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Molecular Operating Environment

Molecular Modeling and Simulations Protein Modeling and Bioinformatics Structure-Based Design Pharmacophore Modeling Cheminformatics and High Throughput Discovery Development Environment

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Comprehensive Software System for Life and Material Science

Molecular Operating Environment (MOE) MOE, the Molecular Operating Environment, is a comprehensive software system for Life andMaterial Science developed by Chemical Computing Group Inc. (CCG).MOE is a combined Applications Environment and Methodology Development Platform thatintegrates visualization, simulation and application development in one package.MOE strongly supports drug design through molecular simulation, protein structure analysis, dataprocessing of small molecules, docking study of proteins and small molecules, and so on under theunified operations.SVL, the Scientific Vector Language, is the portable high performance programming language built-inMOE. SVL is the vectrized command language, scripting language and applications programminglanguage. One-tenth reductions in code size over C and FORTRAN are routinely realized. SVLsource code to MOE applications is distributed with MOE to end-users; this allows MOEapplications to be freely customized or modified.

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Graphical User Interface (GUI)The GUI of MOE provides the common workingenvironment on various platforms from PC's toworkstations. Menu and panels are also customizable andthe environments for users are freely set-up. The mainwindow is equipped with the builder for small molecules,

the fragment libraries of amino acids, nucleic acids, andcarbohydrates, and also the input in SMILES format.Since the molecular structure data are managedhierarchically, it is easy to refer and edit the data. It alsoprovides various display functions like molecular surfaces,protein secondary structures, hydrogen bonds and so on.MOE also supports the hardware stereo.

Molecular Database ManagementThe database has an original format, MDB (MolecularDatabase), for effectively processing huge data used incomputational chemistry, and can be accessed in high speedthrough the spreadsheet-like user interface. It is able tosave any results of molecular dynamics, conformationalsearch, construction of compound libraries, QSAR, etc. in aunified format and to analyze them with statistics andgraphs.It can read/write SD files and ASCII files and save SD filecontents in 1/5 of its disk space with MDB format. It alsoprovides all of the Protein Data Bank (PDB) in MDB fileformat.

SVL Source CodeSource codes of applications written in SVL are basicallyopen. With use of the development tools, e.g ., SVL TextEditor, users can easily refer to the contents of programsand modify the algorithms or parameters.The programs and scripts written in SVL run on varioushardware; Applications developed on Windows PC's can berun on Linux PC's, UNIX workstations or Mac s withoutany changes in codes, and vice versa. SVL codes areautomatically loaded and compiled at the startup of MOEin a short time.

Cross-Platform and Various Modes of UsageMOE's cross-platform architecture makes it ideal forcorporate deployment. MOE runs on Microsoft Windows,Mac OSX, Linux and SUN Solaris platforms.MOE can be used in various modes. It has not only the GUImode, but the webservice mode, MOE/web accessedthrough Web browser or SOAP application, and theparallel computational mode, MOE/smp applicable to thevery large data processing.Experimental scientists as well as computational chemistryexperts can adapt the best usage to their end.


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Implicit Solvent Electrostatics Simulate and understand solvation effects without explicit treatment of water molecules using implicitsolvent electrostatics. All forcefield parameter sets include a Generalized Born implicit solvent model orreaction field electrostatics model. The full non-linear Poisson-Boltzmann equation can be solved using a fastmulti-grid algorithm providing for modeling of mobile implicit ion s effect.

Conformational AnalysisPerform a conformational analysis using a Stochastic, Systematic or LowModeMD search methodology (withfull choice of forcefield). Use a fragment-based high-throughput methodology for construction of largeconformation databases. Visualize and analyze the resulting ensembles of conformations. LowModeMD is aconformational search method that uses implicit vibrational analysis to focus a MD trajectory along thelow-mode vibrations. This has the effect of searching for minima along the valleys and troughs on thepotential energy surface. LowModeMD is has the best overall performance on a wide set of structures fromsmall molecules to peptides, macrocycles, and protein loops.

Diffraction SimulationPredict the results of X-Ray, Neutron or Electron diffraction experiments in gas, amorphous liquid, powder

or single crystal phases using diffraction simulations. Display the structure factor in a variety of intensity plots.

Quantum Chemical CalculationsMOE provides interfaces to popular ab initio, semi-empirical and density functional codes such as GAMESS,Gaussian, ADF, MOPAC7 and MOPAC2007/2009. Uses a graphical interface to configure a calculation andview results such as electron density contours, molecular orbital plots, energy level diagrams and otherproperties. Use MOE/smp to conduct the calculations on collections of compounds in parallel.

Nonbonded Interaction Visualization The methodology used to determine, score andrender hydrogen bonds, clashes and other

non-bonded interactions such as Halogen bond hasbeen replaced with a more sophisticated technique.A fast Extended Hckel Theory calculation isautomatically performed on the molecular systemand the resulting sigma/pi charges and fractionalbond orders are used to parameterize thenon-bonded energy scores.

Macromolecular System Preparation This application for preparing macromolecular structures for the subsequent simulation works is commonstructural problems in X-ray crystalstructure data (lack of terminal

caps, missing atoms, missing loops,etc.) are automatically diagnosedand presented in a list. Eachdiagnosed problem can beinspected and fixed from thegraphical user interface .


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MOE's CASP validated applications for protein structure predictionare powerful, intuitive and easy to use, both for experts and

occasional users. Powerful homologue identification, alignmenttechnology and refinement methodology make high qualitysequence-to-structure predictions routinely possible.

Protein Structure and Family Databases CCG has processed all the PDB structures, corrected common errors and produced a cleaned version ofthe PDB. Search the database using Code, Header, Compound, Title, HET groups, resolution, etc. Thecleaned database is subjected to an exhaustive and iterative structuralclustering procedure to generate the Structural Family Database. Theresult is a database of structural families in excellent agreement withexpert hand-curated family databases.

Remote Homology and Fold IdentificationSearch the Structural Family Database to identify protein familiesrelevant to structure prediction. The search uses a FASTA-type localalignment followed by a family membership test based upon full multiplealignment and Z-score significance testing. Folds of even distantlyrelated homologues can be reliably identified with few false positives(unlike pairwise searches). Use the Domain Motif Search to identifystructural homologues with low sequence identity.

GPCR/Kinase/Antibody Family Database The dedicated MOE protein databases for antibodies, kinases and Gprotein-coupled receptors (GPCRs) are compiled to extract as much structuralinformation from the PDB as possible. A special database update application allowsthe continuous enrichment of the structure pool by scanning the PDB as well asin-house structure repositories for new submissions. Antibody/Kinase/GPCRFamily applications have been added for managing and exploring entries. Anapplication is now available for creating an aligned kinase database and a specializedsearch application can be used to locate and browse entries. This dedicatedsequences can be identified and annotated and alignment constraintscan be automatically added using the Sequence Editor. This greatlyhelps Antibody/Kinase/GPCR sequence alignment work.

Structural Family Analysis Understand the conserved features and differences between related protein structures (and homologous

sequences). A 3D structural family analysis provides insight into conserved geometry, conserved water, saltbridges, hydrogen bonds, hydrophobic contacts and disulfidebonds that are often undetected in sequence alignments. Usestructural or sequence dendrograms to eliminate outliers andimprove alignments.

Mutation and Rotamer Exploration Discover accessible amino acid side chain conformations withMOE's Rotamer Explorer. This predicts the structure of aminoacid mutations in a 3D protein structure. Rank candidaterotamers using an energy-based scoring function and visuallyanalyze them using MOE's graphical interface.

Protein Modeling and Bioinformatics


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Copy and Paste for Loop Grafting Copy and Paste functions allow both 2D and 3D loop graftingor manual sequence insertions. This greatly reduces the numberof chain splits and joins needed to perform such graftingoperations.

Homology Modeling and Antibody Modeling Build a homology model from an amino-acid sequence bystatistically assembling fragments of experimentally determinedbackbone structures from one or more templates, selection ofsidechain conformations from a rotamer library, followed by arefinement protocol based on energy minimization in theforcefields. A ranked ensemble of protein structures isproduced and written to a MOE molecular database forsubsequent analysis or further refinement. Include environment units such as bound ligands and conservedwaters in the structural template. MOE also provides antibody specialized modeling application andupdatable database.

Structural Quality Assessment Assess the reliability of predicted structures with statisticalmeasures of quality derived from X-ray crystallographic data.Diagnostic measures such as Ramachandran Plots and aStereochemical Report make it easy to identify and isolateregions of predicted structures that require furthertreatment.

Protein Engineering/Protein DesignExplore and compare mutant series against a wild type with aunified protein engineering application. Conduct AlanineScanning to systematically explore affinity. Assess proteinstability and optimize unstable regions by identifying disulfide

bridging opportunities through Cysteine Scanning. Rationalizeand perform single point or multiple mutations via ResidueScanning to assess and advance lead candidates. Use SequenceDesign to search all possible multiple mutations to determinean optimal sequence. Easily identify residues prone to naturalmutation, based on single nucleotide polymorphism, using Resistance Scanning. Automatically generateensembles using molecular dynamics or LowModeMD to estimate ensemble averaged properties.

Prediction of Hydrophobic and Electrostatic Hot SpotsCreate molecular surfaces and analyze surfaceproperties such as hydrophobic and electrostaticpotentials. Analyze surface patches to understand localhydrophobic and polar properties. Compare multiplestructures to understand differences in affinity andstructural variability. Highlight potential reactive sitesfor oxidation and deamidation. Visualize and ranks hotspots using knowledge-based potentials and evaluate thenon-linear Poisson-Boltzmann equation to evaluateelectrostatic preferences in order to rationalize interactions and potential sites for mutagenesis.

Protein PropertiesCalculate a comprehensive set of sequence and structure based physical properties such as pI, zeta potential,mobility, dipole moment, etc. for building QSPR model or helping rationalize protein solubility, solutionviscosity, stability and aggregation. Use the predicted properties in conjunction with preliminaryexperimental data to rationalize stability and aggregation at a given pH. Calculate properties for an ensembleof mutants to identify and predict physical property trends on a relative scale.


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Macromolecular crystallographic data, when available, can be avaluable source of information for discovering active ligands. MOEprovides a various applications for visualizing and understandingdetails of receptor active sites and receptor-ligand interactions.These applications are used to suggest improvements to ligands orscreen ligand databases for candidate binders.

Active Site Detection Detect candidate protein-ligand andprotein-protein binding sites using a fastgeometric algorithm based onEdelsbrunner's Alpha Shapes. Each site on amacromolecular structure is rankedaccording to its PLB index*. Visualizeindividual sites or populate them withdummy atoms for docking calculations orstarting points for de novo ligand designefforts.

*PLB index: Soga, S., Shirai, H., Kobori, M., Hirayama, N.; Use ofAmino Acid Composition to Predict Ligand-Binding Sites; J.Chem. Inf. Model.47 (2007) 400-406.

Electrostatic Maps

Determine favorable locations of neutral, positive and negative features in an active site. The electrostaticmaps are calculated by solving the non-linear Poisson-Boltzmann equation for receptor atoms andpseudo-ionic species. The isocontour levels of the generated predicted map are expressed in kcal/mol. Theadvantage of the present method is that fully screened electrostatic potentials are used and the dominationof the potential by ionic groups is avoided.

Probabilistic Contact Potentials Visualize and understand directional details of hydrophobic or hydrophilic contact preferences of a receptoror ligand using probabilistic contact maps. CCG has developed a suite of analytical probability distributionsthat correspond very well to inter-atomic distance, angle and out-of-plane angle histograms derived from alarge collection of crystallographic structures. These distributions are then used to form a compositepreference map for a given macromolecular structure.

Ligand-Receptor Docking Dock small molecules in a macromolecularbinding site. Supply a database of conformationsor generate conformations on-the-fly based onpotential energy models including solvationeffects. The poses are scored using a LondondG scoring function for estimating bindingaffinity. Optionally, constrain the generatedposes to satisfy a pharmacophore query to biasthe search towards known importantinteractions.

GBVI/WSA dG scoring functionThe GBVI/WSA dG scoring function is basedon the forcefield, GB/VI implicit solvent model


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and a weighted surface area term. There are onlythree fit parameters in the scoring function each ofwhich is related to Linear Interaction Energy principlesand were fit to experimental binding free energies.

Multi-Fragment Search Multi-Fragment Search is an ensemble-based

methodology for mapping the preferred locations ofspecific chemical groups in a receptor structure. Anactive site of a macromolecular structure is populatedwith a large number of chemical fragments, which aresubjected to an energy minimization protocol. Theresulting group locations are clustered, scored(including solvation effects) and output to a databasefor subsequent visualization and analysis.

Active Site Depiction Use the protein-ligand interaction diagrams to easilyidentify polar, hydrophobic, acidic and basic residues.Visualize solvent exposed ligand atoms and residues inclose contact with ligand atoms as well as sidechainand backbone acceptor and donor interactions.

LigX LigX is a streamlined interface for interactive 3D ligandoptimization in the active site. A dedicated button barprovides commands for structure preparation, activesite analysis, molecular property/binding affinitycalculations and ligand modification and optimization inthe active site. LigX can be used by both computationaland medicinal chemists.

Molecular Surface and Maps Molecular Surface and Maps is an integrated applicationfor active site analysis. Build molecular surfaces,predict contact preferences and calculate electrostaticmaps. Color molecular surfaces by choosing from avariety of schemes such as temperature factor, pocket,ActiveLP and electrostatic potential.

Scaffold Replacement Link annotations denote substitution points on acandidate scaffold molecule and the locations ofpotential R-group substituents. Search standard 3D

databases or special scaffold and linker databases tofind novel chemical scaffolds that preservesubstituents geometry. Add additionalpharmacophore features to preserve known scaffoldinteractions or volume constraints to satisfy shaperequirements.

Combinatorial BuilderMultiple attachment points and 3D R-group librariescan be systematically enumerated around a scaffold,refined and filtered in a receptor pocket.


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BREED: 3D Ligand Generator BREED takes the idea of "crossover" from the field of Genetic Algorithms to generate new structures. Newligands are generated by combining parts of existing ligands. The user can specify QuaSAR descriptor, Modelfile and/or Pharmacophore query filters to limit the results. If a receptor is present, structures can be refinedin the binding cleft as with docking calculations. Thus, BREED can be used as part of a ligand-based or

structure-based discovery methodology.

MedChem Transformations MedChem Transformations is an approach used todiscover novel chemical structures by applying a set oftransformation rules to existing ligands. Typicaltransformations might exchange functional groups, oralter all or part of individual rings while preserving therest of ligand. These can be applied iteratively, resultingin cumulative changes to the starting structures. If areceptor is available, Forcefield Refinement can be usedto generate bound poses along with various dockingscores.

Water Structure Analysis with 3D-RISM The methodology is 3D-RISM (Kovalenko-Hirata closure) a density functional theory of liquids whichcalculates 3D densities of the oxygen and hydrogen atoms around a solute in aqueous phase. The densitycalculations are direct and no MD or MC simulations are required; consequently, the method is orders ofmagnitude faster than simulation-based alternatives. The resulting density and derived solvation free energycan be mapped in the input solute or complex structure.


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MOE's pharmacophore modeling methodology is a powerful meansto generate and use 3D geometric information to search for novelactive compounds, particularly when no receptor geometry isavailable. Pharmacophore methods use a generalized ligandrepresentation and geometric constraints to bypass the structuralor chemical class bias of 2D methods.

Pharmacophore Query Editor Use an interactive editor to construct a 3D queryfrom a molecular alignment or macromolecularstructure. Use the query to filter a conformationaldatabase in an effort to determine candidate activecompounds that satisfy the pharmacophore model.Refine the query to contain locations of Booleanexpressions of pharmacophore features as well asrestrictions on shape by using union-of-spheres forincluded, excluded and exterior volumes eachcontaining an optional SMARTS chemical pattern.

Pharmacophore Search Rapidly searche 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. Output dataconsists of molecules that satisfy the 3D pharmacophore query (either all conformations or just theconformations that satisfy the query). Partial matches, 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 forvirtual 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 stochasticsearch. The fragment conformations are rapidly assembled by superposing the overlapping atoms. Adatabase of fragments is maintained (and augmented as the search proceeds) making conformationgeneration of combinatorial libraries very fast.

Pharmacophore Elucidation Generate pharmacophore queries from a collection of inputcompounds (possibly with activity data) by considering all possiblediscrete geometries and all possible combinations of feature queryexpressions. A build-up strategy is used to avoid combinatorialexplosion. Enforce limits on feature counts and add custom queryexpressions. Each pharmacophore query is scored based on knownactive compound coverage, statistical activity enrichment andatomic overlap of matching conformations. The resulting scores and induced molecular alignments ofhigh-scoring pharmacophore queries are written to a MOE molecular database for further analysis.

Pharmacophore ConsensusThis application 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 scorethreshold and the consensus score mode. Pharmacophore consensus is particularly useful when startingfrom a few highly active compounds.


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MOE provides a suite of applications for manipulating and analyzing largecollections of compounds, building property models, consensus models and SDpipeline command line tools .

VSA Descriptors MOE's VSA descriptors are van der Waals surfac earea bas ed descriptors for logP, molar refractivityand partial charge properties. These descriptorsshow weak inter-descriptor correlation andcorrelate highly to many physico-chemicalproperties. The VSA descriptors are based on 2Dconnection tables making them ideal for HTSQSAR.

Molecular Descriptors Calculate over 300 molecular descriptors includingtopological indices, structural keys, E-state indices,physical properties (such as LogP , molecular weightand molar refractivity), topological polar surfacearea and CCG's VSA descriptors with wideapplicability to both biological activity and ADMEproperty prediction. Use descriptors forclassification, clustering, filtering and predictivemodel construction. Add custom descriptors usingMOE's built-in Scientific Vector Language.

HTS-Binary QSAR MOE's patented Binary QSAR methodology is ideal for building pass/fail models from high error contentdata and standard molecular descriptors. Use the resulting probabilistic models (based on Bayesianstatistical inference) as a biasing agent in the design of focused combinatorial libraries.

QSAR/QSPR Predictive Modeling Build QSAR/QSPR models using linear, probabilistic and decision-tree methodologies. CCG's unique BinaryQSAR methodology is ideal for building pass/fail models from high error content data. Linear modelsinclude PCR and PLS methodologies and can support biological activity or ADME assessments.

The Structure-Activity Report (SAReport) SAReport contains sophisticated analysis methods to help scientists identify important groups and makemore effective choices for synthesis. As experimental data builds up on discovery projects it is oftendifficult for scientists and managers to keep track of the information. SAReport puts the information into aconsistent context for better decision making.


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High Throughput Conformational Search Construct conformation databases using a parallelized fragment-based approach. Molecules are subdividedinto overlapping fragments each of which is subjected to a rigorous stochastic search. The fragmentconformations are rapidly assembled by superposing the overlap atoms. A database of fragments ismaintained (and augmented as the search proceeds) making conformation generation of combinatoriallibraries very fast.

Similarity, Diversity and Fingerprints Perform similarity searching and diverse subset selection using Descriptor, Conformation and MolecularFingerprint methodologies. Choose between a number of fingerprint systems including 2, 3 and 4- pointpharmacophore fingerprints in 2D or 3D and MACCS key fingerprints.

Automatic 2D Depiction Quickly generate publication quality depictions of smallmolecules in 2D using a unique algorithm. The algorithmhas been validated using a dataset of ~70,000 structures.Calculate 2D depictions for each molecule in a databaseand create depictions during ASCII import of SMILESstrings.

Consensus Modeling Combine linear, binary, fingerprint, and pharmacophoremodels into a single composite model. Save and apply theconstructed models to collections of compounds forclustering, selection, filtering applications or designingfocused combinatorial libraries.

Combinatorial Library Design Enumerate both reaction-based or R-group-based virtual

libraries either in 2D or 3D. Filter the virtualcompounds by properties or pharmacophores. Buildcombinatorial libraries by combining scaffold and R-group databases or with MOE's reaction-based librarygeneration method. Reactions can be chosen from a list or sketched in standard sketchers and applied toenumerate libraries of compounds. The default reagent database contains over 3,000 reagents curatedfrom commercial vendors, however, custom reagent databases can be specified.

RECAP Analysis and Synthesis Analyze large collections of compounds to produce fragments resulting from retrosynthetic rules. Use theresulting fragments in a de novo synthesis methodology to produce novel chemical structures that have anincreased likelihood of synthetic accessibility. Specify heavy atom mean and variance to control the size distribution on the randomly generated structures. Apply leadlike/druglike, QSAR/QSPR predictive modelsor 3D pharmacophore filters for de novo virtual screening applications.

rsynth : Synthetic ScoreThe synthetic feasibility score, which is the fraction of the atoms of each new structure that ultimatelyappear in a retrosynthetic fragment found in the starting materials database. A value of one indicates thatthe molecule is very likely synthesizable.

SD Pipeline Command Line Tools Operate directly on SD files for structure depiction, acid/base protonation state, database filtering, sortingand descriptor calculations. Remove records that do not satisfy a series of filters ( e.g. lead-like, reactivegroups, drug-like, etc.), sort records and remove duplicate entries from SD files. Calculate descriptors and

write the output to SD or ASCII formats.


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In addition to the suite of graphical applications, MOE contains atoolbox for adapting existing applications or creating newapplications for Life Sciences. With MOE, expert modelers,application developers and occasional users can benefit fromsharing the same software system. Methodology written byapplication developers can be validated by expert modelers andthen deployed to occasional users using either the MOE graphicalinterface or a Web interface.

Scientific Vector Language (SVL)SVL is the built-in command language, scripting language and

application development language of MOE. SVL is a "chemistryaware" vectorized computer programming language with over1,000 specific functions for analyzing and manipulating chemicalstructures and related molecular objects. SVL is a concise,high-level language and SVL programs are typically 10 timessmaller than equivalent programs written in C or FORTRAN.SVL source code is compiled to a "byte code" representation,which is then interpreted by the base run-time environmentmaking SVL programs inherently portable across differentcomputer hardware and operating systems.

Background ComputingMOE/batch is an adaptation of the MOE run-time environmentintended for batch or background calculations that do notrequire a graphical interface. All non-graphical MOEfunctionality is accessible. MOE/web technology distributed with MOE is used to create Web Browserinterfaces to MOE applications.

Cluster ComputingA standard part of MOE is the MOE/smp distributed computing technology. With MOE/smp, multiplecooperating computers can be used to perform large-scale calculations. A heterogeneous collection ofcomputers including laptops, workstations and multi-processor clusters, all running different operating

systems, can be easily harnessed together in a single MOE session. The MOE/smp programming model in SVLmakes it easy to parallelize SVL applications.

MOE/web: Web Browser and SOAP Application FrameworkMOE/web is an application environment that allows for large scale deployment of MOE applications orcustom SVL programs to occasional users such as medicinal chemists via a simple web interface and/or toSOAP applications. MOE/web is distributed with MOE and customized applications can be incorporated.

URL (HTTP/FTP) & TCP-IP SocketsAccess data from the internet via FTP, download files from web servers via HTTP and directly access thirdparty database servers such as Oracle and DB2 via JDBC. MOE contains built-in applications to download

new entries from the RCSB Protein Data Bank and a relational database browser. It is also possible to writeSVL programs that interface with existing applications and libraries.

Development Environment


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License StyleMOE is offered under a floating license. It is possible to be used freely on any coexisting computers and

workstations under the network environment with which the license of MOE is common to all thehardware supported by MOE.The license of MOE is managed with network floating license with the token as unit, and can be usedfrom any machine within the limitation of the license. The number of tokens MOE uses at a time isdifferent depending on the mode:

Program (Mode of usage) Number of necessary tokensMOE (Graphics mode) 3 tokens

MOE/batch (Non-graphics mode) 1 token

MOE/web (Webservice mode) 1 token

MOE/smp (Parallel computation mode) 1 token x number of processes

(When non-graphics mode is used)

MOE has no limit of number of install machines.

Support PlatformArchitecture OS Graphics

Intel Windows XP / Vista / 7 / 8 OpenGL*

Linux (glibc version 2.3.4 or later) OpenGL* / X11Mac OS X v10.5 or later OpenGL* / X11

Sun Microsystems, AMD Solaris 8, 10 OpenGL* / X11

As for the supported platform, please inquire of Ryoka Systems Inc.

*To use full graphic effects and anaglyph stereo, OpenGL 2.1 or later with GLSL shader is needed.


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The products or brand names in this catalog are trademarks or registered trademarks oftheir respective holders. The specifications in this catalog may be changed without notice.

Copyright 2013 Chemical Computing Group Inc. & Ryoka Systems Inc. All rights reserved.

Ryoka Systems Inc.Tokyo Skytree East Tower, 29th fl.1-1-2 Oshiage Sumida-ku,Tokyo 131-0045 Japan

http://www.rsi.co.jp/science/index_e.html

[email protected]

Chemical Computing Group Inc.1010 Sherbrooke St. W, Suite 910 Montreal,Quebec, Canada H3A 2R7

http://www.chemcomp.com/

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