MOE™: Molecular Operating Environment

Medicinal Chemistry Applications

CCG has over a decade of experience in creating and deploying solutions for medicinal chemists in lead generation and optimization. The Molecular Operating Environment (MOE) has been adopted by many of the top pharmaceutical research companies for large-scale medicinal chemistry deployment.  A large number of small to medium sized pharmaceutical companies have also deployed MOE as their primary medicinal chemistry modeling platform to accelerate development efforts of novel therapeutics.

  • Harmonized platform for both medicinal chemists and computational scientists
  • Seamless communication between multiple diverse discovery project groups
  • Ease of integration with in-house databases, servers and pipeline workflow systems

CCG has developed (in collaboration with large pharmaceutical companies) a streamlined interface for active site visualization and ligand optimization.  A button bar provides applications for structure preparation, active site analysis, molecular property/binding affinity calculations, potential R-group directions (for substitution opportunities) and ligand optimization in an active site.  Modify ligands using the 3D builder or using 2D sketchers.  Measure distances, angles and dihedral profiles.  Visualize and modify aligned complexes, toggle proteins on/off, browse docking poses, pharmacophore hits and adjust rendering with the System Manager.

MOEsaic is a browser-based application for analyzing series of small molecule chemical structures and related property data from drug discovery projects. Align molecules to facilitate pairwise comparison. Conduct substructure and similarity searches. Perform Matched Molecular Pair (MMP) analyses. Profile R-groups with defined scaffolds using a built-in chemical sketcher. Detect activity cliffs and bioisosteres. Visualize the data through property Plots and applied Filters. Design virtual structures and Document findings with text and images.

Visualize and analyze ligand-receptor interactions such as hydrogen bonds including CH..O interactions, halogen bonds, sulfur-oxygen interactions, proton- and cation-π interactions using Extended Hückel Theory (EHT).  EHT more accurately calculates interaction strengths and takes into account electron withdrawal and resonance effects.

MOE - Medicinal Chemistry Applications Automatically generate 2D diagrams [Clark 2007] of the active site residues interacting with a ligand or series of ligands.  Visualize key interactions such as hydrogen bonds, salt bridges, hydrophobic interactions, cation-π, sulfur-LP and halogen bonds in 2D.  Identify potential locations for ligand substitution using a depicted steric contour.  Visualize solvent exposed ligand atoms and residues with strong hydrophobic interactions.  Browse through a chemical series or receptor family series to identify conserved or non-conserved interactions for selectivity analysis.

Build Molecular Surfaces colored by properties to define and characterize active site topology and identify ligand substitution opportunities.  Predict knowledge-based non-bonded Contact Preferences or calculate Electrostatic Maps using the non-linear Poisson-Boltzmann equation to identify high value hydrophobic regions and polar hot spots.  Calculate water density and binding desolvation penalty maps using 3D-RISM, a first principles theory of solvation based on the Density Functional Theory of liquids.  Detect non-obvious hydrophobic regions of binding sites created by correlation and cavitation effects to prioritize ligand modifications.

Explore ligand conformation space to gain insights regarding bioactive conformations and intra-molecular interactions.  Use LowModeMD [Labute 2010] to generate conformations of macrocycles and multi-component systems (e.g., explicit water or counter-ions) by performing a fast implicit vibrational analysis and short molecular dynamics simulation.

Perform 3D alignment (or superposition) of known and putative ligands to determine structural requirements for biological activity - particularly useful in ligand-based drug design protocols since aligned groups are likely to be important for determining the bioactive conformation .  Use the all-atom flexible alignment procedure [Labute 2001] that combines a forcefield and a 3D similarity function based on Gaussian descriptions of shape and pharmacophore features to produce an ensemble of possible alignments of a collection of small molecules. 

Grow ligands, link fragments and replace scaffolds [Grimshaw 2010] for fast follow-on compounds incorporating innovative linear, cyclic or fused scaffold arrangements.  Refine novel structures in a (flexible) active site while maintaining important pharmacophore interactions and calculate predicted binding affinities.  Use Medicinal Chemistry Transforms to explore local SAR by making small isosteric changes to ligands.  CCG provides a database of 170+ functional group, homologation and hetercycle transformations using rules extracted from the chemical literature.  New transformations can be added with standard 2D sketchers.

MOE - Medicinal Chemistry Applications MOE contains the industry-leading suite of pharmacophore discovery applications used for fragment-, ligand- and structure-based design projects.  Pharmacophore modeling is a powerful means to generate and use 3D information to search for novel active compounds, particularly when no receptor geometry is available.  Pharmacophore methods use a generalized molecular recognition representation and geometric constraints to bypass the structural or chemical class bias of 2D methods.

Use an interactive editor to construct a 3D query from a molecular alignment or receptor structure.  Perform a virtual screen of a conformational database to determine candidate active compounds.  Customize pharmacophore features with SMARTS chemical patterns (for particular groups) and/or expressions.  Restrict shape (receptor or ligand) by using union-of-spheres for included, excluded and exterior volumes.  Refine the query with directional vector constraints on atoms or partial matches on features.

Calculate over four hundred 2D and 3D molecular descriptors including topological indices, structural keys, E-state indices, physical properties, topological polar surface area (TPSA) and CCG's VSA descriptors [Labute 2003] with wide applicability to both biological activity and ADME property prediction. Apply Extended Hückel-based descriptors, such as LogP, LogD, and molar refractivity, for computing molecular properties. Calculate pKa and pKb of small molecules and determine the populations of ligand protonation states at a given pH. Use descriptors for classification, clustering, filtering and predictive model construction. Add custom descriptors using MOE's built-in Scientific Vector Language.

Enumerate compound libraries through the reaction-based Combinatorial Library Builder.  Use commercial or customized in-house reagents as input to a reaction engine.  Conduct simple esterification reactions or multi-component Ugi type or Groebke-Blackburn-Bienyame reactions.  Use standard 2D sketchers to specify reactions or multiple simultaneous reaction steps.  Automatically screen reaction products for chemical similarity to a target or with a pharmacophore model.  Filter the results with chemical descriptors or Lipinski's rule-of-five for drug-likeness.  Calculate focused libraries by applying QSAR or pharmacophore models.


[Clark 2006] Clark, A., Labute, P., Santavy, M.; 2D Structure Depiction; J. Chem. Inf. Model. 46 (2006) 1107-C1123

[Clark 2007] Clark, A. M., Labute, P.; 2D Depiction of Protein-Ligand Complexes; J. Chem. Inf. Model. 47 (2007) 1933-C1944.

[Clark 2008] Clark, A.M., Labute, P.; Detection and Assignment of Common Scaffolds in Project Databases of Lead Molecules; J. Med. Chem. 52 (2008) 469-483.

[Grimshaw 2010] Grimshaw, S.; Scaffold Replacement in MOE; JCCG (2010)

[Labute 2001] Labute, P., Williams, C., Feher, M., Sourial, E., Schmidt, J. M.; Flexible Alignment of Small Molecules; J. Med. Chem. 44 (2001) 1483-C1490.

[Labute 2003] Labute, P.; The Derivation and Applications of Molecular Descriptors Based Upon (Approximate) Surface Area; Chemoinformatics: Concepts, Methods, and Tools for Drug Discovery; J. Bajorath ed. (2003)

[Labute 2010] Labute, P.; LowModeMD - Implicit Low Mode Velocity Filtering Applied to Conformational Search of Macrocycles and Protein Loops; J. Chem. Inf. Model. 50 (2010)