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.

Protein Patch Analysis / Protein Interaction Hot Spots / Antibodies and Related Derivatives / Interaction Sites / 2D Patch Depiction / Comparative Analysis / Key Active Regions

Protein patch analysis is a computational method for identifying and assessing protein interaction hot spots which may be implicated in aggregation, viscosity or solubility of antibodies and related derivatives. Here, we describe an enhanced and recalibrated method for calculating protein patches to better highlight potentially important interaction sites. Multiple structure support facilitates examination of interfaces and comparison across mutation series. Additionally, a 2D patch depiction can be used in comparative analysis to accentuate patch differences and identify key active regions. Examples demonstrate how the application can be used to help understand complexation in different contexts.

Medicinal Chemistry Transformations / Bioisosteres / Lead Optimization / Ligand Ranking and Scoring / Structure-Based Design / Ligand Synthetic Accessibility

The exploration of the immense chemical space for the discovery or optimization of novel drug structures presents a significant challenge. In this presentation we describe an approach for exploring and generating new chemical structures by applying a set of transformation rules and addressing the potentially large set of suggested compounds along with their synthetic accessibility. Common transformation strategies such as bioisoteric replacement to preserve properties and optimization transformations to improve properties in the context of structure-based design for generating relevant structures will be discussed.

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.

Targeted Protein Degradation / PROTACs / Ternary Complex Modeling / Protein-Protein Docking

Targeted protein degradation using bivalent small molecules (such as PROTACs) is a new modality that provides a means to control protein levels in vivo. Despite many clear advantages, numerous challenges exist in PROTAC development, particularly concerning the rational design of efficacious molecules. In this presentation, multiple computational methods that enable the a priori evaluation of putative PROTAC molecules will be discussed. Numerous case studies will be offered, where the application of these computational tools can successfully recommend not only potent PROTAC candidates, but also molecules to avoid. Results from scenarios across different target proteins, E3 ligases, and PROTAC architectures will be presented. Finally, our latest innovations, such as KNIME integration and maximum common substructure matching to simultaneously evaluate multiple PROTAC warheads, will be shown.

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.

Thermodynamic Integration / Free Energy Calculation / FEP / AMBER / Binding Affinity

Until the advent of GPU accelerated molecular dynamics, alchemical free energy simulations had not been routinely applied in early stage drug discovery. While this GPU acceleration made such calculations more feasible, the complexity of the protocols and uncertainty regarding optimal parameters are a lingering problem. In the recently released MOE 2019 a streamlined interface was added to set up free alchemical energy calculations dynamics simulations based on the Thermodynamic Integration (TI) method in AMBER 18. The workflow includes structure preparation, ligand parameterization, simulation planning and analysis. Free energy calculations are known to be extremely sensitive and have a high failure rate. We present an optimal simulation planning methodology that minimizes the expected error for a given system based on the available simulation resources (number of GPUs, nodes, etc.). Another major source of error is the simulation instability due to an imbalance between the electrostatic and van der Waals forces. Optimization of the AMBER soft-core potential resulted in much higher simulation stability and hence lower curvature of the potential function. In conjunction with Fejér numerical integration the evaluation of the alchemical integral can be achieved with spectral accuracy. The methodology was validated through the calculation of relative binding energies of 34 ligands of the p38 MAP Kinase and compared to experimental data.

Molecular Fingerprints / Structural Motif Detection / Pharmacophore Queries / Fingerprint Bit Visualization

Reverse fingerprints can be used to detect molecular structure motifs important for a molecular property of interest. This webinar covers the theory of reverse fingerprinting and presents examples of its application to identify pharmacophore motifs and derive consensus pharmacophore queries from a molecular series.