Comenius University, Faculty of Natural Sciences, Department of Organic Chemistry, Bratislava, Slovakia

Medicinal ChemistryMedicinal Chemistry(Basic Principles)

24th November 2010 Andrej Boháč, Milan Remko

151 527 D(1 356 AA)

Molecular drugs

348

:

435.5 D

1

http://www.pdb.org/

COOBiogenic aminoacids

•• Unpolar Unpolar (8) – (lipophilic) R

HH3N

Alanine (Ala; A)

Valine(Val; V)

Leucine(Leu; L)( a; )

Me- iPr- iBu-

Isoleucine(ILE; I)

sBu-

Methionine(Met; M)

CH3S(CH2)2-

Phenylalanine(Phe; F)PhCH2-Bu CH3S(CH2)2 PhCH2

Tryptophan(Try; W)

(indol 3 yl)CH

Proline(Pro; P)(CH )(indol-3-yl)CH2- -(CH2)3-

covalent bonds > ionic bonds > hydrogen bonds > van der Waalsvan der Waals interactionsinteractions

Biogenic aminoacids COO

•• PPolarolar (7) – (hydrophilic) R

HH3N

Glycine(Gly; G)

Serine(Ser; S)

Threonine(Thr; T)(Gly; G)

H-

(Ser; S)HOCH2-

(Thr; T)HOCHCH3

│

Cysteine Tyrosine AsparagineCysteine(Cys; C)HSCH2-

Tyrosine(Tyr; Y)

para-HOPh-CH2-

Asparagine(Asn; N)

NH2COCH2-Glutamine

(Gln; Q)NH2CO(CH2)2-2 ( 2)2

covalent bonds > ionic bonds > hydrogenhydrogen bondsbonds > van der Waals interactions

Biogenic aminoacids COO

•• IonizedIonized (5)– (hydrophilic) R

HH3N

Lysine Arginine Histidine

CH2

HN

HN

(Lys; K)H3N+(CH2)4-

(Arg; R)H2N(NH2

+)CNH(CH2)3-(His; H)

HN

Aspartic acid(Asp; D)

Glutamic acid(Glu; E)

-OOCCH2-( ; )

-OOC(CH2)2-

covalent bonds > ionic bonds ionic bonds >> hydrogen bonds hydrogen bonds > van der Waals interactions

Interaction analysis

Electrostatic interactions: (5-10 kcal mol-1), (C-C: 80 kcal /mol)

Hydrogen bonds:vary in strenght (1-6 kcal mol-1)

Van der Waals interactions: are very weak (0.5 -1 kcal mol-1 )

Hydrogen bondsHydrogen bonds

Th l t d fi i t h d i ll d h d b d d (HBD)• The electron deficient hydrogen is called a hydrogen bond donor (HBD)• The electron rich heteroatom is called a hydrogen bond acceptor (HBA)

X H Y TargetDrug X

TargetHYδ+δ+

δ- δ-δ-δ-

X HDrug

Y Target

HBD HBA HBA HBD

•• Optimum orientationOptimum orientation is where the Xis where the X--H bond points directly to the lone H bond points directly to the lone pair on Y such that the pair on Y such that the angle between X, H and Y is 180angle between X, H and Y is 180oo

YX H YX H

Hybridisedorbital

Hybridisedorbital

1sorbital

HBAHBAHBDHBD

orbitalorbital orbital

Hydrogen bondsHydrogen bonds

•• strongstrong hydrogen bondhydrogen bond acceptorsacceptors (HBA)(HBA)strongstrong hydrogen bond hydrogen bond acceptorsacceptors (HBA)(HBA)-- carboxylatecarboxylate ion, phosphate ion, tertiary amineion, phosphate ion, tertiary amineRCORCOOO--, RP(=O)(, RP(=O)(OO--))22, R, R33NN

•• moderatemoderate hydrogen bond hydrogen bond acceptorsacceptors (HBA)(HBA)-- carboxylic acid, amide oxygen, carboxylic acid, amide oxygen, ketoneketone, ester, ether, alcohol, ester, ether, alcoholRCRCOOOOH RC(=H RC(=OO)NHR)NHR´́ RC(=RC(=OO)R)R´́ RCRCOOOORR´́ RROORR´́ RROOHHRCRCOOOOH, RC(=H, RC(=OO)NHR)NHR , RC(=, RC(=OO)R)R ,RC,RCOOOORR , R, ROORR , R, ROOHH

•• poor poor hydrogen bond hydrogen bond acceptors acceptors (HBA)(HBA)-- sulphur, fluorine, chlorine, aromatic ring, amide nitrogen,sulphur, fluorine, chlorine, aromatic ring, amide nitrogen,sulphur, fluorine, chlorine, aromatic ring, amide nitrogen,sulphur, fluorine, chlorine, aromatic ring, amide nitrogen,aromatic aminearomatic amineS, F, S, F, ClCl, , PPhh, RC(=O), RC(=O)NNHRHR´́, , ArArNNHH--

•• goodgood hydrogen bondhydrogen bond donorsdonors (HBD)(HBD)•• goodgood hydrogen bond hydrogen bond donorsdonors (HBD)(HBD)-- quaternary ammonium ionquaternary ammonium ion RR33HHNN++

9

Induced dipole interactionsInduced dipole interactions

•• ooccurccur where thewhere the charge on one molecule induces a dipole oncharge on one molecule induces a dipole onooccurccur where the where the charge on one molecule induces a dipole on charge on one molecule induces a dipole on anotheranother

•• between abetween a quaternary ammonium ion and an aromatic ringquaternary ammonium ion and an aromatic ringbetween a between a quaternary ammonium ion and an aromatic ringquaternary ammonium ion and an aromatic ring((LysLys, , ArgArg))

RR NNRR33

++δδ−−

δ+δ+

Binding siteBinding site

What is medicinal chemistry?What is medicinal chemistry?

• definitely not a basic chemistry course for medical students

• interdisciplinary research dedicated to development of new drugs (not only)

• drug development basic chronology: 

selection of disease ( di l t i i f ti h dit t l )selection of disease (cardiovascular, autoimmune, infectious, hereditary, mental, cancer …)

molecular mechanism of the pathology (medicine, molecular biology)

selection of a key biomolecule to influencenew active structure/compound identification: in Silico design HTSnew active structure/compound identification: in Silico design, HTS,of organic molecules possessing appropriate drug‐like properties(biologists, computer chemists) 

organic synthesis (chemists)

biological or biophysical assays (biologists)biological or biophysical assays (biologists)

optimization of activity and other molecular propertiesIP protection + clinical trials + up‐scale synthesis + approval

How many new drugs reach the k t l ?

• DD is highly interdisciplinar time and resources consuming process:

market yearly?DD is highly interdisciplinar, time and resources consuming process: 10 years / from 870 000 000 to 2000 000 000 USD /1 new drug 

Adams C, Brantner V . Health Aff airs (Millwood) 2006 25 420–8.

• global production ca 24 innovative drugs (new chemical entity) / year 

(2009: 26, 2008: 25, 2007: 18, 2006: 22, 2005: 26, 2004: 24, 2003: 26, (2002: 28, 2001: 23, 2000: 26)

• Many failures have been recorded in high stages of drug development,l l l ) h bl ?even in clinical trials)Where is a problem?

Drug‐likeness is often missing.Computer aided rational drug design is preferred to predict activityand bioavailability even before the compound is prepared.

What kind of compounds are d ?drugs?

• Different inorganic, more likely organic compoundse e t o ga c, o e e y o ga c co pou dsand biomolecules (proteins, antibodies, siRNA…) that activatesor inhibits the function of a target with benefit to thepatient

activity (target binding place stereoelectronic compatibility)

low toxicity (selectivity, antitargets: CYP, hERG, Pglycoprot...) 

bi il blitbioavailablity (physico‐chemical and pharmacological properties ensuring drug‐likeness)

Basic terms in medicinal chemistrymedicinal chemistry

• TARGET (biomacromolecule to interfere with)BINDING POCKET ACTIVE SITE• BINDING POCKET – ACTIVE SITE(part of the target appropriate to bind a small ligand)

• PHARMACOPHORE(a part of a molecule that is recognized at a receptor site and is responsible for that molecule's biological activity)receptor site and is responsible for that molecule s biological activity)

• LIGAND organic molecule possessing target affinity, that has to be stereo-electronically compatible with binding pocket)

ACTIVE is a compound detected by usually HTSACTIVE is a compound detected by usually HTSHIT active compound identified in a screen with confirmed structure and activity, that need to be developed into lead compoundLEAD active compound with convenient properties: drug-likeness, solubility, p p p g , y,synthetic feasibility, patentabilityDRUG CANDIDATE high activity, good selectivity, in vivo efficiency DRUG after success in clinical trials approved by FDA, EMEA

• DRUG-LIKENESS complex properties including (ADME/Tox: Absorption Distribution Metabolism Excretion / Toxicity)

StereoelectronicStereoelectronic compatibilitycompatibilityStereoelectronicStereoelectronic compatibilitycompatibility((requirementsrequirements in space and charge distributionin space and charge distribution))

Free Biological DB - UNIPROT

• http://www.uniprot.org/

(gene, AA sequences, biomolecular properties)

http://www.uniprot.org/

From were to get active compounds?

Micro-organisms (bacteria, fungi)Marine chemistr ( l b t i fi h t )

compounds?

A) The Natural World

Marine chemistry (corals, bacteria, fish etc)Plant life (flowers, trees, bushes)Animal life (frogs, snakes, scorpions)Biochemicals (neurotransmitters, hormones)Pure natural products, bioextracts (e.g. plant, or microbial) Ethnopharmacology (Chinese traditional medicine...)

B) The Synthetic WorldLMW synthetic compounds(traditional, combinatorial synthesis, historical

t h i l ll ti i lcorporate chemical collections, commercial sources), SelOoptSideActivities (known drugs)

C) The Virtual World Computer aided drug design (CADD)

to call them „active compounds“ evaluation through biological screening is essential

SOSA = Selective Optimization of Sid A ti itiSide Activities

Exploitation of Existing Drugs as Leads for the Discovery of NewDrugs

all drugs act on more than one target (known and unknown)all drugs act on more than one target (known and unknown),resulting in a several side effects

advantage: drugs and many compounds that underwent clinicaladvantage: drugs and many compounds that underwent clinical development have an established safety profile. Many of them can be therefore safely administered to humans. 

Try to transform one of the side activities into the major effectand strongly reduce their initial pharmacological activity.

C. G. Wermuth Drug Discov Today 2006, 11, 160; J. Med. Chem. 2004, 47, 1303.

DD - flowchartDD flowchart

Case story from HTS to Leadst S h i b i ith• at Schering begins with– HTS of 700,000 compounds, followed by focused librarydesign and repeat HTS of about 2,000 single compounds.g p g pSending 200 compounds forward for IC50 assaying. Theresult is 100 IC50 actives. Purity and structural evaluationsbring the number down to 50 validated actives.g

– subsequent in vitro efficacy, selectivity, and toxicologystudies produce 15 clusters (or single compounds) of"qualified hits"qualified hits .

– qualified hits must be resynthesized to yield morecompound for subsequent in vitro and in vivo evaluations.These evaluations conclude with the identification of 13 leadThese evaluations conclude with the identification of 13 leadstructures (or clusters) after about a 10‐month period, andthese structures are then moved forward into the leadoptimization processoptimization process.

– (13 / 700 000 = 1 / 53 846 enrichment)

What should compound fulfill to b d ?become a drug?

• Biol. active, chemically stable compound possessing appropriate:appropriate:

pharmacodynamic properties (activity, selectivity)pharmacokinetic properties (bioavailability: ADME/TOX)others (novelty scale up synthesis )others (novelty, scale up synthesis...)

• > 30% of all drug failures can be attributed to poor physiochemical properties: Log P (Log D), pKa, and solubility all have impacts on drug absorption and diffusion in vivodrug absorption and diffusion in vivo

Chemical Space

Chem Space: 1060 - 10200

DB f 11 t C N O F 26 400 000 t bl

Lead‐like Drug‐likeDrugs

DB of 11 atoms C,N,O, F: 26 400 000 stable compounds (110.9 M if stereoisomers included)J.-L. Reimond J. Chem. Inf. Model. 47 2007 342.

Cell Membrane – protects cell compartmentcompartment

• provides a hydrophobic barrier around the cell, preventing the passage of water and polar molecules. Proteins (receptors, ion channels and carrier proteins) are present, floating in the cell membrane.

• phospholipid bilayer, the hydrophobic tails interact with each other by van der Waals interactions and are hidden from the aqueous mediavan der Waals interactions and are hidden from the aqueous media

• The polar head groups (phosphatidylcholine) interact with water at the inner and outer surfaces of the membrane

BioavailabilityBioavailability• (in vitro) active compound, to perform as drug, has to reach its

t t i th h b d (i i )target in the human body (in vivo)

• Drug-likeness is qualitative concept to estimate bioavailability fromthe molecular structure before the substance is synthesized. Thedrug-like molecule has to have:

optimal MW and number of HBD, HBA (affecting solubility and absorption)

optimal water and fat solubility logP (octanol / water) (intestinal lining,aqueous blood penetrate cellular membrane to rich inside the cell) Theaqueous blood, penetrate cellular membrane to rich inside the cell) Thedistribution coefficient (Log D) is the correct descriptor for ionisablesystems. log D is pH dependent (e.g. at pH = 7.4 is the physiological pH ofblood serum)

Lipinski's Rule of Five (Ro5)

Lipinski Ro5(all numbers are multiples of five empiric rule)(all numbers are multiples of five, empiric rule) 

for prediction of bioavailability (not activity!) to quicklyeliminate compounds that have poor physicochemicalproperties for oral bioavailabilty• an orally active drug has no more than one violation of the• an orally active drug has no more than one violation of the 

following criteria:MW ≤ 500Lipophilicity (logP ≤ 5) octanol‐water partition   coefficient (better log D ≤ 5 respecting the ionic states present at physiological pH values)physiological pH values)

Sum of hydrogen bond donors ≤ 5 (NH,OH)Sum of hydrogen bond acceptors ≤ 10 (N,O)y g p ( , )

C. A. Lipinski et al. Adv. Drug Del. Rev. 1997, 23, 3. (Ro5)Greg M. Pearl et al., Mol. Pharmaceutics, 2007, 4, 556–560. (log D introduced)

Additional drug-like parametersAdditional drug like parameters

MW ≤ 500

Lipophilicity (logP ≤ 5) octanol‐water partition   coefficient

Sum of hydrogen bond donors ≤ 5 (NH,OH)y g ( , )

Sum of hydrogen bond acceptors ≤ 10 (N,O)

PSA < 140 Å2(Molecular Polar Surface Area – sum of surfaces of polar atoms (N,O...with H) that correlates with human intestinal and BBB b i ) f d BBB i (PSA 60 Å2)absorption) for good BBB penetration (PSA < 60 Å2)

Number of rotatable bonds < 10 (flexibility factor)(high NRB → many conformers)

Ertl, P. in Molecular Drug Properties, R. Mannhold (ed), Wiley-VCH , 2007, 111 – 126.

Ro5 determined from 2D tructure////http://www.molinspiration.comhttp://www.molinspiration.com

Ertl, P. et al., J. Med. Chem. 2000, 43: 3714‐3717. (molecular property prediction toolkit )

Ro5 violations

Absorption as f(PSA, LogP)Absorption as f(PSA, LogP)

• AlogP http://www vcclab org/ (Virtual Computational Chemistry Laboratory)• AlogP http://www.vcclab.org/ (Virtual Computational Chemistry Laboratory)

(membrane transport connected with fat and water solubility)

• log pKa http://ibmlc2.chem.uga.edu/sparc/index.cfm(i fl bi di Ki d l l P)(influences binding Ki and also logP)

Intestinal and other absorption• % ABS = 109 – 0 345 PSA (good when %ABS > 30 %)• % ABS = 109 – 0.345 PSA (good when %ABS > 30 %)

(lower PSA, higher absorption)Zao YH et al. Pharm Res 2002, 19, 1446-1457.

Brain Blood Barrier penetrationBrain Blood Barrier penetration• LogBB = -0.0148 PSA + 0.152 CLogP + 0.139

(to estimate CNS penetration and possible side effects)BB = C-brain / C-blood CNS l BB 0 5 ( id ff t )CNS: logBB > -0.5 (side effects) non CNS: logBB < -1

Other considerationsOther considerations

• despite good druglikeness some compounds shoulddespite good druglikeness some compounds should be avoided as drug candidates:

If contain substructures with known reactive, toxic, mutagenicor teratogenic properties (RCOX, (RCO)2O, Michael acceptors,epoxides, ‐NO2, ‐NO, ‐N3, NH‐NH, N=N...)2 3

bad metabolic parameters, e.g. fast metabolism can quicklydestroy the pharmacological activity of the compound (metabolicdestroy the pharmacological activity of the compound (metabolichalf life, metabolic clearance should be determined)

Inhibit antimetabolites (CYP hERG P glycoprotein)Inhibit antimetabolites (CYP, hERG, P‐glycoprotein)

Case study (phy chem properties optimization)

LogP round 2.5 allows to penetrate compounds to CNS → side effects

(phy-chem properties optimization)

MeON

R

N NH

R

R: MeO- log P (2.59) FW: 255.27 (CNS side effects bright visions)

Cardiotonicum

MeSO- lop P (1.17) FW: 287.34 (Sulmazol)

2‐Aryl‐3H‐imidazo[4,5‐b]pyridine

pKa universal measure of acidity and also basicityand also basicity

Ionised form

pKa = ‐log {[H+].[B] / [HB+]} = pH ‐ log [B]/[HB+] = pH – log 1 = pH

pKa = pH if concentration of base and its protonated form is equal (pH at which the base is on 50 % ionized)

the higher pKa the stronger base or the weaker acid

b i l i

pKa = log {[H+] [B] / [HB+]} = pH log [B]/[HB+]In more acidic environment

at more basic solution

pKa = -log {[H+].[B] / [HB+]} = pH - log [B]/[HB+]-----------------------------------5.1 = 4.1 - log [B]/[HB+] [B] + [HB+] = 100%

two equiations wit two variables[B] + [HB+] = 100%-----------------------------------9% [B] and 91% [HB+]

Rational drug designRational drug design

frequently relies on computer modelling techniquesfrequently relies on computer modelling techniques (computer‐aided (assisted) drug design CADD)AIM:

to discover, enhance, or study biologically active molecules that will bind to a selected target and if so how strongly before a compound is synthesizedy

to estimate drug‐like properties and use them for elimination of undesirable structuresundesirable structures

it still takes several iterations of design, synthesis, and testing before an optimal molecule is discoveredoptimal molecule is discovered

Rational methods in DDRational methods in DD

• Structure‐based drug design SBDDg grequires 3D information about biomolecules (X‐ray crystallography orNMR spectroscopy, PDB database) http://www.rcsb.org/pdb/

• Ligand-based drug design LBDD

• Fragment-based drug design FBDD

Ligand Based Drug DesignLBDD (i di t DD)LBDD (indirect DD)

• relies on knowledge of known molecules that bind to thebiological target (known: structure and bioactivity IC50)

These molecules (ligands) may be used to derive a pharmacophoreThese molecules (ligands) may be used to derive a pharmacophoremodel which defines the minimum necessary structural characteristicsa molecule must possess in order to bind to the target.Virtual screening (based on pharmacophore models; high‐throughputdocking) including drug property filtering (Zinc 13 000 000 / Lipinski)

http://zinc.docking.org/

Alternatively, a quantitative structure‐activity relationship (QSAR) inwhich a correlation between calculated properties of molecules andtheir experimentally determined biological activity may be derived.These may be used to predict the activity of new analoguesThese may be used to predict the activity of new analogues.

Structure Based Drug DesignSBDD (di t DD)SBDD (direct DD)

• relies on knowledge of the 3D structure of the biological g gtarget obtained through X‐ray crystallography or NMR spectroscopy (http://www.rcsb.org/pdb/)

SBDD b di id d hl i t t t i• SBDD be divided roughly into two categories“finding” ligands for a given receptor (database searching). A large number of potential ligand molecules are screened to find those fitting 

(the binding pocket of the receptor. (this method is sometimes referred as ligand‐based drug design) It saves synthetic effort to obtain new active compounds. 

“b ld ” l d ( b d d d ) h l d“building” ligands (receptor‐based drug design). In this case, ligand molecules are built up within the constraints of the binding pocket by assembling small pieces (atoms, fragments) in a stepwise manner. The key advantage is that novel structures not contained in any databasekey advantage is that novel structures, not contained in any database, can be suggested. 

Virtual SBDD screening( finding ligands“)

500 t ti ll ti / 1 500 000 l i lib

(„finding ligands )

• 500 potentially actives / 1 500 000 mol. in library1 : 3000

SBDD „finding ligands“ methodSBDD „finding ligands method

• relies on 3D target structure with docked ligand (PDB complex)g g ( p )• active side identification

ligand and protein atoms need to be classified and their atomic properties

• hydrophobic atom: all carbons• hydrophobic atom: all carbons

• H‐bond donor: OH,NH

• H‐bond acceptor: O,N

• Polar atom: O,N,S,P,X,M,C‐HETATOM

The space inside the ligand binding region would beThe space inside the ligand binding region would be 

studied with virtual probe atoms of the four types above 

to determine what kind of chemical fragments can be put

i t th i di t i th li d bi di iinto their corresponding spots in the ligand binding region 

of the receptor. (latice, grids, intersections)

Fragment based drug discoveryFBDDFBDD

• Screening of small (MW < 300), low potency fragmentsg ( ), p y g(epitops, “seed templates”), which are subsequentlydeveloped into higher potency structures

we need a fragments database to choose fragments fromalthough the diversity of organic structures is infinite, thealthough the diversity of organic structures is infinite, thenumber of basic fragments is rather limitedseed is put into the binding pocket, and add otherfragments one by onefragments one by onenew molecules can be regarded as combinations of two ormore individual binding epitopes

FBDD: Ligand efficiency / Ro3

• Ligand Efficiency LE/ l ( )/LE = ‐ ΔG/HAC ≈ ‐ RTln(IC50)/HAC   

(HAC = Number of heavy atoms)

fragments typically exhibit higher ligand efficiency than higher MW HTS not ideal hits

I. D. Kuntz et al. Proc. Natl. Acad. Sci. USA 1999, 96, 9997.

Th “ l f th ” f i t f t d i• The “rule of three” for appropriate fragment design:

– MW < 300

– Number of H‐bond donors ≤ 3 (NH,OH)

– Number of H‐bond acceptors ≤ 3 (N,O)

– clogP ≤ 3

Case studies - PKIProtein kinases (tyrosine, serin-threonine and histidine

kinases) phosphorylate specific amino acids in protein) p p y p psubstrates. Growth factors trigger the start of signallingcascade that control transcription of specific genes inDNA leading cell growth and cell division In manyDNA leading cell growth and cell division. In manycancers excess of growth factor or PK receptor has beenobserved. Therefore PK inhibitors would be useful as

ti t All PK ATP thanticancer agents. All PK use ATP as thephosphorylation agent. ATP is bound quite loosely, thereare areas which remain unoccupied. There are alsopdifferences in AA within PKs in this binding region. Thereforeit is possible to design selective ATP competing inhibitors.

EGFR inhibitor gefinitib (IRRESA)(approved for refractory lung cancer AstraZeneca)

EGFR (ErbB, HER1) tyrosine kinase receptor: abnormal or over‐expressed in the breast, lung,brain, prostate, gastrointestinal tract, ovaries cancer. EGFR is a receptor for EGF proteins (1986

(approved for refractory lung cancer, AstraZeneca)

Nobel Prize). Upon activation by its growth factor, EGFR forms active homodimer possesingintracellular TK activity that initiate several signal transduction cascades leading to DNAsynthesis and cell proliferation. Gefitinib inhibits EGFR by binding to the ATP‐binding site. Thusreceptor and therefore alsomalignant cells are inhibitedreceptor and therefore alsomalignant cells are inhibited.

4‐anilinoquinazoline SAR optimizedLead I good in vitro activity in vivo

main metabolic products I, II both met. routes blockedLead I, good in vitro activity, in vivo

hampered by rapid metabolismcaused by cytochrome P450enzymes

Cl‐ similar in size and lipophilicity as Me‐ groupF‐ almost the same size as H‐ (no steric effect)

both groups are resistant to oxidation better in vivoboth groups are resistant to oxidation, better in vivo activity, pharmacokinetic properties improved by morpholino group, because of basic nitrogen that

enhanced water solubility 

Substrate bindingSubstrate binding -- Induced fit Induced fit (different conformers of the same protein)

• Binding of ligand alters the shape of the protein active sideto maximise intermolecular interactions. This will result 3Dchanges in protein binding site: induced fit

PhS Phe

SerO

H

I d d

SPhe

SerO

H

CO2Ser

Asp

CO2 Induced fit Asp

CO2

Intermolecular bonds not optimumlength for maximum bonding

Intermolecular bond lengths optimised(conformational changes in AA residues and in backbone observed in the protein)

Example:Example: Binding of pyruvic acid in Lactate Dehydrogenase LDH

O

H

OO

H3CC

COO

H3NOO

O

H

O

H3CC

CO

H3N

O

Prove of VEGFR2 mechanism –impact of induced fit

(different induced fit derived conformers of the same protein accommodate differently the same set of 16 compounds induced fit is a complication for CADD)the same set of 16 compounds, induced fit is a complication for CADD)

in this docking system, the best nMg y

inhibitors should rich the relative

level of interaction energy ca 50

kcal/mol. 3CJF is the one of the two

receptor conformers that almost

reached this level for the best of ourreached this level for the best of our

16 compounds. This allow us to select

the promising compound DMI‐76H

(both enantiomers ‐46.96 and ‐46.74)

that has the capability to inhibit

VEGFR‐2 signalling pathway. Next

values (44, 41, ... kcal/mol).

Thank you for your attention