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| MOE (software) | |
|---|---|
| Name | MOE |
| Developer | Chemical Computing Group |
| Released | 1990s |
| Latest release | (varies) |
| Programming language | C++, Java, Python |
| Operating system | Microsoft Windows, macOS, Linux |
| Genre | Computational chemistry, Molecular modeling, Drug design |
| License | Proprietary (academic licenses available) |
MOE (software) is a commercial molecular modeling and computational chemistry suite developed to support structure-based drug design, cheminformatics, and computational biophysics. It integrates molecular visualization, ligand docking, molecular dynamics, quantitative structure–activity relationship (QSAR) modeling, and virtual screening into a unified platform to assist researchers across pharmaceutical, academic, and biotechnology institutions.
MOE provides tools for molecular visualization, structure preparation, protein–ligand docking, pharmacophore discovery, cheminformatics, homology modeling, and molecular simulation within a single environment. The platform is used by teams working on hit identification, lead optimization, and ADMET prediction, supporting workflows that span from target selection to candidate nomination. It competes in the same market as other commercial and academic packages used by researchers at institutions such as Pfizer, Merck & Co., Novartis, GlaxoSmithKline, and University of Cambridge research groups.
MOE was created by the Canadian company Chemical Computing Group and evolved through iterative releases during the 1990s and 2000s to incorporate advances from computational chemistry and structural biology. The software’s development paralleled milestones in structural genomics and high-throughput screening initiatives associated with institutions like Structural Genomics Consortium, European Molecular Biology Laboratory, and National Institutes of Health. Over time, MOE incorporated methods influenced by publications from groups at Harvard University, Stanford University, University of California, San Francisco, and Massachusetts Institute of Technology, and it has been cited in literature linked to drug discovery programs at companies like AstraZeneca and Bristol-Myers Squibb.
MOE offers features for protein structure manipulation, ligand-based design, and predictive modeling including force fields, solvation models, and conformational sampling. Core functionality includes molecular building and editing, sequence alignment, structure superposition, pharmacophore modeling, docking protocols, QSAR regression and classification, and cheminformatics operations such as substructure search and descriptor calculation. These capabilities support projects in medicinal chemistry groups at organizations like Eli Lilly and Company, Roche, Sanofi, and academic centers such as University of Oxford and Johns Hopkins University.
The software architecture combines a graphical user interface, a scripting interface, and computational kernels implemented in C++ with bindings for scripting languages such as Python and Java. MOE’s architecture supports plug-ins and modules for specialized tasks including molecular dynamics engines, scoring functions, and cheminformatics toolkits. It interoperates with structural databases and standards maintained by entities like the Protein Data Bank, UniProt, and ChEMBL, and it integrates file formats used by institutions such as European Bioinformatics Institute and tools from groups like OpenEye Scientific Software and Schrodinger (company).
MOE is distributed under a commercial license by Chemical Computing Group, with options for academic, non-profit, and corporate licensing. Licensing models include node-locked, floating, and site-wide agreements, and academic collaborations have enabled access for researchers at universities such as Massachusetts Institute of Technology, University of California, Berkeley, University of Toronto, and McGill University. Distribution channels and support networks involve partnerships with regional distributors and attendance at conferences hosted by organizations like American Chemical Society, Gordon Research Conferences, and European Federation for Medicinal Chemistry.
The software is widely adopted for structure-based drug design campaigns, virtual screening efforts, lead optimization projects, and computational chemistry curricula at universities and research institutes. Use cases include fragment-based drug discovery programs at companies like Astex Pharmaceuticals, computational toxicology studies referenced by agencies such as Food and Drug Administration, and collaborative projects between industry and academia, for example between GlaxoSmithKline and University of Oxford. MOE has been used in structural analysis of targets studied at centers including Scripps Research, Broad Institute, and Wellcome Trust Sanger Institute.
MOE is evaluated alongside commercial suites and academic packages such as software from Schrodinger (company), OpenEye Scientific Software, Accelrys (formerly Accelrys) / BIOVIA, GROMACS, AMBER (software), CHARMM, AutoDock, and Rosetta (software). Reviews in journals and conference proceedings often compare MOE’s integrated environment, docking performance, and cheminformatics capabilities to offerings from Chemical Computing Group competitors and academic toolkits developed at institutions like University of California, San Diego and University of Cambridge. Researchers and industrial users typically assess MOE on criteria such as accuracy of scoring functions, extensibility, user interface, and vendor support, and community discussions at venues like RECOMB and ISMB have influenced perceptions of strengths and weaknesses.
Category:Computational chemistry software