by Abraham Heifets A thesis submitted in conformity with the requirements for the degree of Doctor

155 Pages·2013·7.62 MB·English

AUTOMATED SYNTHETIC FEASIBILITY ASSESSMENT: A DATA-DRIVEN DERIVATION OF
COMPUTATIONAL TOOLS FOR MEDICINAL CHEMISTRY
by
AbrahamHeifets
Athesissubmittedinconformitywiththerequirements
forthedegreeofDoctorofPhilosophy
GraduateDepartmentofComputerScience
UniversityofToronto
(cid:13)c Copyright2014byAbrahamHeifets
Abstract
AutomatedSyntheticFeasibilityAssessment: AData-drivenDerivationofComputationalToolsforMedicinal
Chemistry
AbrahamHeifets
DoctorofPhilosophy
GraduateDepartmentofComputerScience
UniversityofToronto
2014
The planning of organic syntheses, a critical problem in chemistry, can be directly modeled as resource-
constrained branching plans in a discrete, fully-observable state space. Despite this clear relationship, the full
artilleryofartificialintelligencehasnotbeenbroughttobearonthisproblemduetoitsinherentcomplexityand
multidisciplinarychallenges. Inthisthesis,Idescribeamappingbetweenorganicsynthesisandheuristicsearch
andbuildaplannerthatcansolvesuchproblemsautomaticallyattheundergraduatelevel. Alongtheway,Ishow
theneedforpowerfulheuristicsearchalgorithmsandbuildlargedatabasesofsyntheticinformation,whichIuse
toderiveaqualitativelynewkindofheuristicguidance.
ii
Contents
Relationtopublishedwork xi
1 Introduction 1
2 Prolegomenatoanyfutureautomatedsynthesisplanning 6
2.1 Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 AND/ORgraphsearchalgorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2.1 AO* . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2.2 LearninginDepth-FirstSearch(LDFS) . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.3 Thequestionofcyclesemantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2.4 ProofNumberSearch(PNS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.5 PN* . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2.6 ProofDisproofSearch(PDS). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2.7 Depth-First Proof Number and variants (DFPN, DFPN+, DFPN(r), DFPN-TCA, and
DFPN-SNDA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3 Theshapesofchemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.4 Challengesoforganicsynthesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.5 Automatedorganicsynthesisplanners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.5.1 LHASAanditsvariants(interactivesynthesisplanners) . . . . . . . . . . . . . . . . . . 29
2.5.2 Noninteractivesynthesisplanners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.6 Heuristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.6.1 Complexity-based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.6.2 Fragment-based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.6.3 Machinelearningandretrosyntheticanalysis . . . . . . . . . . . . . . . . . . . . . . . . 40
2.7 Reactionlibraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
iii
2.8 Thecriticalneedforsearchguidance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3 Adeclarativedescriptionofchemistry 49
3.1 Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4 Retrosyntheticsearchalgorithms 55
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.2 AProofNumberSearch-basedSolver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.3 ConstructingaPublicChemistryBenchmark. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.4 ResultsandDiscussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.5 ChapterConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5 Compilationofsynthesisandchemicaldata 66
5.1 SCRIPDB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.2.1 Patentsasasourceofchemicalimages . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
5.2.2 Patentsasbiomedicalliterature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
5.2.3 Patentsasareactiondatabase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
5.2.4 Patentsasabioisosterecatalog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.3 ChapterConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
6 Domain-specificheuristicsforsyntheticfeasibility 75
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
6.1.1 Humans,eh? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.1.2 Objectivemeasuresofsyntheticfeasibility . . . . . . . . . . . . . . . . . . . . . . . . . 80
6.2 MaterialsandMethods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.2.1 Datacollection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.2.2 Datacleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
6.2.3 Datalabeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
6.2.4 Datamodeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
6.3 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
6.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
6.5 ChapterConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
7 Summary&Conclusion 100
iv
Appendices 103
A Glossary 104
B Whichmoleculesshouldbebuilt? 107
B.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
B.2 Systemandmethods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
B.2.1 Correspondenceofboundligands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
B.2.2 Ligandalignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
B.2.3 Residueclusterextractionviacliquedetection. . . . . . . . . . . . . . . . . . . . . . . . 115
B.3 Resultsanddiscussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
B.3.1 Heme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
B.3.2 Nicotinamideadeninedinucleotide. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
B.4 ChapterConclusionandFutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Bibliography 127
v
List of Figures
2.1 Cyclical AND/OR graphs. Semicircles connect paths in a single hyperedge. Double circles in-
dicategoalstates. Theexamplesaredeliberatelysimple; equivalentyetmore-realisticexamples
maybegeneratedbyreplacingsimplearcswithlargersubgraphs. . . . . . . . . . . . . . . . . . 14
2.2 Ifadescendantnodecanbereachedviamultiplepaths,thenEquations2.1and2.2arenolonger
correct. An example schematic when a node has repeated precursors showing the (dis)proof
counts will be incorrect. In this case, there are only 3 leaf nodes but the root reports a count
of4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3 GraphhistoryinteractionproblemfromKishimotoandMu¨ller(2004). AssumenodeDisaloss
for the player at the root. Node B is an AND node, marked by an semicircle connecting its out
arcs. NodesC,G,andHareANDnodesaswellbutarenotmarkedbecausetheyhaveasingle
outgoingarc. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.4 Aspirin. Vertices labeled C, H, or O denote carbon, hydrogen, and oxygen atoms, respectively.
Edgesdrawnwithsinglelinesdenotesinglebondsanddoublelinesrepresentdoublebonds. Typ-
ically,bondstohydrogenarenotdrawn. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.5 Esterificationreactionofanalcoholactivesitewithananhydrideactivesitetoproduceanester.
Atoms in the molecular fragments are numbered to help the reader track bond changes. When
atomiclabelsareomitted,thevertexispresumedtobeacarbonatomwithsufficienthydrogensto
total4bonds. Reactionconditionshavebeenomittedforsimplicity. . . . . . . . . . . . . . . . . 26
2.6 Synthesis of aspirin (right column) from carbon dioxide, sodium hydroxide, phenol, acetic acid
and ketene starting materials (left column) via the precursor molecules, salicylic acid (top mid)
andaceticanhydride(bottommid). Thefinalaspirin-formingstepisanapplicationoftheesteri-
ficationreactiondepictedinFig2.5. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.7 Palytoxin, a 409-atom molecule synthesized in 1994 (Suh and Kishi, 1994). Bonds depicted as
wedgesindicatethebondisangledoutoftheplaneofthepapertowardthereader.Bondsdepicted
asdashesindicatethebondisangledawayfromthereader. . . . . . . . . . . . . . . . . . . . . 28
vi
2.8 ExamplefromTodd(2005). Structure(40)depictsthequinoneDiels-Alderreaction,while(41)-
(43) show natural products that had been synthesized using the quinone Diels-Alder. LHASA
doesnotapplythequinoneDAtothesecases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.9 8stepsynthesisfromTakahashietal.(1990). Molecularcomplexityproceedsnonmonotonically. . 32
2.10 Figure 19 from Boda et al. (2007) depicting minimum, maximum, and average synthetic acces-
sibilityscoresbyfivemedicinalchemists. Structuresaresortedbyaveragescore. Moleculesof
particularlywidescoredisagreementarelabeled. Mostmoleculeshavescoresof4±1andmany
haverangeswhichoverlap. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.11 Figure7fromHuangetal.(2011)depictingminimum,maximum,andaveragesyntheticaccessi-
bilityscoresbyfivemedicinalchemists. Structuresaresortedbyaveragescore. Mostmolecules
havescoresof4±1andmanyhaverangeswhichoverlap. . . . . . . . . . . . . . . . . . . . . . 35
2.12 Examplecomparisonofsyntheticcomplexitymeasures, takenfromBaroneandChanon(2001).
Syntheticprogressisnonmonotonic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.13 Reaction example from Pirok et al. (2006) depicting a Friedel-Crafts Acylation reaction. Ad-
ditional properties specify the charge necessary at the active site for the reaction to complete.
Problematiccompoundsareexcludedwithadditionalpatterns. . . . . . . . . . . . . . . . . . . . 42
2.14 Diels-AlderexamplefromWilcoxandLevinson(1986). Lines1and4showtworeactions. Lines
2 and 3 are the MXC and CXC, respectively, for the first reaction. Line 5 shows the maximum
commonsubstructurefromthetworeactions(notetheactivatingelectron-withdrawingoxygenon
thedieneophile). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.15 ExamplefromLawetal.(2009). Figure(a)depictsasamplereaction,while(b)and(c)showan
extractedcoreandextendedcore,respectively. ComparetotheMXCandCXCfromFigure2.14.
Lawetal. notethatthenon-chemically-essentialatom2iscorrectlynotincludedintheextended
core;incontrast,abondradiusapproachsuchas(SatohandFunatsu,1999)wouldhaveincludedit. 46
4.1 The benchmark target molecules. Images generated directly from the problem definition using
OpenBabelO’Boyleetal.(2011a). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.2 Computer-generatedAtorvastatinsynthesismatchingthesynthesisreportedinBroweretal.(1992)
andRoth(2002). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
vii
5.1 Cumulative SCRIPDB content. Although SCRIPDB includes patents from 2011, we show data
through2010,thelastcompleteyear. (a)LeftpanelshowsthenumberofChemDrawCDXstruc-
turefiles,andthestructuresdescribedtherein,availableinSCRIPDBforvariousyears.SCRIPDB
contains 4,814,913 CDX files from 2001 through 2010, comprising 10,840,646 molecules. Du-
plicate molecules were filtered from each patent but not across patents, as described in the text.
(b)Rightpanelshowsthenumberofpatentsanddetailsthesubsetcontainingreactions. For2001
through2010,SCRIPDBcontains107,560patents,ofwhich25,048containsyntheticreactions. . 68
5.2 Example Markush structure from US Patent 6,268,504 (Raveendranath et al., 1999) defining a
chemicalclassviasubstituent,positional,andfrequencyvariations. . . . . . . . . . . . . . . . . 68
5.3 Structures per patent in SCRIPDB. While 34,789 patents contain ten or fewer structures, two-
thirdsofpatentscontainmorethantenand1,296patentscontainmorethanathousandstructures. 69
5.4 NumberofCDXdatafileswiththatcontainvariousnumbersofreactionarrows. . . . . . . . . . 70
5.5 Sampleofsearchresultsformoleculescontaininganacridinesubstructure. . . . . . . . . . . . . 71
6.1 ChartfromBodaetal.(2007)depictingminimum,maximum,andaveragesyntheticaccessibility
scores by five medicinal chemists. Structures are sorted by average score. Molecules of par-
ticularly wide score disagreement are labeled. (This is Figure 2.10, duplicated here for reader
convenience.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
6.2 Chart from Ertl and Schuffenhauer (2009) depicting the average of chemist scores for 40 test
molecules,inblue. Theerrorbarsdenotethestandarderrorofthemeanofscoresby9chemists.
Therefore, to translate to standard deviation the bars would need to be tripled in size. Struc-
turesaresortedbyaveragescore. Moleculesofparticularlywidescoredisagreementbetweenthe
averagechemistscore,inblue,andtheirsoftware’sscores,inred,arelabeled. . . . . . . . . . . . 79
6.3 Data flow schematic depicting the processing steps in each of the collection, cleaning, labeling,
andmodelingstages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
6.4 ExamplesynthesisfromUSPatent7,238,717(Flemingetal.,2007). “ProcedureA(Synthesisof
Weinreb Amides)” is described in the patent as: “ Asubstitutedanthranilicacid(24mmol)wasdissolved
inacetonitrile(200mL),1.05equivalentsofN,Odimethylhydroxylaminehydrochloride,1.05equivalentsofEDC,0.05
equivalents of dimethylaminopyridine and 1.0 equivalent of triethylamine were added and the reaction was stirred at
roomtemperatureovernight.Theacetonitrilewasremovedbyrotaryevaporationandtheresiduewaspartitionedbetween
ethyl acetate and water. The organic layer was washed with brine then concentrated to a residue. The residue was
chromatographedonsilicagel(ethylacetateaseluent)togivetheproduct.Typicalyieldsare70-90%”. . . . . . . . . 83
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6.5 AvailableboundingboxesaroundgeometricentitiesintheChemDrawfilesdistributedwithUSPTO
patents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.6 Difficultvisualparsingexample.Whichmoleculesarereagentsandwhichareproducts,forwhich
reactionstep? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
6.7 CDX reading example. First bounding boxes (in blue) are computed for each molecule. Then
theminimumdistancebetweenfragmentsismeasured(ingreen),andusedtocomputemeanand
standarddeviationforinter-moleculedistance. Moleculesintersectingwith2standarddeviations
from an arrow head or tail (dashed purple arrow) are considered possible reagents or products,
andareclassifiedasdescribedinthetext. Thethreebottommoleculesoverlapand,therefore,are
groupedintoanenclosingboundingbox(inorange). Becausethisboxenclosesanarrow, these
moleculesarerejected. Similarly,becausethecentralarrowintersectslinesegments(inthecenter
blackcircles)wecannotassignuniquedirectionforthearrowanditisrejected. . . . . . . . . . . 86
6.8 Illustrative schematic of organic synthesis. Although there are 8 reaction arrows depicted, the
A→Breactionisrepeatedfourtimesanditislikelythatonly5reactionswererunatthebench.
AssumingthatAandCarestartingmaterials,Algorithm5labelsAandCasrequiringzerosteps,
Brequiring1,Drequiring2,Erequiring3,Frequiring4,andGrequiring5. . . . . . . . . . . . 88
6.9 Distributionofthelabelsformoleculesinthetrainingdata. . . . . . . . . . . . . . . . . . . . . 93
6.10 The predictive performance on the automatically-labelled training data for the top 3 algorithms
fromTable6.1andrandomforestforcomparison. TheplotsweregeneratedwithR;thelinearfit,
R2andp-valueswerecomputedusingR’slmlinearmodel. . . . . . . . . . . . . . . . . . . . . 95
6.11 The predictive performance on the automatically-labelled external validation data for the top 3
algorithmsfromTable6.1andrandomforestforcomparison. TheplotsweregeneratedwithR;
thelinearfit,R2andp-valueswerecomputedusingR’slmlinearmodel. . . . . . . . . . . . . . 96
6.12 ThepredictiveperformanceonthemanuallyscoreddatafromErtlandSchuffenhauer(2009)for
thetop3algorithmsfromTable6.1andrandomforestforcomparison. Theplotsweregenerated
withR;thelinearfit,R2andp-valueswerecomputedusingR’slmlinearmodel.Forcomparison,
ErtlandSchuffenhauer(2009)reportthatther2 among9chemistsonthese40moleculesranged
from0.450to0.892,withanaverageof0.718. . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
B.1 LigAlignFlowchart. Thethreestagesofligand-basedactivesitealignment,namelyligandcorre-
spondence,ligandalignment,andclusterdetection,areshownalongwiththetechniquesusedto
accomplisheachstage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
ix
B.2 Topological vectors encode atom counts as a function of bond distance from a selected atom.
Forexample,thenumbersnexttotheatomsdepicttheminimalbonddistancefromatomA.The
topologyvectorforBis[3,5,1]indicatingthreeatomsatdistance1,fiveatomsatdistance2,and
oneatomatdistance3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
B.3 AsequencealignmentofP450homologsandextractedpatterns,ascomputedbyMUSCLEEdgar
(2004)usingdefaultsettings. ThecolorscorrespondtothedefaultClustalcoloringscheme. Four
biologically-significantregionsNebel(2006)areboxedandnumberedandtheconservedcysteine
residue from PROSITE pattern PS00086 is marked. The first five rows comprise the input pro-
teins; the next five rows show the subset of residues marked as conserved by LigAlign; the last
tworowsaretheconservedresiduesintheresultsreportedbyNebel. . . . . . . . . . . . . . . . 118
B.4 Aligand-basedalignmentofP450homologsshowingthesharedhememoiety(coloredtan)sur-
rounded by the residue clusters detected by LigAlign. The patterns labelled in Figure B.3 are
distinguishedbycolor. Pattern1isshowninpurple;pattern2isdarkblue;pattern3isgreen;and
pattern4ispresentedinred. Clusteredresidueswhicharenotmembersofoneofthesepatterns
areshowninlightgrey. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
B.5 A rigid minimal-RMSD ligand-based alignment of the NAD ligand from the 21 NAD-binding
proteinslistedinTableB.1.ThesharedNADligandiscoloredtan.Consistentclustersofresidues
are shown surrounding the ligand. Hydrophobic residues (LVAGIMP) are depicted as orange
lines; acidic residues (DE) are shown as pink lines. Red spheres correspond to the location of
structurallyconservedwatermolecules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
B.6 FragmentationoftheboundNADligandfrom1HDR(eachrigidfragmentisshowninadifferent
color), after fragmentation but before alignment to the green pivot NAD ligand in 1HDX. The
NADmoietiesofnicotine,nicotineribose,nicotinephosphate,adeninephosphate,adenineribose,
andadeninearelabeled. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
B.7 AproteinalignmentusingonlythenicotinemoietyoftheNADligand(showninadashedcircle).
ThesharedNADligandiscoloredtan. Themisalignmentinducedbynicotinealignmentonthe
non-nicotine moieties is apparent. Consistent clusters of residues, as listed in Table B.2, are
shownsurroundingtheligand. TheunderlinedC5clusterwasidentifiedbyflexiblealignmentbut
was not detected by rigid alignment. Hydrophobic residues (LVAGIMP) are depicted as orange
lines;basicresidues(RHK)arebluelines. Redspherescorrespondtothelocationofstructurally
conservedwatermolecules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
x