COMPUTATIONAL MODELING OF DRUGS AGAINST ALZHEIMER S DISEASE

642 Pages·2017·21.5 MB·English

Neuromethods 132
Kunal Roy Editor
Computational
Modeling of
Drugs Against
Alzheimer’s
Disease
N
EUROMETHODS
SeriesEditor
Wolfgang Walz
University ofSaskatchewan,
Saskatoon, SK,Canada
Forfurther volumes:
http://www.springer.com/series/7657
Computational Modeling of Drugs
Against Alzheimer’s Disease
Edited by
Kunal Roy
Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
Editor
KunalRoy
DepartmentofPharmaceuticalTechnology
JadavpurUniversity
Kolkata,India
ISSN0893-2336 ISSN1940-6045 (electronic)
Neuromethods
ISBN978-1-4939-7403-0 ISBN978-1-4939-7404-7 (eBook)
DOI10.1007/978-1-4939-7404-7
LibraryofCongressControlNumber:2017954502
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Preface to the Series
Experimental life sciences have two basic foundations: concepts and tools. The Neuro-
methodsseriesfocusesonthetoolsandtechniquesuniquetotheinvestigationofthenervous
system and excitable cells. It will not, however, shortchange the concept side of things as
carehasbeentakentointegratethesetoolswithinthecontextoftheconceptsandquestions
underinvestigation.Inthisway,theseriesisuniqueinthatitnotonlycollectsprotocolsbut
also includes theoretical background information and critiques which led to the methods
andtheirdevelopment.Thusitgivesthereaderabetter understandingoftheoriginofthe
techniquesandtheirpotentialfuturedevelopment.TheNeuromethodspublishingprogram
strikes a balance between recent and exciting developments, like those concerning new
animal models of disease, imaging, and in vivo methods, and more established techniques,
including immunocytochemistry and electrophysiological technologies. New trainees in
neurosciences still need a sound footing in these older methods in order to apply a critical
approachtotheir results.
Under the guidance of its founders, Alan Boulton and Glen Baker, the Neuromethods
serieshasbeenasuccesssinceitsfirstvolumepublishedthroughHumanaPressin1985.The
seriescontinuestoflourish throughmanychangesover the years. Itisnow published under
the umbrella ofSpringer Protocols. While methods involvingbrain researchhave changeda
lot since the series started, the publishing environment and technology have changed even
more radically. Neuromethods has the distinct layout and style of the Springer Protocols
program,designedspecificallyforreadabilityandeaseofreferenceinalaboratorysetting.
Thecarefulapplicationofmethodsispotentiallythemostimportantstepintheprocess
of scientific inquiry. In the past, new methodologies led the way in developing new dis-
ciplines in the biological and medical sciences. For example, physiology emerged out of
anatomyinthenineteenthcenturybyharnessingnewmethodsbasedonthenewlydiscov-
eredphenomenonofelectricity.Nowadays,therelationshipsbetweendisciplinesandmeth-
ods are more complex. Methods are now widely shared between disciplines and research
areas. New developments in electronic publishing make it possible for scientists that
encounter new methods to quickly find sources of information electronically. The design
of individual volumes and chapters in this series takes this new access technology into
account. Springer Protocols makes it possible to download single protocols separately. In
addition, Springer makes its print-on-demand technology available globally. A print copy
canthereforebeacquiredquicklyandforacompetitivepriceanywhereintheworld.
Saskatoon,SK,Canada WolfgangWalz
v
Preface
AccordingtoanestimatepublishedintheWorldAlzheimerReport2016(https://www.alz.
co.uk/research/world-report-2016),therewere46.8millionpeopleworldwidelivingwith
dementia(lossofmemoryandothercognitiveabilities)in2015,andthisnumberwillreach
131.5millionin2050.ThetotalestimatedworldwidecostofdementiaisUS$818billion,
anditwillbecomeatrillion-dollar diseaseby2018.Peoplelivingwithdementiahavepoor
access to appropriate healthcare, even in most high-income country settings, where only
around50%ofpeoplelivingwithdementiareceiveadiagnosis.Inlow-andmiddle-income
countries,lessthan10%ofcasesarediagnosed.
Alzheimer’s disease is the most common form of dementia. It is a lethal neurological
disorder due to progressive degeneration of various parts of the brain [1]. It gradually
destroyslearningskills,thinking,memory,andfinallytheabilitytocarryoutbasicactivities
ofdailyliving.Alzheimer’sdisease(AD)ismultifactorial,involvinggeneticandenvironmen-
tal factors, and it apparently involves several different etiopathogenic mechanisms. It has
been identified as a protein misfolding disease due to the accumulation of abnor-
mally folded amyloid beta proteins in the brains of Alzheimer’s patients. The root cause as
well as treatment of AD is unknown, while several hypotheses exist such as the cholinergic
hypothesis, amyloid hypothesis, tau hypothesis, etc. Currently, four FDA-approved drugs
(rivastigmine, galantamine, donepezil, memantine) are available in the market, and these
only provide symptomatic relief. Although research has revealed a number of biological
targets,specificdrugmoleculesagainstthesetargetsshowingacompletecureofthedisease
still remain unknown. Thus, it is of timely need to develop an effective treatment strategy
againstthedisease.
Computational modeling techniques including quantitativestructure–activity relation-
ship (QSAR), pharmacophore mapping, homology modeling docking, virtual screening,
and other cheminformatics approaches play a vital role in the finding and optimization of
leads in any drug discovery program. Computational modeling helps to understand the
important molecular features contributing to the binding interactions with the target
proteins thus facilitating the design of new potential compounds and prediction of activity
of designed compounds which have not yet been tested. These approaches can save time,
money, and more importantly animal sacrifice in the complex, long, and costly drug
discoveryprocess.
Thisvolumeunder theNeuromethodsseriesdescribesdifferentcomputationalmethods
encompassing ligand-based approaches (QSAR, pharmacophore), structure-based
approaches(homologymodeling,docking,moleculardynamicssimulation),andcombined
approaches (virtual screening) with applications in anti-Alzheimer drug design. Different
background topics like molecular etiologies of Alzheimer’s disease, targets for new drug
development,anddifferentcheminformaticsmodelingstrategieshavealsobeencoveredfor
completeness. Special topics like multi-target drug development, natural products, protein
misfolding, and nanomaterials have also been included in connection with computational
modelingofanti-Alzheimerdrugdevelopment.
Chapter 1 authored by Awanish Kumar and Ashwini Kumar gives an introduction to
Alzheimer’sdiseaseandpresentsanoverviewofthepathophysiologyanddiseaseetiologies.
Differentpromisingtargetsforanti-Alzheimerdrugdevelopmentarealsodiscussed.
vii
viii Preface
Chapter 2 authored by Sergi Go´mez-Ganau, Jesu´s Vicente de Julia´n Ortiz, and Rafael
Gozalbes gives a brief introduction to different computational drug design approaches,
mainly QSAR, molecular docking, pharmacophore development, and molecular dynamics
simulations. Some recent applications of these techniques for design of anti-Alzheimer
agentsarealsobrieflymentioned.
Chapter3authoredbyAgostinhoLemos,RitaMelo,IrinaS.Moreira,andM.Nata´liaD.
S.CordeirofocusesontheroleofG-protein-coupledreceptors(GPCRs)inthepathogenesis
ofAD.Different structure-and ligand-basedinsilicoapproaches and theirapplicability on
the development of small molecules that target various GPCRs potentially involved in AD
arediscussedinthischapter.
Chapter 4 authored by Livia Basile discusses on virtual screening as a tool to select
quicklyandeconomicallycompoundsendowedwithoptimumphysicochemical,pharmaco-
kinetic,andbiologicalpropertiesforthedevelopmentofnewpotentialdrugcandidates.The
use of virtual screening for the design of specific ligands for targets related with AD is
discussedwithexamples.
Chapter 5 authored by Eugene V. Radchenko, Vladimir A. Palyulin, and Nikolay S.
Zefirovdiscussesonmolecularfieldtopologyanalysis(MFTA)asaQSARmethoddesigned
to model the activities mediated by small molecules binding to biotargets using the local
physicochemical descriptors reflecting the major types of ligand–target interactions. The
design of potential anti-Alzheimer and other neuroprotective compounds based on the
MFTAstructure–activitymodelsisdescribed.
Chapter 6 contributed by Irini Doytchinova, Mariyana Atanasova, Georgi Stavrakov,
IrenaPhilipova,andDimitrinaZheleva-Dimitrovadescribesadocking-basedtechniquefor
thedesigningofgalantaminederivativeswithdual-sitebindingfragments–oneblockingthe
catalytic site and another blocking the peripheral anionic site of acetylcholinesterase. The
study illustrates the efficiency of the docking-based design of galantamine derivatives as
acetylcholinesteraseinhibitors.
Chapter7authoredbyOdailsonSantosPaz,ThamiresQuadrosFroes,FrancoHenrique
Leite,andMarceloSantosCastilhofocusesontheimportanceofcomputationaltoolsinthe
hit identification and lead optimization steps with reference to anti-Alzheimer drug devel-
opment. The theory and application of different computational tools for development of
BACE-1inhibitorsasanti-Alzheimeragentsaredescribed.
Chapter 8 contributed by Yoshio Hamada and Kenji Usui discusses a novel “electron-
donorbioisostere”conceptindrugdiscoverystudyandreportsthedesignofpotentBACE1
inhibitors using this concept. The authors suggest that a quantum chemical interaction,
suchasσ–πinteractionorπ–πstacking,playsacriticalroleinBACE1inhibitionmechanism.
Chapter 9 authored by Maricarmen Herna´ndezRodrı´guez, Leticia Guadalupe Fragoso
Morales, Jose´ Correa Basurto, and Martha Cecilia Rosales Herna´ndez focuses on inhibition
of Aβ production and aggregation as an important therapeutic strategy to design com-
pounds against AD. This chapter analyzes the applications of molecular docking and
molecular dynamics simulations to estimate the binding energy and binding pose of com-
poundsthatcouldavoidAβ42aggregation.
Chapter 10 authored by Praveen P. N. Rao and Deguo Du focuses on computational
tools to study and design amyloid aggregation inhibitors and modulators. The authors
describe an in silico method that uses the Aβ hexapeptide-derived steric-zipper octamer
assembly as an alternative and effective model to predict the binding interactions of planar
small molecule libraries with complex Aβ structures including oligomers, protofibrils, and
fibrils.
Preface ix
Chapter 11 authored by Kailas Dashrath Sonawane and Maruti Jayaram Dhanavade
deals with the applications of computational methods to investigate structure–function
relationship of enzyme Aβ complex and to design new lead molecules to control amyloid
beta peptide levels in Alzheimer’s disease. Different molecular modeling methods like
energyminimization,moleculardocking,moleculardynamicssimulation,virtualscreening,
binding free energy, solvent-accessible surface calculations, etc. have been discussed in this
connection.
Chapter 12 authored by Prabu Manoharan and Nanda Ghoshal focuses on gamma
secretase (GS) as an attractive therapeutic strategy to slow down the pathological progres-
sion ofAD.This chapter provideswith a detaileddiscussion ona QSAR-guidedfragment-
basedvirtualscreeningmethodforGSinhibitordesignandidentification.
Chapter 13 authored by Carlos Navarro-Retamal and Julio Caballero focuses on tau
hyperphosphorylation, which is related to the formation of amyloid plaques and neurofi-
brillary tangles in Alzheimer’s disease patients. Molecular modeling studies on complexes
between proline-directed protein kinases, which are responsible for tau hyperphosphoryla-
tion,andtheirinhibitorsaredescribedinthischapter.
Chapter 14 authored byMangeRam Yadav, Mahesh A. Barmade, RupeshV. Chikhale,
andPrashantR.Murumkarfocusesonrolesofproteinkinasesinthehyperphosphorylation
of tau protein in AD. The computational studies carried out on various protein kinases in
searchofpotentialanti-Alzheimeragentsarecriticallydiscussed.
Chapter 15 contributed by A´da´m A. Kelemen, Stefan Mordalski, Andrzej J. Bojarski,
andGyo¨rgyM.Keseru˝ focuseson5-hydroxytryptaminereceptor6(5-HT R)asatargetfor
6
drugdevelopmentforalleviatingcognitive,learning,andmemorydeficitsrelatedtoAlzhei-
mer’s disease. The authors discuss the use of ligand- and structure-based methods for the
design of new 5-HT R antagonists and highlight advantages and limitations of
6
corresponding approaches and computational modeling tools in the field of 5-HT R drug
6
design.
Chapter 16 contributed by Dionysia Papagiannopoulou and Dimitra Hadjipavlou-
Litina focuses on radionuclide imaging techniques and molecular imaging agents for the
in vivo detection of amyloid plaques in Alzheimer’s disease. The authors review in this
chaptercomputationalmodelingstudiesperformedonPETandSPECTimagingagentsin
connectionwithAlzheimer’sdisease.
Chapter 17 authored by Manika Awasthi, Swati Singh, Sameeksha Tiwari, Veda P.
Pandey, and Upendra N. Dwivedi discusses the recent advances in the application of
cheminformatics methods to quantify the chemical diversity and structural complexity of
natural products and analyze their arrangement in chemical space with respect to the
treatmentofAD.Theauthorsalsodiscusstheadvancementinvirtualscreeningto system-
atically identify bioactive compounds from natural products databases and the progress in
target identification methods to discover molecular targets of compounds from natural
originwithreferencetoAD.
Chapter 18 authored by Luciana Scotti and Marcus T. Scotti discusses in silico studies
reportedonnaturalproductswithreferencetoanti-ADdrugdevelopment.Theauthorsalso
discuss multi-target QSAR models which can be used to predict activity or classify com-
poundsasactivesorinactivesagainstdifferenttargets,suchasproteins(amyloid-A4protein
(ABPP), glycogen synthase kinase-3 alpha, glycogen synthase kinase-3 beta (GSK-3β),
monoamineoxidaseB(MAO-B),andpresenilin-1(PSN-1)).
Chapter19contributedbyAkhilKumarandAshokSharmafocusesondual-ormulti-
target inhibitors which halt multiple disease-causing pathways and improve the disease
x Preface
conditions.Theauthorsdescribevariouscomputationalmethodstoscreenandidentifytop
hits and molecular dynamics to ensure the affinity in terms of binding free energy of the
receptor–ligandcomplextodesignmulti-target-directedligandsforAlzheimer’sdisease.
Chapter 20 authored by Gerald H. Lushington, Frances E. S. Parker, Thomas H. W.
Lushington,andNoraM.Wallacefocusesonmisfoldingofcentralnervoussystemproteins
intoenergeticallyfavoredphysiologicallydysfunctionalformsleadingtoseveralneurological
disorders.Theauthorsdiscussthefundamentalphysiologicalissuesthatcauseneuropathies
and suggest the ways in which molecular docking and molecular dynamics simulations can
be brought to bear in formulating testable hypotheses that can form a basis for the
systematicformulationofanewgenerationofmedicines.
Chapter 21 contributed by R. Navanietha Krishnaraj, Dipayan Samanta, and Rajesh
K. Sani discusses the potential of nanomaterials for the treatment of AD. This chapter
addresses the advantages of computational analysis of ADME (absorption, distribution,
metabolism, and excretion) characteristics, the druglikeness of nanomaterials, and the role
ofmoleculardockingtechniquesforassessingthetherapeuticefficacyofnanomaterials.
Iamsurethatthiscollectionof21chapterswillbehelpfultoresearchersworkinginthe
field of anti-Alzheimer drug research. I am especially thankful to the series editor Prof.
Wolfgang Walz for his help during the development of this book and to the publisher for
bringingoutthisvolume.
Kolkata,India KunalRoy
Contents
Prefacetotheseries............................................................ v
Preface ..................................................................... vii
Contributors................................................................. xv
PART I AN INTRODUCTION TO THE DISEASE
1 Alzheimer’sDiseaseTherapy:PresentandFutureMolecules ................. 3
AwanishKumarandAshwiniKumar
PART II COMPUTATIONAL MODELING METHODS
FOR ANTI-ALZHEIMER AGENTS
2 RecentAdvancesinComputationalApproaches
forDesigningPotentialAnti-Alzheimer’sAgents ........................... 25
SergiGo´mez-Ganau,Jesu´sVicentedeJulia´n-Ortiz,andRafaelGozalbes
3 Computer-AidedDrugDesignApproachestoStudyKey
TherapeuticTargetsinAlzheimer’sDisease ................................ 61
AgostinhoLemos,RitaMelo,IrinaS.Moreira,
andM.Nata´liaD.S.Cordeiro
4 VirtualScreeningintheSearchofNewandPotent
Anti-AlzheimerAgents .................................................. 107
LiviaBasile
5 MolecularFieldTopologyAnalysis(MFTA)intheDesign
ofNeuroprotectiveCompounds .......................................... 139
EugeneV.Radchenko,VladimirA.Palyulin,andNikolayS.Zefirov
PART III MODELING OF LIGANDS ACTING AGAINST
SPECIFIC ANTI-ALZHEIMER DRUG TARGETS
6 GalantamineDerivativesasAcetylcholinesteraseInhibitors:
Docking,Design,Synthesis,andInhibitoryActivity......................... 163
IriniDoytchinova,MariyanaAtanasova,GeorgiStavrakov,
IrenaPhilipova,andDimitrinaZheleva-Dimitrova
7 ModelingofBACE-1InhibitorsasAnti-Alzheimer’sAgents ................. 177
OdailsonSantosPaz,ThamiresQuadrosFroes,
FrancoHenriqueLeite,andMarceloSantosCastilho
8 DesignofAnti-Alzheimer’sDiseaseAgentsFocusing
onaSpecificInteractionwithTargetBiomolecules.......................... 207
YoshioHamadaandKenjiUsui
xi