Pharmacophore Model for PTP-1B Inhibitors

8/6/2019 Pharmacophore Model for PTP-1B Inhibitors

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Pharm acophore M ode l ing for Prote in Tyrosine Ph osp hatase 1B

Inhibitors

K a v i th a B h a r a t h a m t, N a g a k u m a r B h a r a t h a m t , a n d K e u n W o o L e e

D i v is i on o f A p p l i ed L i fe S c i ence , E nv i r onm en t a l B i o t echno l ogy N a t i ona l C o r e R esea r chNat i ona l Un i vers i t y , J i n ju 660-701 Korea

C en t e r , G yeongsang

(Received September 13, 2006)

A t h r e e d i m e n s i o n a l c h e m i c a l f e a t u r e b a s e d p h a r m a c o p h o r e m o d e l w a s d e v e l o p e d f o r t h einh ib i to rs o f p ro te in t y ros ine phospha tase 1B (PTP1B) us ing the CATALYST so f tware , wh ichwou ld p rov ide usefu l know ledge fo r pe r fo rm ing v i r tua l sc reen ing to i den t i fy new inh ib i to rs ta r -

ge ted toward t ype I I d iabe tes and obes i t y . A da tase t o f 27 i nh ib i to rs , w i th d i ve rse s t ruc tu ra lp roper ti es, and ac ti vi ti es rang ing f rom 0 .026 to 60 0 pM , was se lec ted as a t ra in ing se t . H yp o l ,the mos t re li able quan ti ta t ive fou r fea tu red p harm acop hore h ypo thes is , wa s ge nera ted f rom at ra i n in g s e t c o m p o s e d o f c o m p o u n d s w i t h t w o H - b o n d a c c e p t o r s , o n e h y d r o p h o b i c a r o m a t i cand one r ing arom at ic features. I t has a corre lat io n coeff ic ient, RM SD an d cost d i f ferenc e (nul lcos t- to ta l cos t ) o f 0 .946 , 0 .840 an d 65 .731 , respec t i ve ly . The bes t hy po the s is (H yp o l ) wa s va l -i da ted us ing fou r d i ff e ren t me thods . F i r st ly , a c ross va l i da t i on was per fo rme d by rando miz ingthe da ta us ing the Cat-Scramble t e c h n i q u e . T h e r e s u l t s c o n f i r m e d t h a t t h e p h a r m a c o p h o r emode ls genera ted from the tra in ing se t we re va l i d . Secondly, a tes t se t o f 281 mo lecu les w asscored , w i th a co r re la t ion o f 0 .882 ob ta ined be twee n the exper im en ta l and p red ic ted ac t i v i ti es .Hy po l pe r fo rmed we l l in co r rec t l y d i sc r im ina t i ng the ac t i ve and inac t i ve mo lecu les . Th i rd ly , t hemode l was inves ti gated by map p ing on two PTP 1B inh ib i to rs i den t i fi ed by d i f fe ren t pha rma ceu -t i c a l c o m p a n i e s . T h e H y p o l m o d e l c o r r e c t l y p r e d i c t e d t h e s e c o m p o u n d s a s b e i n g h i g h l yac ti ve . F ina ll y, dock ing s imu la t i ons were pe r fo rmed on few c om pou nds to su bs tan t i a te the ro leo f the ph armacoph ore fea tu res a t the b ind ing s i te o f the p ro te in by ana lyz ing the i r b ind ing con -

fo rmat ions . These mu l t ip le va l i da t i on appro ache s p rov ided con f idence in the u t i li t y o f t h i s pha r -macophore mode l as a 3D query fo r v i r tua l sc reen ing to re t r i eve new chemica l en t i t i esshowing potent ia l as potent PTP1B inh ib i tors .

K e y w o r d s : PTP1B Inh ib i to rs , P ro te in t y ros ine phospha tase 1B, Pharmacophore hypo thes is ,Mo lecu la r dock ing

I N T R O D U C T I O N

P h o s p h o r y l a t i o n a n d d e p h o s p h o r y l a t i o n o f p r o t e i n s a c t

a s a s w i t c h in g m e c h a n i s m t o s t i m u l a t e o r d is a b l e p r o te i n

a c t iv i ty . T h e r e f o r e , t h e b a l a n c e b e t w e e n p r o t e in ty r o s i n e

k i n a s e s ( P T K s ) a n d p r o t e i n ty r o s i n e p h o s p h a t a s e s ( P T P s )i s v e r y i m p o r t a n t . D e r e g u l a t i o n o f a s i n g l e e n z y m e c o u l d

l e a d t o v a r i o u s d i s e a s e s . O n e s u c h e x a m p l e i s d i a b e t e s

m e l li tu s , a c o m m o n d i s o r d e r i n h u m a n s , c a u s e d d u e to

t h e d e r e g u l a t i o n o f i n s u l i n s i g n a l i n g . P T P 1 B i s a n e g a t i v e

r e g u l a t o r o f t h e i n s u l i n s i g n a l i n g a n d t h u s , w o u l d b e a

s p e c i f i c t a r g e t f o r t r e a t i n g t y p e I I d i a b e t e s ( J o h n s o n et al . ,

tBoth authors hav e contributed equal ly to the w ork.Correspondence t o: K e u n W o o Lee , Div is ion of Appl ied L i fe Sc i -ence, Envi ronmenta l B iotechnology Nat ional Core Research Cen-ter, Gyeongsa ng Na tional Universi ty, Jinju 660-701 KoreaE-mail : [email protected]

2 0 0 2 ) . I t h a s a l s o b e e n p r o p o s e d a s a t a r g e t i n t h e

t r e a t m e n t o f o b e s i t y b e c a u s e i t r e g u l a t e s l e p t i n s i g n a l

t r a n s d u c t i o n ( Z a b o l o t n y et al . , 2 0 0 2 ) . P T P 1 B k n o c k o u t

a n d a n t i s e n s e s t u d i e s h a v e s h o w n l o w e r b l o o d g l u c o s e

l e v el s a n d i m p r o v e d i n s u li n re s p o n s i v e n e s s i n n o r m a l a n d

d i a b e t i c m i c e v i a e n h a n c e d i n s u l i n r e c e p t o r s i g n a l i n g i np e r i p h e r a l t i s s u e s ( E l c h e b l y et al . , 1 9 9 9 ; K l a m a n et al . ,

2 0 0 0 ; Z i n k e r et al . , 2 0 0 2 ) . T h u s , i n h i b it i n g t h e a c t i v it y o f

P T P 1 B c o u l d b e a p r o m i s i n g w a y t o tr e a t d i s e a s e s r e l a t e d

t o i t s a c t i v it y . I n h i b i t o r s o f P T P 1 B a s a t a r g e t fo r d i a b e t e s ,

s t a r t e d w i t h v a n a d i u m s a l t s , w i t h v a n a d a t e f o u n d t o b e a

p o t e n t, n o n s e l e c t i v e i n h i b it o r o f p h o s p h a t a s e s . B y t h e

m i d - 1 9 8 0 s , i t w a s u n d e r s t o o d t h a t b lo c k i n g o n e o r m o r e

p h o s p h a t a s e s c o u l d e n h a n c e t h e p h o s p h o r y l a t io n s t a te o f

t h e i n s u l i n re c e p t o r k i n a s e / s u b u n i t a n d / o r it s d o w n s t r e a m

s i g n a l i n g p a r t n e r s a n d r e s t o r e t h e i n s u l i n r e s i s t a n c e ,

w h i c h i s a c h a r a c t e r i s t i c o f t y p e I I d i a b e t e s ( H oo F { v a n

533



534 K. Bhara tham e t a l .

Huijsduijnen e t a l . , 2004). Since then, many drugs have

been synthes ized by var ious companies for target ing

PTP 1B, wh ich is very chal lenging due to the c losed form

of the cata ly t ic s i te o f PTPs conta in ing a h igh ly po lar

phospho tyrosine (pTyr) binding site. Presently, comp ounds

with var iou s activ it ies, drug properties and mechanisms of

action have been identif ied. I t is interesting to note that

most o f these compounds have d iverse modes of ac t ion,

ranging f rom the c lassical com pet i t ive type of inhibi tors to

noncompet i t ive binders or redox agents. Nevertheless, al l

comp ounds target the ac t ive s ite.

The quest for oral PTP1B inhibitors, with a satisfactory

balance between physicochemical propert ies and select ivity,

is st i l l in its early stages, but despite the recent progress,

compounds with opt imal oral act iv i ty remain to be dis-

covered . So far , there has been no repo rt on developing

pha rmac oph ore models using inhibi tors of PTP1B, which

is currently a powerful tool in identifying new leads. A

pharmacophore model represents the 3D arrangements

of the st ructural or chemical features of a drug (smal l

orga nic compou nds, pept ides, pept idomimetics, etc.) that

may be essent ial for interact ing with the protein for

opt imum binding. These pharmacophore models can be

used di f ferent ly in drug design program s ( i) as a 3D query

tool for virtual screening to identify potential n ew com pounds

from 3D d atab ase s of "drug-l ike" molecules th at have

patentable st ructures di f ferent f rom those that current ly

exist , and ( i i ) as a tool to predict the act iv i t ies of a set of

new compounds that remain to be synthes ized. A largenum ber of successful appl ications hav e c lear ly been

demonstrated in medic inal chemist ry (Bharatham e t a l . ,

2006a). Here, at tempts w ere m ade to: ( i ) select a t raining

set on a rat ional basis of the divers i t ies in st ructures and

activit ies, (i i) generate a pharmacoph ore hypothesis ba sed

on the t raining set , and ( i i i ) val idate the pharmacophore

model using four dist inct methods.

M E T H O D S

Biological data col lect ion

An in-house P TP IB inh ib itor database has been co l -lected a nd dev e loped f rom var ious journa ls us ing the

M D L I S I S sof tware (Shen, 2003). The database is com-

pr ised of 506 PTPIB inhibi tors, with both their st ructure

and biological act iv ity . Co mp oun ds w ere el iminated i f they

lacked exa ct act iv i ty values o r had com pletely di f ferent

assays . The 27 compounds (L i l jebr is e t a l . , 2002;

Hamaguch i e t a l . , 2000; Ahn e t a L , 2002 ; Chen e t a L ,

2002; Guer t in e t a L , 2003; Lau e t a L , 2004; Shres tha e t

a l . , 2004; B lack e t a l . , 2005; Wang e t a l . , 1998; Holmes e t

a l . , 2005; Wrobel e t a l . , 1 9 9 9 ; M a l a m a s e t a l . , 2000a;

M a l a m a s e t a L , 2000b; Lazo e t a l . , 2001 ; Hartshorn e t a l .,

200 5) we re rationally and intui t ively selected as a t raining

set, and represented structural dive rsity and covered the

entire act ivity range.

Train ing set select ion cr i ter iaThe most cr it ical asp ect in the generat ion of the phar-

macophore hypothesis using the C A T A L Y S T software is

select ion of the training set. Some basic strategies hav e

been elegantly laid out, with basic guidelines as follows.

( i) A m inimum of 16 diverse compounds should be

selected to avoid an y chance correlat ion. ( i i) Th e ac tivity

data should h ave a range o f 4-5 orders o f mag nitude. ( i i i)

The compounds should be selected to provide clear,

concise information to avoid redundancy or bias in terms

of bo th structural features and activity range. ( iv) The

most active compounds should be included so that they

provide information on the most crit ical features required

for a reliable/rational pharma cophore mo del. (v) Inclusion

of any compound know n to be inact ive du e to steric

hindrance must be avoided because the current features

within the C A T A L Y S T s o f t w a r e cannot handle such cases.

On the basis of the a bove cr iteria, 27 and 281 compounds

were selected for the training and test sets, respectively.

Pharmacophore hypothes is generat ionPharmacophore hypotheses generat ion was achieved

using the H y p o G e n module of C A T A L Y S T 4 . 1 0 sof tware

and the t raining set of 27 compounds. Molecular f lex ibi l ity

wa s taken into account by considering each compound as

a collect ion of conformers representing a dif ferent area ofconformational space accessible to the molecule within a

given energy range. The "b est quality searching procedure"

was adopted to select representative conformers within a

20 kcal/mol range abo ve the computed global minimum

energy. Training se t compounds, as show n in F ig. 1, we re

imported into C A T A L Y S T and conformat ion models

generated for all molecules (both training and test sets),

with 250 maximum number of conformat ions. C A T A L Y S T

selects conformers using the Poling algorithm, which

penal izes an y ne wly generated conformer i f i t is too c lose

to any previously found conformer. This method ensures

maximum covera ge of the conformat ion space. Dur ing theinitial phase o f the h ypo thes is generation exercise, it wa s

observed tha t features, l ike H-bond acceptors (HBA),

hydrophobic aromat ic (HY-AR) and r ing aromat ic (RA),

could effect ively m ap all crit ical chem ical/structural features

of all the training set molecules. Therefore, ten pharma-

cophore hyp othese s we re generated f rom the t raining set ,

using a default uncertainty value of 3. The minimum and

maximum feature coun ts we re 0 and 5, respect ively.

Qual ity o f pharmacophore hypothes is asse ssm entThe quality of the generated pharmacophore hypotheses

was eva luated by cons ider ing the cos t func t ions ( re-



Pharmacophore M odeling or PTP1B Inhibitors 535

H

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O O ~ N S rc , o N O o .

r-N--~N 1 9O0 % 0 ~ H O ~ " Hu . O - , ~ F F 0 ~ , - 6

F ~ -H 2 0~ 6FF._}__ ?O.H H O

z 2 : 1 3 . . _ ~ "2 1 N ,0 ~ S

H'o~P"oF ~ 0 Ho o

Br O/--~O'H H N'H N~ H ' H ~ N o ~ O H

H. , -"~~.~-'L. I~H

9 N/,

FF F

24 F Op.O-H ~ ~ 0 -

1 5 I I r ~ ) 2 5 H.O. o . . ~ - ~ ; ~O~o

O.HO H i _ ~ \FO-H

1 6 N 2 6 O H' L ' " ~ N../

S " ~'~ N 'N . ~ 2 7

17 O H H,O ..~.~_.j O.....-~.~ O..~'-...~

Fig. 1. The molecular structures of the 27 training set compounds, take n from the literature

p resen ted in b i ts un i t ) ca lcu la ted us ing the CATALYST/HypoGenmo d u le d u r i n g h y p o th e s i s g e n e r a t io n . A m e a n -

in g fu l p h a r m a c o p h o r e h y p o th e s i s m ig h t b e g e n e r a te d

w h e n th e d i f f e r e n c e b e tw e e n th e n u l l ( c o s t o f a c o mp le x

hypo thes is ) and the f i xed cos t ( cos t o f a s imp le hypo thes is )

va lues w as la rge , i .e . 60 -70 b i ts . The to ta l cos t ( cos t o f the

g e n e r a te d h y p o th e s i s ) s h o u ld b e c l o s e to t h e f i x e d c o s t ,

a n d t h e c o n f i g u r a t i o n c o s t s h o u ld b e l e s s t h a n 1 7 , a s t h e

l a tt e r d e s c r i b e s t h e c o mp le x i t y o f t h e h y p o th e s e s s p a c e t o

b e e x p lo r e d . H y p o l s a t i s f i e d a l l t h e a b o v e c r i t e r i a a n d

th u s , w a s c h o s e n f o r t h e v a l i d a t i o n .

V a l i d a t i o n o f b e s t p h a r m a c o p h o r e m o d e l ( H y p o l )Va l idat ion was per formed u s ing the fo l lowing three



536 K. Bhara tham et al.

d is t inc t me thods : i ) C a t - S c r a m b l e p r o g r a m ( D u e t al. ,

2 0 0 5 ) a v a i l a b l e i n C A T A L Y S T , a va l ida t ion p rocedu re

b a s e d o n t h e F i s c h e r ' s r a n d o m i z a t i o n t e s t , w h i c h c h e c k s

w h e t h e r a s t r o n g c o r r e l a t i o n e x i s t s b e t w e e n t h e c h e m i c a l

s t ruc tu re s and the b io log ica l ac t i v i t y . Th is i s ca r r ied ou t by

r a n d o m i z i n g t h e a c t i v i t y d a ta a s s o c i a t e d w i t h t h e t r a in i n g

s e t c o m p o u n d s . T h e s e r a n d o m i z e d t r a i n in g s e t s w e r e

u s e d t o g e n e r a te p h a r m a c o p h o r e h y p o t h e s e s , e m p l o yi n g

t h e s a m e f e a t u r e s a n d p a r a m e t e r s a s u s e d i n t h e

d e v e l o p m e n t o f t h e o r ig i n a l p h a r m a c o p h o r e h y p o t h e s i s . If

t h e r a n d o m i z e d d a t a s e t r e s u l t s i n t h e g e n e r a t i o n o f a

p h a r m a c o p h o r e m o d e l w i t h s i m i l a r o r b e t t e r c o s t v a l u e s ,

r o o t m e a n s q u a r e d e v i a t i o n ( R M S D ) , a n d c o r r e l a t i o n

c o e f f i c ie n t ( r ) o f t h e o r i g in a l h y p o t h e s i s , t h e n i t w o u l d h a v e

b e e n g e n e r a t e d b y c h a n c e . I n t h i s v a l id a t i o n t e s t, t h e 9 5 %

c o n f i d e n c e l e v el w a s s e l e c t e d a n d t h u s , 1 9 s p r e a d s h e e t s

w e r e g e n e r a t e d , i i) a te s t s e t o f 2 8 1 c o m p o u n d s h a v i n g

e x p e r im e n t a l P T P I B i n h ib i to r y a c t iv i t ie s w e r e u s e d t o

q u a n t i f y t h e v a l id i ty , a n d i ii ) c a n d i d a t e m o l e c u l e s w e r e

f i n a ll y m a p p e d o n t o t h e m o d e l a n d t h e i r a c t i v i ti e s pr e -

d i c t e d .

Molecular dockingT h e b i n d i n g o r ie n t a t i o n s o f v a r i o u s c o m p o u n d s w e r e

a n a l y z e d u s i n g G O L D m o l e c u l a r d o c k i n g a n d c o m p a r e d

w i t h t h e p h a r m a c o p h o r e m a p p i n g r e s u l t s a s a fi n a l v a l i d a -

t i o n m e t h o d . T h e G O L D 3 . 0 . 1 p r o g r a m ( G e n e t i c O p t i m i s a -

t i o n f o r L i g a n d D o c k i n g ) , f r o m C a m b r i d g e C r y s t a l l o g r a p h i c

D a t a C e n t e r , U K , ( J o n e set a l . ,

1 9 9 7 ) , u s e s a g e n e t i ca l g o r i t h m f o r d o c k i n g f l e x i b l e l i g a n d s i n t o p r o t e i n b i n d i n g

s i t e s ( B h a r a t h a m , e t aL , 2 0 0 6 b ) . A t r a i n i n g s e t c o m p o u n d ,

t e s t s e t a n d c a n d i d a t e m o l e c u l e w e r e d o c k e d i n t o t h e

P T P 1 B a c t i v e s i t e ( P D B I D : 1 Q 6 P ) . A r a d iu s o f 7 . 0 A

a r o u n d t h e c r y s t a l l i g a n d w a s c o n s i d e r e d a s t h e a c t i v e

s i t e . T h e w a t e r o f c r y s t a l l i z a t i o n p r e s e n t w i t h i n t h e a c t i v e

s i te reg ion was a lso cons ide red in the dock ing s imu la t ion .

T h e R M S D , a n n e a l i n g p a r a m e t e r o f v a n d e r W a a l ' s ( v d w )

inte rac t ion and hyd rogen bond in te rac t ion we re cons ide red

w i th in 1 .5A , 4 .0A and 2 .5A , respec t i ve ly .

R E S U LT S A N D D I S C U S S I O N

P h a r m a c o p h o r e h y p o t h e s i s g e n e r a t io n w a s a c h i e v e d

us ing the t ra in ing se t . Compounds 14 (py r im ido - t r iaz ine -

p ipe r id ine ) and 16 (py r idaz ine ) o f the t ra in ing se t we re

p o t e n t . c a n d i d a t e m o l e c u l e s , d i s c o v e r e d b y R o c h e a n d

B iov i t rum, respec t i ve ly . They we re inc luded in the t ra in ing

s e t b e c a u s e t h e i r a c t i v i t i e s w e r e a v a i l a b l e , w h i c h w o u l d

he lp in gene ra t ing a reaso nab le pha rm acop ho re mode l .

T e n p h a r m a c o p h o r e h y p o t h e s e s w e r e g e n e r a t e d , a m o n g

w h i c h t h e b e s t m o d e l w a s s e l e c t e d . A l l t e n h y p o t h e s e s

had the same fou r chemica l fea tu res . The re fo re , se lec t ion

o f t h e i d ea l p h a r m a c o p h o r e h y p o t h e s i s w a s c h a r a c t e r iz e d

us ing the h igh cos t d i f fe rence (nu l l - f i xed ) , l ow e r ro r cos t ,

l o w R M S D a n d b e s t c o r re l a t io n c o e f f ic i e n t. H y p o l i s

c o n s i d e r e d t h e b e s t a s i t is c h a r a c t e r iz e d b y t h e h i g h e s t

c o s t d i f f e r e n c e ( 7 2 . 0 2 6 ) , l o w e s t R M S D v a l u e ( 0 . 8 4 6 ) a n d

a lso had the bes t co r re la t ion coe f f i c ien t (0 .946 ) , wh ich

ind ica tes a t rue co r re la t ion and good p red ic t i ve capab i l i t y .

T h e t o t a l c o s t v a l u e o f e a c h h y p o t h e s i s w a s c l o s e t o t h e

f i x e d c o s t v a l u e, w h i c h i s e x p e c t e d f o r a g o o d h y p o t h e s i s .

T h e c o n f ig u r a t io n c o s t v a l u e o f t h e h y p o t h e s i s w a s a l s o

w i th in the a l lowed range , i .e . 17 . The nu ll cos t , f i xed cos t

a n d t h e c o n f i g u r a t i o n c o s t v a l u e s f o r t h e 1 0 b e s t r a n k i n g

hypo theses were 182.256, 106.9 7 and 15.028, respect ive ly .

The cos t va lues , co r re la t ion coe f f i c ien ts ( r ) fo r the t ra in ing

s e t , R M S D v a l u e s a n d f e a t u r e s o f a l l t e n p h a r m a c o p h o r e

models are l is ted in Tab le I .

H y p o l c o m p r i s e d o f t w o H - b o n d a c c e p t o r s ( H B A ) , o n e

h y d r o p h o b i c a r o m a t i c ( H Y - A R ) a n d o n e r i n g a r o m a t i c

Table I. Information of the c os t values m easured in b its RM SD, correlation coefficient values and features for top-ten hypotheses

Co st difference Correlation value orHypo-thesis Total cos t RMSD r Features

(null-total cos t) 281 te st set compounds

1 116.525 65.731 0.840 0.946 HBA,HBA,HY-AR,RA 0.882

2 117.323 64.933 0.874 0 . 9 4 1 HBA,HBA,HY-AR,A 0.862

3 121.179 61.077 1.025 0.919 HBA,HBA,HY-AR,RA 0.829

4 121.247 61.009 1.028 0 . 9 1 8 HBA,HBA,HY-AR,A 0.838

5 121.251 61.005 1.021 0.919 HBA,HBA,HY-AR,RA 0.798

6 121.376 60.880 1.024 0 . 9 1 9 HBA,HBA,HY-AR,A 0.870

7 122.020 60.236 1.054 0 . 9 1 4 HBA,HBA,HY-AR,A 0.807

8 122.964 59.292 1.087 0.908 HBA,HBA,HY-AR,RA 0.834

9 123.025 59.231 1.083 0 . 9 0 9 HBA,HBA,HY-AR,A 0.743

10 123.195 59.061 1.094 0.907 HBA,HBA,HY-AR,RA 0.835

"Null c ost of top-ten score hypotheses s 182.256 bits Fixed cost is 106.97 bits. Configuration cos t is 15.028 bits. Abbreviation used for features:

HB A, hydrogen-bond acceptor; HY -AR, hydrophobic aromatic; RA, ring aromatic.



Pharmacophore Modeling for PTP IB Inhibitors 537

Fig. 2. The best ranked pharrnacophorehypothesis Hypol). The distances between he chemical features of the 3D pharmacophore hypothesis,where orange represents he ring aromatic (RA), green he H-bondacceptor HBA) and light blue the hydrophobicaromatic (HY-AR) eature.

(RA) features (Fib. 2). The two best active training set

compounds that were mapped on to the pharmacophore

model, Hypol, are shown in Fig. 4a and 4b, respectively.

Compoun d 2 wa s a reversible, competitive and catalytic

site-binding PTP1B inhibitor, where the phenyldifluoro-

methylphosphonate group targets the primary binding site

and forms a hydrogen bond with Arg221 (Lau et aL, 2004,

Giovanna Scapin et aL, 2003). Analogously, our pharma-

cophore model mapped the phosphonate hydroxyls of

compound 2 as two HBA features, which interact with

catalytic site residues. The docking results for compound

2 also revealed that it interacts with Arg221 and Gly220

Fig. 3. Correlation graph between the experimental and Hypol

predicted activities

via hydrogen bonding (Fig. 6a). The hydrophobic phenyl

(mapped as RA feature) and indole groups (mapped as

HY-AR feature) interact with the Tyr46 and Arg47 side

chains, respectively, wh ich are the se cond ary binding sites,

which have also been extensively studied. Compound 3

belongs to a class of highly hydrophobic, more promiscu ous

PTP1B inhibitors, with a benzothiophene biphenyl oxo-

acetic acid group. The carboxylic acid portion of the ligancL

does not interact directly with Arg221, but participates in

hydrogen bonds with two water molecules bddging the

ligand with Arg221 (Malamas et al., 2000b). The two HB A

features of our pharmacophore model were ma pped onto

the carboxyl group, which indirectly interacts with catalytic

site residues.

A ph arrnacopho re model capable of predicting an active

or inactive compo und wou ld red uce the time of the drug

discovery process. Therefore, all compounds in both the

training and test sets were classif ied into three groups;

high ly active (+++, 1(35o 1 ~M), m odera tely active (++, 1

t~M < IC~o < 10 ~M) and inactive c om pou nds (+, 10 I~M).

The experimental and Hypol predicted activit ies for the

27 training set compounds are shown in Table I1. Out of

the 27 compounds, only two moderately active (++)

compounds were predicted as being inactive (+), while all

the remaining compounds were predicted to the same

magnitude. The error value was calculated as the ratio

betw een the predicted and experimental activities. A

positive e rror value indicates that the predicted ICso is

higher than that obtained experimentally, while a neg ative

error value indicates that the p redicted ICso is lower than

that obtained experimentally. An error value of less than

ten represents a difference no greater than one order

between the predicted and experimental activities. Amo ng

the training set compounds, very few had an error value >

3. Hence, the pharmacophore model was selected for



538 K. Bharatham et al.

Fig. 4. Mapping of the top scored Hypo l on the highly active raining set compounds 2 (a) and 3 (b), the test set compounds 188 (c) and t362 (d),

and the candidate molecules cl (e) and c2 (f). In the pharmacophore hypothesis; orange represents the ring aromatic (RA), green the H-bondacceptor (HBA) and light b lue the hydrophobic aromatic (HY-AR) eature.

validation using various methods.

The validation of Hypol was performed using four distinct

methods. First, a validation procedure was performed

using the Cat-Scramble technique, which is based on the

principle of ran domizing the activity data of the training set

compounds, and generates pharmacophore hypotheses

using the same features and parameters as used in the

deve lopme nt of the original pharma cophore hypothesis.

Nineteen random spreadsheets (or 19 HypoGen runs)were generated for the 95% confidence level. The data of

cross validation clearly indicated that al l values generated

after randomization produced hypotheses with no pre-

dictive value near or similar to that obtained for Hypol, as

shown in Table III. Out of the 19 runs, only two had a

correlation close to 0.7, but the RMSD was high and the

total cost was close to the null cost, which is not desirable

for a good hypothesis. This cross validation provided

strong confidence on the initial pharmacophore model,

Hypo l .

The val idi ty of any pharmacophore model needs to be

ascertained by its application to the test set to find if the

model correctly predicts the activity of the mo lecules in

the test set molecules and m ost importantly, w het he r it

correctly identifies active and in active molecules. Therefo re,

in the second method, 281 molecules with experimental

PTP1B inhibitory activit ies were imported, and conformers

generated in a similar ma nner to that of the training set. A

regression analysis was performed on the 281 test set

compounds, with the best hypothesis (Hypol) generated

from the original training set. The graph drawn betweenexperimental an d predicted activit ies generated for the

test set compounds using Hypol is shown in Fig. 3. A

correlation of 0.882 was observed between the experi-

mental and predicted activ ity values, signifying a good

correlation. None o f the test set comp oun ds had an error

value greater than 10, implying their activit ies were predi-

cted within the same magnitude.

Two of the highly active test set compounds were

mapped onto Hy po l (Fig. 4c and 4d). The molecular

structures of the two test set compounds were shown in

Fig. 5a and 5b. The predicted activit ies of t188 and t362

were 0.48 pM (experimental IC50 = 1.01 pM), and 0.15 pM



Pharma cophore Mod el ing for PTP1B Inh ib i tors 539

Table I I . E xperimental and predicted biological da ta m easured asIC5o (pM) ba sed on p harma copho re mod el Hypol for training setmolecules

Experimental Pre. Fitness Activity Pre . ActivityComp. Act iv ity pM ) Act iv i t y Erro r scoreb Scalec Sca le

1 0.026 0.038 1.5 6.93 +++ +++

2 0.038 0.085 2.2 6.58 +++ +++

3 0.052 0.012 -4.2 7.41 +++ +++

4 0.061 0.24 3.9 6.13 +++ +++

5 0.098 0.079 -1.2 6.61 +++ +++

6 0.16 0.29 1.8 6.05 +++ +++

7 0.24 0.16 -1.5 6.31 +++ +++

8 0.39 0.55 1.4 5.76 +++ +++

9 0.65 0.76 1.2 5.63 +++ +++

10 0.85 0.59 -1.4 5.74 +++ +++

11 1.3 1.1 -1.2 5.46 ++ ++12 1.9 1.6 -1.2 5.29 ++ ++

13 2.1 1 -2 .1 5.51 ++ ++

14 2.9 2.3 -1.2 5.14 ++ ++

15 4.3 8.9 2.1 4.56 ++ ++

16 5.6 82 15 3.60 ++ +

17 6 5.2 -1.2 4.8 ++ ++

18 8 38 4.8 3.92 ++ +

19 2 6 47 1.8 3.84 + +

20 42 40 -1 3.9 + +

21 55 38 -1.5 3.93 + +

22 73 60 -1.2 3.73 + +23 86 58 -1.5 3.75 + +

24 95 58 -1.6 3.74 + +

25 120 39 -3 3.92 + +

26 140 63 -2.2 3.71 + +

27 600 83 -7.2 3.59 + +

a+ indicates tha t the predicted ICs0 is h igher than the experimental

IC50; - indicates tha t the predicted ICs0 s low er than the experimental

IC50b Fitness score indicates how we ll the features in the pharmacophore

overlap the chem ical features n the m olecule.

c PTP1B activity sca le: +++ , ICs0 1 p M (high active); ++, 1 p M < IC~0 <

10 pM (mod erate active ); +, IC~0 10 pM (inactive)

( e x p e r i m e n t a l IC 5 o = 0 . 1 4 5 p M ) , r e s p e c t i v e ly . A l t h o u g h n o

s p e c i f i c b i n d i n g m e c h a n i s m h a s b e e n d e s c r i b e d f o r 1, 2 -

n a p h t h o q u i n o n e d e r i v a t iv e s , it w a s a s s u m e d t h a t t h e a c id

g r o u p o f t 1 8 8 f o r m s H - b o n d i n g w i t h A r g 2 2 1 ( A h n e t a l . ,

2 0 0 2 ). A c c o r d i n g ly , t h e t w o H B A f e a t u re s o f o u r p h a r m a -

c o p h o r e m o d e l w e r e m a p p e d p e r fe c t ly o n t o t h e a c i d

g r o u p o f t 1 8 8 . T h e d o c k i n g r e s u l t s a l s o r e v e a l e d t h a t t h e

c a r b o x y l i c g r o u p f o r m e d h y d r o g e n b o n d s w i t h th e g u a n i d o

g r o u p o f A r g 2 2 1 . T h e R A f e a t u re , w h e n m a p p e d o n t o 1 ,

2 - n a p h t h o q u i n o n e , f o r m s h y d r o p h o b i c i n t e r a c ti o n s w i t h

Table I I I. R esults fr om cross-validat ion usin g C A T S C R A M B L E

method in CATALYST a

CorrelationTrial no. Total c o s t Fi xe d ost RMSD

coefficient (r)

Results for unscrambled116.525 106.97 0.840

Results ~rsc ~m bled

0.946

1 169 .94 3 100 .237 2.260 0.496

2 171 .29 3 101 .267 2.269 0.490

3 182.256 90.817 2.600 *

4 166 .22 7 104 .404 2.133 0.573

5 164 .79 8 101 .142 2.171 0.551

6 179.061 98.481 2.411 0.380

7 172 .68 5 103 .646 2.258 0.497

8 178.817 96.942 2.445 0.345

9 16 5.5 70 103 .446 2.145 0.56610 182.256 90.813 2.602 *

11 17 5.4 74 101.531 2.329 0.447

12 16 4.3 58 106 .077 2.076 0.602

13 177 .81 7 103 .612 2.325 0.451

14 182.256 90.817 2.602 *

15 16 5.0 38 101.921 2.162 0.556

16 182.256 90.817 2.602 *

17 14 9.6 42 107.991 1.756 0.737

18 178.492 99.557 2.412 0.376

19 14 7.2 43 10 3.4 32 1.801 0.721

aNull cos t is 182.256*Indicates tha t correlation coefficient cou ld not be obtained.

a ) o o b )

I S B r 0r / ._ _ p / ~ _ _ O H

. o

H

,dr o o

Fig. 5. The molecular structures of test set compounds t188 (a) and

t362 (b) and the candidate molecules cl (c) and c2 (d)

t h e s id e c h a i n o f A r g 4 7 , w h i l e t h e H Y - A R f e a t u r e w h e n

m a p p e d o n t o t h e p h e n y l r i n g o f t h e i n d o le g r o u p f o r m s

h y d r o p h o b i c i n t e r a c t io n s w i t h M e t 2 5 8 . T h e b i n d i n g o r i e n -

t a t i o n o f t 1 8 8 a t t h e a c t i v e s i t e i s s h o w n i n F i g . 6 b . I n



540 K. Bharatham et al.

Fig. 6. The molecular docking results. Docked compound 2 of the training set (a), the test set compounds 188 (b) and t362 (c), and the candidatemolecule c l (d) with he catalytic residues are represented as sticks, with water as a sphere n the PTP1B protein active site.

compound t362, the phosphonate group was ear l ier

hypothesized to bind to the side chain of the active site

Arg221 vi a a charge-charge interaction (Wrobel et al.,

1999). The docking results also confirm the hydroxyl

groups of phosphonate form hydrogen bonds with Arg221

(guanido group) and Gly220 (main chain). The HY-AR

feature (mapped on corner phenyl of fused ring) formed

hydrophobic interactions with the Arg47 side chain, while

the R A feature mapped onto the five membered ring

formed hydrophobic interactions with Tyr46 and Lys120

(Fig. 6c). As the pharmacophore model represented the

crucial features required fo r binding, i t was a ble to

appropriately predict their activit ies.

As a third trial, another validation process was performed

to find the usefulness of the selected pharmacophore

model in evaluating two diverse potent PTPIB inhibitors

(Fig. 5c and 5d), which have either been cl inical ly intro-

duced or are in the developmental stages. The rationale

of this approach was if the pharma copho re model maps

onto those inhibitors and predicts their activity well, the

pharmac ophore model is then exp ected to be useful as a

search tool for identifying new PTP1B inhibitors. No

attempts were made to directly compare the predicted

and experimental activit ies of these compounds, as no

detailed a ctivity data have previou sly been reported. Merck

Frosst has described a charged compound, monodifluoro-

phosphonate derivative (cl), but no biological data was

disclosed. H ypo l predicted the activ ity (IC50 for binding to

PTP1 B) to be 0.0061 pM, an d also correctly classified the

molecule as being highly active. The two HBAs map the

oxygen atoms of the ph ospho nate involved in the catalytic

activity. The RA and H Y-AR features map the phenyl r ingsthat contribute to the hydrophobic interactions. Similarly,

the docking results also showed the two hydroxyl groups

of phosphonate formed hydrogen bonds with Arg221 and

Gly220, while the benzoyl and phenyl groups formed

hydrophobic interactions with the Arg47 side chain and

Met258, respectively (Fig. 6d).

To avoid multiple negative charges, while still showing

potency, several inhibitors, such as ertiprotafib (c2), showed

modest selectivity profiles, have been tested in clinical

tr ials and have reached phase II development. The

inhibition of PTP1B by this compound was presumed to

involve the oxidation of the active site cysteine of PTP1B



Pharmacophore Model ing fo r PTP1B Inh ib i to rs 541

t o th e c o r r e s p o n d i n g s u l f e n i c a c i d . T h e H y p o l p r e d ic t e d

a c t i v i ty w a s 0 . 0 7 2 I ~ M , a n d t h e m o l e c u le w a s c o r r e c tl y

c l a s s i f i e d a s b e i n g h i g h l y a c t i v e . T h e t w o H B A s m a p t h e

o x y g e n a t o m s o f t h e c a r b o x y l a t e i n v o l v e d i n t h e c a t a l y t i c

a c t iv i ty . T h e R A a n d H Y - A R f e a t u r e s m a p t h e f u s e d

t h i o p h e n e a n d p h e n y l r i n g s o f 1 1 - A r y l b e n z o [ b ] n a p h t h o

[2 ,3 -dJth iophenes , respec t i ve ly , wh ich con t r ibu te to the

h y d r o p h o b i c i n t e ra c t i o n s . T h e m a p p i n g o f t h e c a n d i d a te

mo lecules, c l and c2 , us ing H yp o l a re show n in F ig. 4e

and 4 f . As a fou r th va l ida t ion me thod , dock ing s tud ies

w e r e p e r f o r m e d , a n d t h e r e s u l t s w e r e s i m u l t a n e o u s l y

d e s c r i b e d f o r b e t t e r c o m p a r i s o n w i t h t h e p h a r m a c o p h o r e

m o d e l m a p p i n g . T h u s , H y p o l w a s v a l i d a te d u s i n g f o u r

me thod s , a ll o f wh ich g ave re l iab le resu lts . The refo re , the

p h a r m a c o p h o r e m o d e l i s e x p e c t e d t o h e lp i n t h e i d e n ti -

f ic a t i on o f n e w c l a s s e s o f P T P I B i n h ib i to r s f r om v i rt u a l

s c r e e n i n g .

CONCLUS I ONS

O n e o f t h e m a j o r g o a l s o f t h i s s t u d y w a s t o g e n e r a te a

p red ic t i ve pha rmacopho re mode l tha t cou ld be u t i l i zed as

a q u e r y t o o l t o s e a r c h 3 D d a t a b a s e s o f d i v e r s e d r u g - l i k e

c o m p o u n d s f o r t h e i d e n t i f i c a t i o n o f n e w m o l e c u l e s t h a t

possess po ten t PTP1 B inh ib i to ry ac t i v i t i es . The bes t pha r -

m a c o p h o r e h y p o t h e s i s , H y p o l , a s c h ar a c t e ri z e d b y t h e

h igh co r re la t ion coe f f i c ien t o f 0 .946 , was gene ra ted fo r

P T P I B i n h i b i t o r s u s i n g a t r a i n i n g s e t o f 2 7 c o m p o u n d s ,

and va l ida ted us ing fou r d is t inc t me thods . In add i t i on , th i s

s t u d y c l e a r l y i n d i c a t e s t h a t t h e s e l e c t e d p h a r m a c o p h o r e

m o d e l c a n b e u s e d t o f i n d n e w c h e m i c a l e n t i ti e s w i t h

p o t e n t a c t i v i t i e s a g a i n s t a t a r g e t d i s e a s e , w h i c h i s o f

u tmos t impo r tance to the pha rmaceu t i ca l i ndus t ry . Ou r

p h a r m a c o p h o r e m o d e l s u c c e s s f u l l y p r e d i c te d th e b io -

log ica l ac t i v i t i es o f the compounds in the tes t se t , as we l l

a s a c c u r a t e l y c l a s s i fi e d t w o e x i s t i n g P T P 1 B i n h ib i to r s f r o m

t w o d i f f e r e n t p h a r m a c e u t i c a l c o m p a n i e s . T h e b i n d i n g

o r i e n t a t i o n s o f t h e c o m p o u n d s a l s o s u b s t a n t i a t e d t h e

f e a t u r e s m a p p e d b y th e p h a r m a c o p h o r e m o d e l. I t h a s

b e e n c o n f i r m e d t h a t c o r r e c t m a p p i n g t o f o u r f e a t u r e s i s

su f f i c ien t to suc ces s fu l l y iden t i f y spe c i f i c PTP1 B inh ib i to rs .

T h e s e l e c t e d p h a r m a c o p h o r e m o d e l i s e x p e c t e d t o h e l p

iden t i f y new c lasses o f PTP1B inh ib i to r .

A C K N OW L E D G E M E N T S

N a g a k u m a r B h a r a th a m a n d K a v i th a B h a ra t h am w e r e

r e c i p i e n t s o f f e l l o w s h i p s f r o m t h e B K 2 1 P r o g r a m . T h i s

w o r k w a s s u p p o r te d b y g r a n ts f ro m t h e M O S T / K O S E F f o r

t h e E n v i r o n m e n t a l B i o t e c h n o l o g y N a t i o n a l C o r e R e s e a r c h

C e n t e r ( g r a n t # : R 1 5 - 2 0 0 3 - 0 1 2 - 0 2 0 0 1 - 0 ) a n d fo r t h e B a s i c

R e s e a r c h P r o g r a m ( g r a n t # : R 0 1 - 2 0 0 5 - 0 0 0 - 1 0 3 7 3 - 0 ).

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Pharmacophore Model for PTP-1B Inhibitors

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