Point out how you see the rest of the workshop going…
Access relevant chemical space that at present may not be available in reality… Screen fast then accurate, validate results with QSAR in order to find cancer inhibitor drug molecules
Inhibox core services…data platform based on ChemAxon toolkits and Oracle…
A tangible starting point for virtual synthetic reactions is C-Space build. This is a data warehouse style view of global, approaching real time, available commercial molecules. A continual queue of SDF data to process (running 24/7) is downloaded from supplier websites. A job is added to QUE table and the Oracle QUE package is called to process the job. The QUE table controls all the transactions, STG, INT and UNQ. This is the minimal user interaction possible! [Can have many jobs running at once but relatively slower] First the STG transaction is used to create a JChem staging table and import the SDF data (JChem base will standardize on import, this is implemented as Java Stored Procedure as there is no cartridge equivalent). The INT transaction integrates/migrates data from each stage area into the JOIN table. JOIN table is a route to map supplier information supplier_no to corporate molecule ID (one molecule_id to many supplier_no) The INT.JCSearch function is used to define the MOLECULE_ID which is the system wide unique identifier. [Query precedence is Exact search, Exact fragment search (salts), Exact (fragment) double bond stereo relaxed and then supplier_no, this is also the approx order of query time!] A new molecule_id is generated if the search return 0. A JChem Server licence is definitely required to build in anything real time! The SUP table simply lists the suppliers currently available to the system. The UNQ transaction migrates any new molecules from the JOIN table to MOL table. The MOL table is CA table and is visible to JSP application for subsequent SSS. The MOL table is tending towards 3 million distinct structures. The MOL table forms the basis of subsequent building blocks/fragments table FRA which is the actual source of virtual reactants, MOL can be used for direct screening purposes also. The FRA (fragments) table is the subset of UNQ with certain criteria applied which makes them suitable Virtual reactions (Mwt <= 350, heavy atom count <= 13). The FRA table is tending towards X. FRA use JCIDX. SMI is a table of “cleansed” SMILES in non-JChem, partitioned table for external file and docking. Cartridge functions used: JC_EXACT,JC_COMPARE and JC_INSERT. Oracle standards used: Oracle Packages, table partitions (JOIN), Optimiser hints (JOIN), large SGA as possible, locally managed Tablespaces. Note: Ultimately all fast search is completed in TOMCAT cache and available memory is required for this. On an Oracle server not all available physical memory is available for use and so using Tomcat in conjunction with Oracle Uses up any excess memory i.e. Java processing complete is completed in TOMCAT, PL/SQL is Oracle allocated memory and so uses the best of further available resources. Other Oracle performance feature like bulk collect may help speed up the “PL/SQL bit”.
Established synthetic transformations, reliable literature sources, reasonable yields…
Translation of real reaction to virtual really is completed on a case by case basis…
Automation adds some overhead and so should only process desired reactants (pharmacophore filters/undesirables removed)…
3d chemical space is exponentially larger than the “real time” commercial set, C-Space, covers and so in order to identify novel leads, virtual chemical space V-space needs to be generated and explored also. In order to be able to subsequently work with real world chemists, we have chosen to adopt a reaction based approach to generating our virtual chemical space / libraries. We see that this task can be completed in two ways below, either exhaustively or by using functional group filters in a de-novo led approach in order to define more tenable sets: De-Novo: Initial fast screen of C-space helps to define functional groups of interest for a particular protein cavity, these are placed in a project pha list. Generic functional groups of interest can be maintained in PHA of which pha can be a snapshot (A). Previous experience has shown that we should source virtual reactant input from tangible real world C–space, the FRA table is a viable subset (<400 Mwt) of the MOL table (B). FRA are maintained automatically from the C-space build, however PHA of interest are maintained in a more judicious way. A project copy of all available reactions can be defined from the master “RXN” table (C) and placed in “rxn” copy (D) this way only Linker/core/template of interest will be processed for the project. The relevant reactant and reaction SMARTS queries are extracted from RXN table are used to generate project level copy of the reactants of interest which are optionally placed in “rcta” and “rctb” (E) and of course react the reactants via CA reactor engine. The result is a focused project products table “FOC” (F) which will contain the results of many chosen reactions producing products with previously defined pharmacophores of interest only. Generating these sets require relatively less enumeration time, disk and memory consumption and subsequent screening time. We can then visualise and fast search our output with JSP (G) as we don’t expect the record numbers and thus memory requirements to be too limiting. All project level objects are treated as editable copies of their source tables. Exhaustive: Enumeration time, disk and memory consumption and subsequent screening time are significant factors here hence this approach is treated in a secondary manner as a back ground job that should not contend with primary processes for resource . For example the Amide reaction can currently yield 35 million + products from C-space FRA, most of which will not be of interest for the individual query. Data directly from FRA (B) can be processed by RXN package from RXN (C) into set of non-JChem EXH tables (H), which can then be queried through the cartridge JChem index. The memory requirements will certainly stop JSP visualisation using Tomcat on even relatively high specification hardware (memory!) but the set can be queried in a screening sense (I). In both cases updates to reactants in FRA table are carefully managed through to FOC and EXH so that, ideally “big queries” are only completed once. The JCartridge functions used in Oracle RXN package, which handles all processing are JC_REACT4, JCTF_REACT,JC_COMPARE,JC_INSERT,JC_MATCHCOUNT.
Works well in the real world! (~1000 Acid Halide, lots 1 or 2 amines) Works well in the virtual world! Easy way to join two fragments in a “linear” fashion, Good to use for all benchmarking! Where to stop in terms of accuracy of library vs speed and data redundancy Have a go at developing the Amide reaction to your satisfaction!
Reactions which we have found: Work in both the real and virtual worlds Enough reactants in the fragments set to warrant use is de-novo (or exhaustive) Introduce several points of diversity in the product molecule Produce drug like molecules that exhibit less conformers / pharmacophore hypothesis easier Can be reacted further in well known reactions Aromatic heterocyclic chemistry David T Davies !
Diagram of Aromatic Nitration: Reality Toluene goes all the way to TNT
Can use charge and reactivity/tolerance rules in order to emulate accurate output for this reaction (Maybe need to access the runtime charge data in order to make decisions regarding boundary) Step 1 in reality gives us mix of –o AND –p product, however to achieve end result could use specified numbers If step 1 goes to meta first then second product can be two isomers (end result is achieved irrespective)
Looking at reactions at alpha C only for now…
pKa in water can help to define likely kinetic/thermodynamic de-protonation regioselectivity Although pKa may not be directly relevant to actual solvent defined for reaction
Prochiral centre + primary alkyl halide can give two enantiomers at alpha C (SN2) Prochiral centre + secondary (chiral) alkyl halide can give 4 diastereoisomers (inversion if SN2/ inversion + retention if SN1 at electrophilic C) 3. Prochiral centre + Tertiary (chiral) alkyl halide can give 4 diastereoisomers (inversion + retention as likely SN1 at electrophilic C) Likely Enolate Alkylation occurs by as SN2 process so either only consider case 1 and 2 (+ enforce inversion) Possibly due to carbocation intermediate not approach Lithium counter ion conversely polar aprotic solvate the Lithium cation and generate bare enolate anion which may even react SN1 (additional effect is Carbocation is stabalised)? So maybe query should only get primary/secondary AlkylHalides? ~ 12000 1 or 2 Alkyl Halides many Carbonyl with possible alpha Carbon
Query results, intermediate, stereochemistry May find some “enforced” stereochemistry if use well defined inputs so need to run through set to define all outputs… Alternative is to standardize all the hits to remove stereochemistry and thus effectively generate intermediate species
So…might use most acidic selectivity rule + tolerance rule of x pka units either side of this up to kinetic or thermodynamic cut off point…In reality mixtures are always formed as equilibration occurs to a greater or lesser extent…
Stereo Chemistry needs to be explicitly defined… Could use standardizer in order to remove any retained chirality from alpha C reaction site… Mapping does not accurately reflect two step mechanism, so this is compression…
Frequently substituted Carbonyl are used for ring formation stereochemistry is naturally removed and propagation of correct configuration is of no further concern…regiochemistry is now a consideration though!
Alternatively extend virtual chemical space and don’t worry about chirality issues until after the molecule has been identified by screening to be of interest
Can be used as a catch all stereochemistry generator to further cover chemical space... Logical thing to do in a screening sense although subsequent chiral synthesis may be reasonably untenable Easier than carefully defining all possible stereo chemistry outcomes though…
/* Fast? */ BEGIN FOR recsa in cursA (ReactASmart) LOOP EXIT WHEN cursa%notfound; FOR recsb in cursB (ReactBSmart) LOOP EXIT WHEN when cursb%notfound; Options := 'method:n mappingStyle:c outFormat:sdf reactionID:amide reactantIDs:' || recsa.molecule_id || ',' || recsb.molecule_id || ' productIdTag:synthesis_id'; BEGIN outSDF := jcf_react4 (reaction,recsa.cd_smiles,recsb.cd_smiles,null,null,Options); porductSDF := jc_standardize (outSDF,’aromatize”); EXCEPTION WHEN OTHERS THEN COMMIT; END; IF productsdf IS NOT NULL THEN BEGIN cdidarr := jc_insert (productSDF,products,'jchemproperties', 'true','false','userDefColMap:synthesis_id=synthesis_id'); EXCEPTION WHEN OTHERS THEN COMMIT; END; END IF; COMMIT; productsdf := null; END LOOP; END LOOP; END; /* Faster? */ BEGIN INSERT INTO tab (smiles,synthesis_id) SELECT product,synthesis_code FROM reactant t1, reactant t2, TABLE (jctf_react4(reaction,t1.cd_smiles,t2.cd_smiles,null,null, 'reactionId:amide reactantIds:' || t1.molecule_id || ',' || t2.molecule_id || '')) WHERE jc_compare (t1.cd_smiles,ReactASmart,'t:s') =1 AND jc_compare (t2.cd_smiles,ReactBSmart,'t:s')=1; COMMIT; END; /* Fastest? */ BEGIN SELECT molecule_id,cd_smiles BULK COLLECT INTO vMoleculeIDsB,vSmilesB FROM reactant WHERE jc_compare(cd_smiles,ReactASmart,'t:s)=1; SELECT molecule_id,cd_smiles BULK COLLECT INTO vMoleculeIDsA,vSmilesA FROM reactant WHERE jc_compare(cd_smiles,ReactBSmart,'t:s')=1; FORALL indx IN vMoleculeIDsA.First .. vMoleculeIDsA.Last INSERT INTO product (smiles,synthesis_id) SELECT product,synthesis_code FROM TABLE(jctf_react4(reaction, SELECT * FROM TABLE (CAST (vSmilesA(indx) AS vSmilesType), SELECT * FROM TABLE (CAST (vSmilesB(indx) AS vSmilesType), null,null,'reactionId:amide reactantIds:' || SELECT * FROM TABLE (CAST (vMoleculeIDsA(indx) AS vMolIDType) || ',' || SELECT * FROM TABLE (CAST (vMoleculeIDsB(indx) AS vMolIDType) || '')); COMMIT; END;
Thanks for listening…
Print off equivalent to circulate…
Define you reaction in Marvin Sketch application using react buttons (ensure no red box around this) Save it as a .rxn file. Determine your query for reactant A and B and generate some sdf data (reality minimum 100 * 100). Edit the react.bat call for your reaction Run the react.bat call and generate your product sdf Run standardizer call and standardize your product sdf Create a JChem table in schema (using custom standardization) and import your standardizer sdf file View the table using the JSP application <URL> Edit PL/SQL, import reactant SDF into fragments table and run the anonymous PL/SQL block in order to “automate”. Use JSP application to view results .rxn and pl/sql template script available
Virtual Reaction Service Using Chem Axon Reactor July06
<ul><li>Trial Reactor implementation at Inhibox (briefly!) </li></ul><ul><li>Try it yourself developing the Amide reaction… </li></ul><ul><li>Some useful reactions/libraries we have developed </li></ul><ul><li>(Aromatic Heterocyclic Chemistry David T Davies) </li></ul><ul><li>Trial Calculator plug in Case 1: </li></ul><ul><li>Aromatic Nitration reaction using the charge measure </li></ul><ul><li>Trial Calculator plug in Case 2: </li></ul><ul><li>Enolate reaction using pKa measure </li></ul><ul><li>Best to try it yourself (each reaction has it’s own challenges!) </li></ul><ul><ul><li>Suggested approach to developing reactions (hand out) </li></ul></ul><ul><ul><li>Further exercises and general walk around Q&A until lunch… </li></ul></ul><ul><ul><li>I hope to learn about the reactions you would expect to implement! </li></ul></ul>Daniel Butler Workshop Overview
Why use reactor? Access relevant/target and novel set of chemical space for fast/accurate docking Importantly: Have a clear synthetic route to obtain real molecules
http//:www.inhibox.com Virtual screening company – speed up lead ID process <ul><li>Commercial molecules warehouse “C-space” </li></ul><ul><li>Reactor implementation to cover relevant chemical “V-space” </li></ul><ul><li>Ultra fast shape/electrostatics similarity matching tools development </li></ul><ul><li>Accurate scoring function and docking methods development </li></ul><ul><li>Protein site pharmacophore visualisation hypothesis (CCG/MOE) </li></ul><ul><li>Biological validation and QSAR analysis </li></ul>
Source of Virtual reactants is C - Space SDF JSP UNQ QUE QUE STG STG INT MOL SUP JOIN FRA SMI I handle all of the Java processing rather than aurora and so need memory too! My SGA needs to be as large as possible, but I should consider tomcat Mandatory Server Licence Is required for continious 24/7 ~3M recs ~1M recs
<ul><li>Established synthetic transformations </li></ul><ul><ul><li>Reliable literature source, available product data </li></ul></ul><ul><ul><li>Reasonable yields so as to promote possible multi-step synthesis </li></ul></ul><ul><ul><li>Known % composition/control of any isomeric outputs </li></ul></ul><ul><li>Sufficient available fragments (<400Mwt) in C-space </li></ul><ul><ul><li>Reactant functional groups available in commercial supplier database </li></ul></ul><ul><ul><li>Inexpensive reactants / easily obtainable </li></ul></ul><ul><ul><li>Small fragments if required for multi-step reactions </li></ul></ul><ul><li>Product molecules that are drug like </li></ul><ul><ul><li>produce natural templates with several points of diversity populated by reactants </li></ul></ul><ul><ul><li>real drug molecule criteria (donors/acceptors/Mwt<500) </li></ul></ul><ul><li>Product molecules that are target/design led </li></ul><ul><ul><li>Choosing reaction templates based on our “De-novo” geometry requirements for given target (ideally one template would be suitable) </li></ul></ul><ul><ul><li>Chemists should be able to define retro synthetic analysis around target and then locate the forward reactions and available reactants </li></ul></ul><ul><li>Expense of chemistry expertise / facilities </li></ul>Real reaction considerations?
<ul><li>Establish level of control </li></ul><ul><ul><li>What to build around reactor “atom mapping” (scope) </li></ul></ul><ul><ul><li>How to translate real to virtual world using reactor? </li></ul></ul><ul><ul><li>Is accurate regio-/stereo- diversity/control of product molecules ? </li></ul></ul><ul><ul><li>Is accurate Control/filter of Reactivity/Selectivity of reacting inputs? </li></ul></ul><ul><ul><li>Standardizer issues to consider pre/post reaction? </li></ul></ul><ul><li>Translating the real to virtual world </li></ul><ul><ul><li>Compression/resolution of mechanistic steps? Chemist will expect discrete reaction with clearly defined input/ output </li></ul></ul><ul><ul><ul><li>Literature may be presented in terms of several apparent steps? Possible to compress mechanism to a single mapping? (AmidoOximes example) </li></ul></ul></ul><ul><ul><ul><li>Generated in-situ / one pot but necessary to define as separate reactions for simplicity (Imidazoles example) </li></ul></ul></ul><ul><ul><ul><li>The reaction workflow has to be realistic otherwise untenable to Chemist </li></ul></ul></ul><ul><ul><li>How should one handle reactions/reactants that have fully defined stereochemistry or ill defined stereochemistry? </li></ul></ul><ul><ul><li>What is best use of chemical terms to define accurate reactions? Choice of plug-in for a given reaction? </li></ul></ul>Virtual reaction considerations?
Virtual reaction considerations <ul><li>Implementation/automation questions (Oracle) </li></ul><ul><ul><li>How to define, store and version our reaction repository – as SMARTS </li></ul></ul><ul><ul><li>Use reactor API directly in Java wrapper class? </li></ul></ul><ul><ul><li>Use Cartridge interface in PL/SQL wrapper package? </li></ul></ul><ul><ul><li>Which is the fastest/reliable implementation? </li></ul></ul><ul><ul><li>What useful information do we need to build around each reaction instance to automate checking? Synthesis ID (errors/isomers) </li></ul></ul><ul><li>Performance, data migration and tracking issues </li></ul><ul><ul><li>Resolution into separate reactant tables? </li></ul></ul><ul><ul><li>Ensure reactant query is equivalent to that defined in reaction (order is important!) </li></ul></ul><ul><ul><li>Visualisation of reactants or products or not at all? (Memory limitations) </li></ul></ul><ul><ul><li>Sum of all operations vs enumeration time (should apply Lipinski rules) </li></ul></ul><ul><ul><li>Required enumerations only and limit subsequent screening time of irrelevant data </li></ul></ul><ul><ul><li>Filter using Pharmacophore groups of interest (at project level)? </li></ul></ul><ul><ul><li>Filter out any undesirable functional group (Epoxides) in advance? </li></ul></ul><ul><ul><li>Implementation of Lipinski should be applied to minimum amount of records </li></ul></ul>
Virtual synthesis approach: De-Novo vs Exhaustive LOG JSP FRA PHA RXN PRJ EXH RXN FOC rxn pha JSP JSP rcta rctb I could also do with some disk space! Reactor is memory intensive PARTLY due to Oracle/Tomcat round trip… Multiple instances of tomcat are required As single instance has physical limit 1 2 Edit
Developing the Amide reaction Still allows Amide as reactant, Aniline type amine allowed Does not allow for secondary Amine Or Acid Bromide Does allow Amide Ideal definition? SMARTS reactivity rule 1 Ensure amide not included ..r:!match(ratom(4),'NC=O') SMARTS reactivity rule 2 Basicity criteria for Amine N ..r:!match(ratom(4),'NC=O') && (pka(ratom(4))>20)
Aromatic Heterocyclic reactions (2 steps AmidoOximes / 1,2,4 Oxadiazoles) (OXADI) ~1000 Acid Halide Two points of diversity for our pharmacophore fragments filter ~100M to choose from (AMIDO) The other tautomer is produced in reality ~100’000 C#N fragments avaiable HydroxylAmine reagent Comments Reaction definition
Developing Imidazoles (one step/regioisomers) Di-carbonyls ~1000 (IMIDA) 14 million + Regioisomers This is a one-pot reaction Aldehyde ~14000 Comments Reaction definition
Virtual Aromatic Nitration (charge) How accurate is selectivity order for more complicated molecules? <ul><li>Suggest use plug-in in conjunction with (one step behind) real chemistry for focused libraries </li></ul><ul><li>In accordance with observation, access runtime calculation data and use to determine the reactivity/tolerance cut off value(s) </li></ul><ul><li>Previously the charge plug-in / reactivity filter used to get simple “expected” results </li></ul>Try Simple Aromatic Nitration?
Case 2: pKa plug in applied to Enolate C reaction Possible de-protonations depending upon conditions… Logical resolve: Focus on trapped Enolate C reacting with say AlkylHalide/Aldehyde, not , Micheal additions, O-alkylation…which are separate atom mapping instance…
Kinetic vs Thermodynamic partition using pKa (water) range? pKa in water can help to define likely kinetic/thermodynamic de-protonation regioselectivity Although pKa value may not be directly relevant to actual solvent defined for reaction Abstraction of H pKa > 20 Alkene stability increases with substitution Abstraction of H pKa < 20 more likely de-protonation
Stereochemical consideration at C and electrophilic C Virtual implementations Real SN type reactions
How to approach stereochemistry I/O for all hits? 2. Alternative: Reaction “set” to cover all possible inputs, inversion/retention and outputs: Ret Inv <ul><li>Vanilla reaction + standardize reacting C only / remove all chirality / generate “intermediate” </li></ul><ul><li>Can this be done using Chemical terms? </li></ul>
Correct use of pKa plug in with Enolate – C? ..s:min(pka(ratom(a))..t:4 ? ..s:min(pka(reactant(0), filter(reactant(0), "match('[C;H1]')"), "acidic")) > 14.5)..t:4 ? pka < 21 Kinetic? LDA/THF/-78C pka > 21 Thermodynamic? LDA/THF/-78C Equilibrate / RT pKa view Molecule
Real vs virtual Aldol addition (E/Z)… Will need to define stereochemistry specifically + standardize reactant Virtual implementation Real reaction
Alkylation examples pka < 15 then Pyrimidines Subsequent Ring closure to Pyrimidines Real Enolate reaction
Resolved molecules cover chemical space comprehensively <ul><li>Proteins are inherently chiral and the small molecules they interact with in nature are to a large extent chiral. </li></ul><ul><li>Can extend virtual chemical space by creating all possible diastereoisomers from a single molecule starting point? </li></ul><ul><li>This is completed using Java built around the ChemAxon fast clean (3D) function which effectively identifies the Chiral centres </li></ul><ul><li>Followed by exploding the SMILES in 2D and combinatorially re-combine to generate set followed by ChemAxon SMILES parse. </li></ul><ul><li>Implemented in the workflow as a packaged Java Stored Procedure using 2 n type algorithm . </li></ul><ul><li>Recognised that chiral synthesis is an expensive / difficult undertaking and chiral leads are a rare beast! </li></ul>
Working closely with ChemAxon developers… I believe they are working on building this directly into reactor? (jc_standardize is available) Direct pre/post standardization built into reaction definitions (just realised how useful this is!) Helping to define fastest syntax for automated reaction - in particular Oracle cartridge table functions Speed of automated virtual reaction relatively slow (Oracle/Tomcat round trip) They swiftly provided the facility to easily create unique synthesis ID using reactant ID as a parameter We suggest a synthesis ID be part of reactor output to cover any isomers, possible errors ChemAxon response Request/issue
<ul><li>Reactor is a great tool to work with… </li></ul><ul><ul><li>care is required to correctly translate real world chemistry into virtual version - completed case by case </li></ul></ul><ul><li>Automation </li></ul><ul><ul><li>Running reactor outside of Oracle is super fast and highly scalable </li></ul></ul><ul><ul><li>R eactor via Oracle cartridge requires substantial memory as the Oracle/Tomcat round trip seems to be intensive </li></ul></ul><ul><ul><li>key at present – working closely with ChemAxon to implement “one trip” function in Oracle </li></ul></ul><ul><ul><li>Consider implement reactor in straight Java using jdbc to interact with Oracle, no round trip to Tomcat… </li></ul></ul><ul><li>Stereochemistry </li></ul><ul><ul><li>I/O issues covered by reaction “sets” or or by judicious standardizer (remove stereochemistry) application (can this be applied to reacting site atom only? </li></ul></ul><ul><ul><li>Use a diastereoisomer generator and don’t worry about stereochemistry until defined molecules of interest? </li></ul></ul><ul><li>Multiple step reactions – </li></ul><ul><ul><li>Only possible if single step are accurately defined, essentially not far off thereafter with suite of available evolving reactions </li></ul></ul><ul><ul><li>Building molecules to fill shape/electronic requirements and place functional groups with accurate geometry guided by de-novo fragments using reaction as template. </li></ul></ul><ul><li>Creating focused libraries – </li></ul><ul><ul><li>Calculator plug ins should be used in conjunction with real reaction data </li></ul></ul><ul><ul><li>Use fragments of interest only (SSS in addition to reacting functional group) to filter also </li></ul></ul><ul><ul><li>Start to think of reactions as template selection </li></ul></ul><ul><li>Misc </li></ul><ul><ul><li>Ensure reactions/reactants equate in query terms </li></ul></ul><ul><ul><li>Post reaction standardizer is required to clean output for inspection/import </li></ul></ul><ul><ul><li>Watch out for balanced mapping of implicit/explicit H atoms when dealing with N, O </li></ul></ul><ul><ul><li>May need to use NOT ring atom (RO) in certain ring formation reactions </li></ul></ul>Results, issues, conclusions and future…
Have a go, hands on suggestions… <ul><li>A - Build amide reaction and source the reactants from (fragments/acidhailde/amines) tables </li></ul><ul><li>B - Build Enolate (fragments/carbonyls/alkylhalides) tables </li></ul><ul><li>C - Build Aromatic Nitration reactions (fragments) table (nitration requires single reagent NO2+) </li></ul><ul><li>D - Run any of the pre-defined Aromatic heterocyclic reactions (documentsworkshop) </li></ul><ul><li>E - Try the “automated” version of a reaction using SMARTS in PL/SQL </li></ul><ul><li>F - Run the Enolate set using chemical terms filter (pKa) </li></ul><ul><li>G - Run Aromatic Nitration reaction using chemical terms filter (charge) </li></ul><ul><li>H – Well defined suite of reactions provided (Favourites ChemAxon reactor) : </li></ul><ul><li>http://www.chemaxon.com/jchem/examples/reactor/jsp/index.jsp </li></ul><ul><li>I – Implement any reaction you want to investigate? </li></ul><ul><li>Should have available tools: </li></ul><ul><ul><li>New Reactor GUI! </li></ul></ul><ul><ul><li>ChemAxon vanilla JSP application (subsequent SSS) (Favourites JCHEM JSP) </li></ul></ul><ul><ul><li>MarvinSketch (define reactions and reactants query) </li></ul></ul><ul><ul><li>MarvinViewer (quick view results) </li></ul></ul><ul><ul><li>C:jcheminReact.bat (run reaction using sdf inputsdocumentsworkshop) ) </li></ul></ul><ul><ul><li>C:jcheminStandardizer.bat (convert and standardize SDF outputs documentsworkshop ) </li></ul></ul><ul><ul><li>Oracle 9i and client side SQLPLUS (for automated call if required) </li></ul></ul><ul><ul><li>If you require a JChem table creating I can do this for you… </li></ul></ul>
Suggested way of working…use reactor GUI! Marvin Sketch .rxn .sma Marvin Viewer standardizer .bat jcman table jcman import pl/sql JSP sqlplus .sdf .sdf A.sma B.sma A.sdf B.sdf Client Server