Pharmacophore Discovery

MOE’s pharmacophore modeling methodology is a powerful means to generate and use 3D geometric information to search for novel active compounds, particularly when no receptor geometry is available. Pharmacophore methods use a generalized ligand representation and geometric constraints to bypass the structural or chemical class bias of 2D methods. MOE’s pharmacophore applications are powerful, intuitive and easy to use, both for experts and occasional users.

Scaffold Replacement Use Link pharmacophore annotations for scaffold replacement or mimetic projects. Link annotations denote substitution points on a candidate scaffold molecule and the locations of potential R-group substituents. Search standard 3D databases or special scaffold and linker databases to find novel chemical scaffolds that preserve substituents geometry. Add additional pharmacophore features to preserve known scaffold interactions or volume constraints to satisfy shape requirements.

Pharmacophore Elucidation Generate pharmacophore queries and induced molecular alignments from a collection of input compounds (possibly with activity data) by considering all possible discrete geometries and all possible combinations of feature query expressions. A build-up strategy is used to avoid combinatorial explosion. Enforce limits on feature counts and add custom query expressions. Score queries based on known active compound coverage, statistical activity enrichment and atomic overlap of matching conformations.

Pharmacophore Search Rapidly search a conformational database for compound conformations that satisfy a pharmacophore query. Search multiple databases, a sub-range of molecules or a database of docked compounds. Search MOE MDB, compacted MOE MDB or Omega OEB files directly. Output data consists of molecules that satisfy the 3D pharmacophore query (either all conformations or just the conformations that satisfy the query). Partial matches, SMARTS patterns, output of all symmetric matches and specification of essential features are supported.

High Throughput Conformational Analysis Use MOE’s High Throughput Conformational Search methodology to construct conformation databases for virtual screening. Conformational databases are constructed using a parallelized fragment-based approach. Molecules are subdivided into overlapping fragments each of which is subjected to a rigorous stochastic search. The fragment conformations are rapidly assembled by superposing the overlapping atoms. A database of fragments is maintained (and augmented as the search proceeds) making conformation generation of combinatorial libraries very fast.

Pharmacophore Query Editor Use an interactive editor to construct a 3D query from a molecular alignment or macromolecular structure. Use the query to filter a conformational database to determine candidate active compounds that satisfy the pharmacophore model. Customize pharmacophore annotations with SMARTS chemical patterns and Boolean 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.

Pharmacophore Consensus suggests possible pharmacophore queries based on a set of aligned active compounds. A consensus calculation requires a set of aligned input molecules, a tolerance radius, the consensus score threshold and the consensus score mode. Pharmacophore consensus is particularly useful when starting from a few highly active compounds.