RATIONAL DRUG DESIGN

RATIONAL DRUG DESIGN

Drug Design & Discovery: IntroductionDrugs:Natural sourcesSynthetic sourcesTargets:

Ideal Drug1) target: bio-molecule ,involved in signalingor metabolic pathways, that are specific todisease process by either protein-protein orprotein-nucleicproteinnucleic acid interactions.interactions2)antagonist action-inhibiting functions of thedisease causing proteins.3) Inhibiting interactions of the proteins.4)Activates other proteins, that are deregulatedin such disease like cancer.

Discovering and Developing the‘One Drug’

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Drug Design- Molecular Modeling- Virtual ScreeningIdentify diseaseIsolate proteininvolved indisease (2-5 years)Find a drug effectiveagainst disease protein(2-5 years)Scale-upPreclinical testing(1-3 years)Human clinical trials(2-10 years)FormulationFDA approval(2-3 years)

1)challenging2)Expensive3)Time consumingSo, Multidisciplinary approach:Computational tools, methodologies for structure guided approach Global genexpression data analysis by softwares.Hence,1)Efficiency increased2)Cost effectiveness3)Time saved4)Strategies to overcome toxic side effects

Medicinal chemists today arefacing a seriouschallenge because of the increased cost and enormousamount of time taken to discover a new drug, and alsobecause of fierce competition amongst different drugcompanies .

GENOMICS, PROTEOMICS & BIOPHARM.Potentially producing many more targetsand “personalized” targetsHIGH THROUGHPUT SCREENINGIdentify diseaseScreening up to 100,000 compounds aday for activity against a target proteinVIRTUAL SCREENINGUsing a computer topredict activityIsolate proteinCOMBINATORIAL CHEMISTRYRapidly producing vast numbersof compoundsFind drugMOLECULAR MODELINGComputer graphics & models help improve activityIN VITRO & IN SILICO ADME MODELSTissue and computer models begin to replace animal testingPreclinical testing

Drug Discovery overviewApproaches to drug discovery: Serendipity (luck) ChemicalC e ca Modificationod cat o Screening Rational

ways:A) Development of ligands with desired properties fortargets having known structure and functions.B)Development of ligands with predefined properties fortargets whose structural information may be or may notbe known.This, unknown target information can be found by globalgene expression data.

In 1970s the medicinal chemists considered moleculesas topological entities in 2 dimension (2D) withassociated chemical properties.QSAR concept became quite popular. It wasimplemented in computers and constituted firstgeneration rational approach to drug design

The acceptance by medicinal chemists of molecularmodeling was favored by the fact that the QSAR wasnow supplemented by 3D visualization.The “lock and key” complementarily is actuallysupportedt dbby 3D model.d l ComputerCt aidedid d molecularl ldesign (CAMD) is expected to contribute to intelligentlead .

Ancient times: Natural products with biological activitiesused as drugs.Chemical Era: Synthetic organic compoundsRationalizing design process: SAR & ComputationalChemistry based DrugsBiochemical era: To elucidate biochemical pathways andmacromolecular structures as target as well as drug.

NMR and X-raystructure determinationQM, MM methodsQSAR/3D QSARStructure-based drug designRational drug designModel constructionMolecular mechanicsConformational searchesMolecular dynamicsCombinatorial chemistryChemical similarityChemical diversityHomology modelingBioinformaticsChemoinformatics

Molecular Graphics: Visual representationof molecules & their properties.Computational Chemistry:Chemistry: Simulation ofatomic/molecular properties of compoundthrough computer solvable equations.( b’b’-b’0)[ V1cos ] b’( - 0) [V1cos ]Statistical Modeling:Modeling: D-R, QSAR/3QSAR/3-D QSAR Molecular dataInformation Management:Management: Organizational databases retrieval/search & processing of properties of 10001000 of compounds.MM Computation Visualization Statistical modeling Molecular Data Management

(A) MOLECULAR MECHANICS (MM)(B) QUANTUM MECHANICS (QM)

Quantum Mechanics (QM)Ab-initio and semiAbsemi--empirical methodsConsiders electronic effect & electronicstructure of the moleculeCalculates charge distribution and orbitalenergiesCan simulate bond breaking and formationUpper atom limit of aboutatoms

Molecular Mechanics (MM)Totally empirical technique applicable toboth small and macromolecular systemsa molecule is described as a series ofcharged points (atoms) linked by springs(bonds)The potential energy of molecule isdescribed by a mathematical function calleda FORCE FIELD

When Newton meets Schrödinger.Sir Isaac Newton(1642 - 1727)F maErwin Schrödinger(1887 - 1961)Ĥ

When Quantum Chemistry Starts to Move.Traditional ParrinelloMDClassical MDSimulations

Mixed Quantum-Classicalin a complex environment - QM/MMMain ideaPartitioning the system into1. chemical active partt t d bytreatedb QM methodsth d2. Interface region3. large environment that ismodeled by a classicalforce fieldClassical MMinterfaceQM

Mixed Quantum-Classicalin a complex environment - QM/MMMain ideaPartitioning the system into1. chemical active partt t d bytreatedb QM methodsth d2. Interface region3. large environment that ismodeled by a classicalforce fieldClassical MMinterfaceQM

Receptor nGenerate 3D structures,Similarity/dissimilarityHomology modellingHTS, Comb.Comb ChemistryActive Site SearchReceptor Based DDde NOVO design,3D searching(Build the lock, then find the key)(Build or find the key that fits the lock)Indirect DDLigand-Based DDAnalogs DesignRational Drug Design(Structure-based DD)Molecular Docking(Drug-Receptorinteraction)2D/3D QSAR &Pharmacophore

Computer Aided Drug Design Techniques- Physicochemical Properties Calculations- Partition Coefficient (LogP), Dissociation Constant (pKa) etc.- Drug Design- Ligand Based Drug Design- QSARs- Pharmacophore Perception- StructureSt tBasedB d DrugDDesignD i- Docking & Scoring- de-novo drug design- Pharmacokinetic Modeling (QSPRs)- Absorption, Metabolism, Distribution and Toxicity etc.- Cheminformatics- Database Management- Similarity / Diversity Searches-All techniques joins together to form VIRTUAL SCREENING protocols

QSARs are the mathematical relationships linking chemical structures withbiological activity using physicochemical or any other derived property as aninterface.Biological Activity f (PhysicoPhysico--chemical properties)Mathematical Methods used in QSAR includes various regression andpattern recognition techniques.Physicochemical or any other property used for generating QSARs is termedas Descriptors and treated as independent variable.Biological property is treated as dependent variable.

Compounds biological activityQSARNew compounds withimproved biological activity

Receptor-based Drug Design Examine the 3D structure of the biological target (an X-ray/ NMRstructure. Hopefully one where the target is complexed with a small moleculeligand (Co-crystallized) Look for specific chemical groups that could be part of an attractiveinteraction between the target protein and the ligand. DesignDesign a new ligands that will have sites of complementaryinteractions with the biological target.Advantage: Visualization allowsdirect design of molecules

Put a compound in the approximate area wherebinding occursDocking algorithm encodes orientation ofcompound and conformations.Optimize binding to proteinMinimize energyHydrogen bondingHydrophobic interactionsScoring

Can pursue both receptor and pharmacophore-based approachesindependently If the binding mode of the ligand and target is known,information from each approach can be used to help the otherIdeally, identify a structural model that explains the biologicalactivities of the known small molecules on the basis of theirinteractions with the 3D structure of the target protein.

Typical projects are not purely receptor or pharmacophore-based;theyy use combination of information, hopefullypy synergisticallyy gy

Drug Design Successes (Fruits of QSAR)Name of the drug discovered1. Erythromycin analogs2. New Sulfonamide dervsdervs.3. Rifampicin dervs.dervs.4. Napthoquinones5. Mitomycins6. Pyridine –2-methanol’s7. Cyclopropalamines8. -Carbolines9. Phenyl oxazolidines10.Hydantoin dervs.10dervs.11.Quinolones11Biol. ntiAntimalerialsAntileukemiaSpasmolyticsMAO inhibitorsMAO InhibitorsRadioprotectivesAnti CNSCNS--tumorsAntibacterial

While we are still waiting for a drug totally designedfrom scratch, many drugs have been developed withmajor contributions from computational methodsOONHCO2HFNMeONEtHNHOdonepezil (1996)Alzheimer's treatmentacetylcholinesterase inhibitorshape analysis and docking studiesN NHNNNNSO2MeOnorfloxacin (1983)antibioticfirst of the 6-fluoroquinolonesQSAR studiesClNBulosartan [Cozaar] (1995)angiotensin II antagonistanti-hypertensiveModeling Angiotensin II octapeptideOONHHSSO2NH2dorzolamide [Trusopt] (1994)glaucoma treatmentcarbonic anhydrase inhibitorSBLD and ab initio calcsHNNMe2zolmatriptan [Zomig] 19955-HT1D agonistmigraine treatmentMolecular modeling

HIV-1 protease inhibitorsNPhHNOHNNNHNOOSindinavir [Crixivan] (Merck, 1996)X-rayy data from enzymeyand molecular mechanicsMeHOSPh OONHNMeHNNHOPhHnelfinivir [Viracept] (Agouron, 1996)OHONHSONritonavir [Norvir] (Abbott, OHCONH2OHNHHsaquinavir [Invirase, Fortovase] (Roche, 1990)transition state mimic of enzyme substrate

Drug Discovery is a multidisciplinary, complex, costly andintellect intensive process.Modern drug design techniques can make drug discoveryprocess more fruitful & rational.Knowledge management and technique specific expertise cansave time & cost, which is a paramount need of the hour.

Approachestodrugdiscovery: Serendipity(luck) ChemicalModification Screening Rational. ways: A)Development of ligands with desired properties for targets having known structure and functions. B)Development of ligands with predefined properties for targets whose structural information may be or may not be known.