Computer Applications in Drug Discovery and Development

348 Pages·1998·13 MB·English

by  India), S. Lakshmana Prabu (Anna University, India) and A. Umamaheswari (Anna University

A volume in the Advances in Medical
Technologies and Clinical Practice (AMTCP) Book
Series
Computer Applications
in Drug Discovery and
Development
A. Puratchikody
Anna University, India
S. Lakshmana Prabu
Anna University, India
A. Umamaheswari
Anna University, India
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Table of Contents
Preface..................................................................................................................................................xii
Acknowledgment................................................................................................................................ xvi
Chapter 1
DrugDiscovery:CurrentStateandFutureProspects............................................................................. 1
S. Lakshmana Prabu, Anna University, India
Chapter 2
ChemicalStructureDatabasesinDrugDiscovery............................................................................... 47
Pramodkumar Pyarelal Gupta, D. Y. Patil University (Deemed), India
Virupaksha Ajit Bastikar, Amity University Mumbai, India
Santosh Subhash Chhajed, MET Bhujbal Knowledge City, India
Chapter 3
LeadOptimizationintheDrugDiscoveryProcess............................................................................... 62
S. Lakshmana Prabu, Anna University, India
Rathinasabapathy Thirumurugan, Plants for Human Health Institute, USA
Chapter 4
QSARandLeadOptimization.............................................................................................................. 80
N. Ramalakshmi, C. L. Baid Metha College of Pharmacy, India
S. Arunkumar, Gulf Medical University, UAE
Sakthivel Balasubramaniyan, Anna University, India
Chapter 5
VirtualScreeningandItsApplicationsinDrugDiscoveryProcess................................................... 101
Gurusamy Mariappan, St. Mary’s College of Pharmacy, India
Anju Kumari, St. Mary’s College of Pharmacy, India
Chapter 6
ComputationalInvestigationofVersatileActivityofPiperine........................................................... 127
Thenmozhi Marudhadurai, Selvam College of Technology, India
Navabshan Irfan, Anna University, India


Chapter 7
TargetIdentifcationofHDAC8IsoformfortheTreatmentofCancer............................................... 140
A. Umamaheswari, Anna University, India
A. Puratchikody, Anna University, India
Sakthivel Balasubramaniyan, Anna University, India
Chapter 8
MolecularModellingStudiesofNovelCOX-2Inhibitors.................................................................. 173
A. Puratchikody, Anna University, India
A. Umamaheswari, Anna University, India
Navabshan Irfan, Anna University, India
Dharmaraj Sriram, Birla Institute of Technology and Sciences, India
Chapter 9
ConstructionandAnalysisofProtein-ProteinInteractionNetwork:RoleinIdentifcationofKey
SignalingMoleculesInvolvedinaDiseasePathway.......................................................................... 204
Divya Dasagrandhi, Bharathidasan University, India
Arul Salomee Kamalabai Ravindran, Bharathidasan University, India
Anusuyadevi Muthuswamy, Bharathidasan University, India
Jayachandran K. S., Bharathidasan University, India
Chapter 10
QualitybyDesigninPharmaceuticalFormulation............................................................................. 221
Sundaramurthy Vivekanandan, Bluefsh Pharmaceuticals Pvt. Ltd, India
Chapter 11
TheNextGenerationSequencingTechniquesandApplicationinDrugDiscoveryand
Development....................................................................................................................................... 240
Afzal Hussain, Maulana Azad National Institute of Technology, India
Chapter 12
SemanticTechnologiesforMedicalKnowledgeRepresentation........................................................ 260
Shridevi S., VIT Chennai, India
Saleena B., VIT Chennai, India
Viswanathan V., VIT Chennai, India
Compilation of References............................................................................................................... 276
About the Contributors.................................................................................................................... 325
Index................................................................................................................................................... 330
Detailed Table of Contents
Preface..................................................................................................................................................xii
Acknowledgment................................................................................................................................ xvi
Chapter 1
DrugDiscovery:CurrentStateandFutureProspects............................................................................. 1
S. Lakshmana Prabu, Anna University, India
Modernchemistryfoundationsweremadeinbetweenthe18thand19thcenturiesandhavebeenextended
in20thcentury.R&Dtowardssyntheticchemistrywasintroducedduringthe1960s.Developmentofnew
moleculardrugsfromtheherbalplantstosyntheticchemistryisthefundamentalscientifcimprovement.
About10-14yearsareneededtodevelopanewmoleculewithanaveragecostofmorethan$800million.
Pharmaceutical industriesspend thehighestpercentageof revenues,but theachievementofdesired
molecularentitiesintothemarketisnotincreasingproportionately.Asaresult,anapproximateof0.01%
ofnewmolecularentitiesareapprovedbytheFDA.Thehighestfailurerateisduetoinadequateefcacy
exhibited inPhaseIIof thedrugdiscoveryanddevelopmentstage. Innovative technologiessuchas
combinatorialchemistry,DNAsequencing,high-throughputscreening,bioinformatics,computational
drugdesign,andcomputermodelingarenowutilizedinthedrugdiscovery.Thesetechnologiescan
acceleratethesuccessratesinintroducingnewmolecularentitiesintothemarket.
Chapter 2
ChemicalStructureDatabasesinDrugDiscovery............................................................................... 47
Pramodkumar Pyarelal Gupta, D. Y. Patil University (Deemed), India
Virupaksha Ajit Bastikar, Amity University Mumbai, India
Santosh Subhash Chhajed, MET Bhujbal Knowledge City, India
Biologicallyactiveandapprovedmoleculeshaveattractedgreatinterestfromscientistsworkinginthe
therapeuticarea.Thishasgreatlyincreasedthepressureonthepharmaandlifescienceindustryinfueling
newmoleculestothemarket.Chemicalstructuredatabase,thebackboneofcheminformaticsandthe
bioinformaticsindustry,haswarehousedmillionsofactiveandnon-activemolecules/ligands/derivatives
ofdrugcompounds.Numerouspublicandprivatechemicaldatabasessupportthedrugdiscoveryprojects
bycontributingtheirdatasourceintermsof2D,3Dstructure,andannotationreportsindevelopmentof
efectivetherapeuticprojects.Inthischapter,theauthorsdiscussimportantchemicalstructuredatabases
andtheirdiversedatasetutilizationindrugdiscoveryprojects.


Chapter 3
LeadOptimizationintheDrugDiscoveryProcess............................................................................... 62
S. Lakshmana Prabu, Anna University, India
Rathinasabapathy Thirumurugan, Plants for Human Health Institute, USA
Discoveringanewdrugmoleculeagainstdiseaseisthemainobjectiveofdrugdiscovery.Leadoptimization
isoneoftheimportantstepsandactsasastartingpoint.Overtheyears,ithassignifcantlychanged
thedrugdiscoveryprocess.Itsmainfocusisthedevelopmentofpreclinicalcandidatesfrom“Hit”or
“Lead.”Leadoptimizationcomprisesleadselectionandoptimization,drugcandidateconfrmation,and
preclinicaldrugcharacterization.Leadoptimizationprocesscanimprovetheefectivenesstowardsits
targetpotency,selectivity,proteinbinding,pharmacokineticparameters,andtodevelopagoodpreclinical
candidate.Leadoptimizationfromhigh-throughputscreeningtoidentifcationofclinicaldrugcandidate
isaseamlessprocessthatdrawsnewtechniquesforacceleratedsynthesis,purifcation,screeningfrom
iterative compound libraries, validation, and to deliver clinical drug candidate with limited human
resources.Inconclusion,leadoptimizationphaseisdoneunderthesuggestionthattheoptimizedlead
moleculewillhaveactivityagainstaparticulardisease.
Chapter 4
QSARandLeadOptimization.............................................................................................................. 80
N. Ramalakshmi, C. L. Baid Metha College of Pharmacy, India
S. Arunkumar, Gulf Medical University, UAE
Sakthivel Balasubramaniyan, Anna University, India
Therearemanydiseasesforwhichsuitabledrugshavenotbeenidentifed.Asthepopulationincreases
and the environment gets polluted, new infections are reported. Random screening of synthesized
compoundsforbiologicalactivityistimeconsuming.QSARhasaprominentroleindrugdesignand
optimization.Itisderivedfromthecorrelationbetweenthephysicochemicalpropertiesandbiological
activity.QSARequationsaregeneratedusingstatisticalmethodslikeregressionanalysisandgenetic
functionapproximation.Both2Dparametersand3Dparametersareinvolvedingeneratingtheequation.
AmongseveralQSARequationsgenerated,thebestonesareselectedbasedonstatisticalparameters.
Validation techniques usually verify the predictive power of generated QSAR equations. Once the
developedQSARmodelisvalidatedtobegood,theresultsofthatmodelmaybeappliedtopredictthe
biologicalactivityofneweranalogues.ThischapterillustratesthevariousstepsinQSARanddescribes
thesignifcanceofstatisticalparametersandsoftwareusedinQSAR.
Chapter 5
VirtualScreeningandItsApplicationsinDrugDiscoveryProcess................................................... 101
Gurusamy Mariappan, St. Mary’s College of Pharmacy, India
Anju Kumari, St. Mary’s College of Pharmacy, India
Virtualscreeningplaysanimportantroleinthemoderndrugdiscoveryprocess.Thepharmacompanies
investhugeamountsofmoneyandtimeindrugdiscoveryandscreening.However,atthefnalstageof
clinicaltrials,severalmoleculesfail,whichresultsinalargefnancialloss.Toovercomethis,avirtual
screeningtoolwasdevelopedwithsuperpredictivepower.Thevirtualscreeningtoolisnotonlyrestricted
toolsmallmoleculesbutalsotomacromoleculessuchasprotein,enzyme,receptors,etc.Thisgives
aninsightintostructure-basedandLigand-baseddrugdesign.VSgivesreliableinformationtodirect

theprocessofdrugdiscovery(e.g.,whenthe3Dimageofthereceptorisknown,structure-baseddrug
designisrecommended).Thepharmacophore-basedmodelisadvisablewhentheinformationaboutthe
receptororanymacromoleculeisunknown.InthisADME,parameterssuchasLogP,bioavailability,
andQSARcanbeusedasflters.Thischaptershowsbothmodelswithvariousrepresentativeexamples
thatfacilitatethescientisttousecomputationalscreeningtoolsinmoderndrugdiscoveryprocesses.
Chapter 6
ComputationalInvestigationofVersatileActivityofPiperine........................................................... 127
Thenmozhi Marudhadurai, Selvam College of Technology, India
Navabshan Irfan, Anna University, India
Piperineisknownforitsversatiletherapeuticactivity.Ithasbeenusedforvariousdiseaseconditions(e.g.,
cold,cough,etc.).Piperineisanalkaloidfoundinblackpepper.Itpossessesvariouspharmacological
actionslikeanti-infammatory,anti-oxidant,anti-cholinergic,andanti-cancerous.Theabove-mentioned
propertieswillbestudiedbyselectingtargetproteinsCOX-2protein,angiotensinconvertingenzyme,
acetylcholineesterases, and survivin using computational docking study. This chapter explains the
inhibitionpropertyofpiperineagainstselectedtargetproteinfromtheresultsofdockingstudies.Based
onthedockingscoresandprotein-ligandinteractions,piperinewasfoundtobindwellintheactivesite
oftheselectedtargetproteins.Itensuresthebindingefcacyofpiperineagainstselectedtargetproteins.
Dockingscoresandprotein-ligandinteractionsplaysanimportantroleinitstherapeuticactivity.
Chapter 7
TargetIdentifcationofHDAC8IsoformfortheTreatmentofCancer............................................... 140
A. Umamaheswari, Anna University, India
A. Puratchikody, Anna University, India
Sakthivel Balasubramaniyan, Anna University, India
Targetidentifcationhasbeenconsideredasachiefparameterindrugdiscoveryasitfullycharacterizes
on-targetandof-targetefectsofdrugbinding.Cellsignalingreceptors,structuralproteins,andpost-
translationalmodifcationsofhistonesbyhistonedeacetylasesarethemostwidespreadtargetsthatare
progressivelybeingexplored.TheFDAapprovedhistonedeacetylasesinhibitorsandthemajorityof
HDACiinandoutofclinicaltrialsbasedontheactivitiesof11isoformsoftheenzymeinnon-selective
infuence approach. Unfortunately, reported HDACi does not possess a high degree of structural
specifcityandultimatelylessensthetherapeuticindexwithmanydoselimitingtoxicities.Thischapter
illustrateshowdiferentapproachesareincorporatedintothenovelinhibitorsdiscoverythataretruly
isoform-selectiveandwhicharespecifcallyinvolvedintargetingonlyaparticularisozyme.Further,it
highlightstheaspectsrelatingtoprovideawidertherapeuticindexwithanimprovedtoxicityprofleof
leadlikeepigeneticmodulators.
Chapter 8
MolecularModellingStudiesofNovelCOX-2Inhibitors.................................................................. 173
A. Puratchikody, Anna University, India
A. Umamaheswari, Anna University, India
Navabshan Irfan, Anna University, India
Dharmaraj Sriram, Birla Institute of Technology and Sciences, India

Molecularmodellingusestheoreticalandcomputationalchemistry,whichofersinsightintothenature
of molecular systems. This chapter highlights the theoretical explanation of molecular modelling
methodsanddescribesthedesigningofnoveltyrosineCOX-2inhibitorsusingmolecularmodellingas
anexample.Asafrststep,fragment-baseddrugdesignisusedtodesignthenoveltyrosineanalogues
andligand-baseddrugdesignsuchasQSAR,andpharmacophorewasusedtoidentifythedescriptors,
ensembleofstericandelectronicfeatures,whichisresponsiblefortheselectiveCOX-2inhibition.The
nextstep,structure-baseddrugdesign,wasusedtoanalysesintra-andintermolecularinteractionsin
thedrugreceptorsystemtoimprovethebindingafnityandpharmacokineticproperties.Finally,the
pharmacokineticandtoxicitypropertieswerepredictedquantitativelyusingrationalizationofobserved
structure-activityrelationshipsandtheresultsarereported.
Chapter 9
ConstructionandAnalysisofProtein-ProteinInteractionNetwork:RoleinIdentifcationofKey
SignalingMoleculesInvolvedinaDiseasePathway.......................................................................... 204
Divya Dasagrandhi, Bharathidasan University, India
Arul Salomee Kamalabai Ravindran, Bharathidasan University, India
Anusuyadevi Muthuswamy, Bharathidasan University, India
Jayachandran K. S., Bharathidasan University, India
Understandingthemechanismsofadiseaseishighlycomplicatedduetothecomplexpathwaysinvolved
inthediseaseprogression.Despiteseveraldecadesofresearch,theoccurrenceandprognosisofthe
diseasesisnotcompletelyunderstoodevenwithhighthroughputexperimentslikeDNAmicroarrayand
next-generationsequencing.Thisisduetochallengesinanalysisofhugedatasets.Systemsbiology
is one of the major divisions of bioinformatics and has laid cutting edge techniques for the better
understandingofthesepathways.Constructionofprotein-proteininteractionnetwork(PPIN)guidesthe
modernscientiststoidentifyvitalproteinsthroughprotein-proteininteractionnetwork,whichfacilitates
theidentifcationofnewdrugtargetandassociatedproteins.ThechapterisfocusedonPPIdatabases,
constructionofPPINs,anditsanalysis.
Chapter 10
QualitybyDesigninPharmaceuticalFormulation............................................................................. 221
Sundaramurthy Vivekanandan, Bluefsh Pharmaceuticals Pvt. Ltd, India
Qualitybydesign(QbD)isasystematic,scientifc,risk-basedapproachtoproductdevelopmentand
manufacturingprocesstoconsistentlydeliverthequalityproduct.Inthischapter,application,benefts,
opportunities, regulatory requirements involved inqualitybydesignofpharmaceuticalproductsare
discussed.Inqualitybydesignapproach,duringdevelopment,thedeveloperdefnesqualitytargetproduct
profle(QTPP)andidentifescriticalqualityattributes(CQA).Criticalprocessparameters(CPP)ofunit
operationswhichimpactscriticalqualityattributesneedtobeidentifedtounderstandtheimpactof
criticalmaterialattributes(CMA)onqualityattributesofthedrugproduct.Qualitybydesignapproach
isdefnedinICHguidelinesQ8–PharmaceuticalDevelopment,Q9–QualityRiskManagement,Q10–
PharmaceuticalQualitySystem.Thischapterdescribestheimplementationofnewconceptsinqualityby
designlikedesignofexperimentstoachievedesignspace,controlstrategytoconsistentlymanufacture
qualityproductthroughouttheproductlifecycle.