as PROTACs (Proteolysis-Targeting Chimeras) have recently shown great potential in drug discovery. Their mechanism of action involves degradation of a target protein rather than its inhibition, and thus computational modeling of PROTAC-mediated systems requires consideration of not only the traditional issue of how a small molecule interacts with its target, but also considerations of interactions with a second protein, an E3 ligase. In this work, we will discuss our recent work in generating in silico ensembles of possible ternary complexes, followed by identification of those that are more likely to be experimentally relevant. The utility of these modeling approaches will be demonstrated by comparing the relative degradation tendencies of known systems across different targets, different ligases, and with different PROTACs.

Antibody Modeling / Developability Assessment / Solubility and Aggregation Prediction / Titration, pI, and pKa Calculation

mAb candidates identified from high-throughput screening or binding affinity optimization often present liabilities for developability, such as aggregation-prone regions or poor solution behavior. In this work, we developed a method for modeling proteins and performing pH-dependent conformational sampling, which can enhance property calculations such as hydrophobic patches, charge and pI. A retrospective data analysis demonstrates that these 3D descriptors, averaged over conformational sampling and stochastic titration, can accurately predict pI values, screen candidates and enrich libraries with favorable developability properties for a range of biotherapeutics. The clinical landscape of antibodies is also analyzed and its property profile and insights thereof are presented.

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 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.

MOE project / specialized protein families / project search / Organizing and centralizing project data / protein family modeling

The course covers MOE-Project, the automatic protocol for organizing SBDD project data. Topics include preparing protein data, using a graphical interface to create a project database of aligned and superposed protein structures, applying the MOE Project Search panel to mine the project data and analysis of molecular interactions using Protein-Ligand Interaction Fingerprints (PLIF).

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.

MOE databases / Calculated Descriptors / Fingerprints / QSAR Modeling / Binary QSAR / Similarity Searching / Consensus Modeling

The course will introduce cheminformatics applications using the MOE software. The topics covered include MOE database manipulation, importing/exporting data to various formats (SDF, SMILES), molecular descriptor calculation, data analysis and visualization, QSAR and binary-QSAR modeling, fingerprint-based similarity searching, clustering, diverse subset selection and consensus modeling.

MOE Databases / Descriptors / Fingerprints / QSPR Modeling / Pharmacophore Modeling / Template-Forced Docking / Scaffold Replacement / MedChem Transformations

The course covers the suite of MOE applications which can be applied to small-molecule virtual screening. Topics include the preparation of small molecule databases for virtual screening, filtering databases based on substructure matching and property values, building QSAR/QSPR models and fingerprint similarity models as database filters, pharmacophore query creation and searching, and small-molecule docking. These tools are used in conjunction to present a complete virtual screening workflow. The creation of de novo structures using the MOE Scaffold Replacement and MOE Medchem transformation applications is also covered.

PROTAC / Targeted Protein Degradation / Ternary Complexes / Protein-Protein Docking

Bifunctional small molecules known as PROTACs (Proteolysis-Targeting Chimeras) have recently shown great potential in drug discovery. Their mechanism of action involves degradation of a target protein rather than its inhibition, and thus computational modeling of PROTAC-mediated systems requires consideration of not only the traditional issue of how a small molecule interacts with its target, but also considerations of interactions with a second protein, an E3 ligase. In this work, we will discuss our recent work in generating in silico ensembles of possible ternary complexes, followed by identification of those that are more likely to be experimentally relevant. The utility of these modeling approaches will be demonstrated by comparing the relative degradation tendencies of known systems across different targets, different ligases, and with different PROTACs.

Antibody Modeling / Developability Assessment / Solubility and Aggregation Prediction / Titration, pI, and pKa Calculation

mAb candidates identified from high-throughput screening or binding affinity optimization often present liabilities for developability, such as aggregation-prone regions or poor solution behavior. In this work, we developed a method for modeling proteins and performing pH-dependent conformational sampling, which can enhance property calculations such as hydrophobic patches, charge and pI. A retrospective data analysis demonstrates that these 3D descriptors, averaged over conformational sampling and stochastic titration, can accurately predict pI values, screen candidates and enrich libraries with favorable developability properties for a range of biotherapeutics. The clinical landscape of antibodies is also analyzed and its property profile and insights thereof are presented.