カルボキシルエステラーゼ阻害剤のインシリコデザ …知re-activity relationship...
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カルボキシルエステラーゼ阻害剤のインシリコデザインと評価
誌名誌名 Journal of pesticide science
ISSNISSN 1348589X
巻/号巻/号 353
掲載ページ掲載ページ p. 240-249
発行年月発行年月 2010年8月
農林水産省 農林水産技術会議事務局筑波産学連携支援センターTsukuba Business-Academia Cooperation Support Center, Agriculture, Forestry and Fisheries Research CouncilSecretariat
11 [1111 [1111[111111 111111 1111
Review 11111111111111111111111111111
(Special Topic)
J. Pestic. Sci., 35(3), 240-249 (2010) DOI: 10.l584/jpestics.R10-06
In silico design and evaluation of carboxylesterase inhibitors
Shana V. STODDARD,t Xiaozhen Yu,t Philip M. POTTERtt and Randy M. WADKINS汁
t Department of Chemistry and Biochemistry, University of Mississippi, University, MS 3867スUSA
tt Department of Chemical Biology and Therapeutics, St.んdeChildren s Research Hospital, Memphis,刀V38105, USA
(Received April 13,2010; Accepted June 1,2010)
Carboxylesterases (CEs) are important enzymes that catalyze biological detoxification, hydrolysis of certain pes-
ticides, and metabolism of many esterified drugs. The development of inhibitors for CE has many potential uses, including increasing drug lifetime and altering biodistrubution; reducing or abrogating toxicity of metabolized
drugs; and reducing pest resistance to insecticides. In this review, we discuss the major classes of known mam-malian CE inhibitors and describe our computational efforts to design new scaffolds for development of novel, selective inhibitors. We discuss several s仕ategiesfor in silico inhibitor development, including s仕ucturedocking, database searching, multidimensional quantitative s仕ucture-activityanalysis (QSAR), and a newly-used ap-
proach that uses QSAR combined with de novo drug design. WhiIe our research is focused on design of specific
inhibitors for human intestinal carboxylesterase (hiCE), the methods described are generaIIy applicable to in-
hibitors of other enzymes, including CE from other tissues and organisms. l1:J Pesticide Science Society of
Japan
Keywords: irinotecan; CPT-ll; molecular dynamics; QSAR; drug design; modeling.
Introduction
Carboxylesterases (CEs) are enzymes that convert esters into
the corresponding a1cohol and carboxylic acid.
Carboxylesterases are members of the larger α/ s-hydrolase
fold farnily that includes a wide variety of enzymes such as li-
pases, cholinesterases, haloalkane dehydrogenases, and epox-
ide hydrolases.I-3) The catalytic machinery of the CE is an
amino acid仕iadconsisting of the residues serine, histidine, and glutamate that sit in a nucleophilic elbow, making these enzymes members of the even larger family of serine hydro-
lases.
Carboxylesterases are ubiquitous in nature. In mammals, they are expressed in numerous tissuesρ) The hydrolytic ac-
tivity will vary based on tissue type, with the liver isozyme being one of the most active of all isozymes studied. The hy-
drolytic activity of these enzymes are important in合唱 me-
tabolism, protection against xenobiotics, and detoxiぢingpes-
ticides such as pyrethoids.6) CE's are also responsible for hy-
drolyzing c1inically useful批ugsuch as capecitabine and
* To whom corr巴spondenceshould be addressed. E-maiI: rwadkins@olemiss.edu Published onIine July 15,2010 。PesticideScience Society of Japan
irinotecanク)as well as illicit drugs such as heroin.9)
Carboxylesterases have potential as therapy for pesticide
overexposure. Organophosphate (OP) and carbamate (CB) in-
secticides have the potential to poison humans by acting on
aceザ1cholinesterase (AChE). Carboxylesterases can bind
organophosphate and carbamate insecticides and reduce toxi-
city by two pathways: metabolism of the insecticide by CEs
and irreversible binding by the insecticides.IO,II)
Carboxylesterases are also important in the activation of
prodrugs. One such clinically important prodrug is irinotecan
(7 -ethyl-l 0-[4・(1・piperidino)ーI-piperidino]carbony loxycamp-
tothecin), an anticancer agent used as企ont-linetherapy for
colorectal cancer (Fig. 1). In humans, several CEs have been
well characterized, particularly liver CE 1 (hCE1) and human
intestinal CE (hiCE), the latter of which is localized to the
small intestinal epithelia. Both hCEl and hiCE are known to
convert irinotecan i凶oits active form, SN幽 38(7-ethyl-1O・hy-
l刷。t院制(CPT-11) S件38(actlve fonn 0' drug)
Fig. 1. lrinotecan (Ie丘)conversion to SN-38 (right) is one ofmany
reactions catalyzed by carboxylesterases.
Vol. 35, No. 3, 240ー249(2010)
droxycamptothecin; Fig. 1). However, hiCE is expressed at
high 1evels in the small intestine and is much more efficient at
converting irinotecan than hCE1.8,12) Thus, ov巴rproductionof
SN・38occurs in the small intestine during irinotecan therapy, and tissue damage to this organ contributes to delayed diar-
rhea in patients, a side司 effectthat often requires hospita1iza-
tionY) This is the dose-limiting toxicity of irinotecan. Devel-
opment ofhiCE-selective CE inhibitors to reduce or eliminate
unwanted toxicity of irinotecan has been the recent goal of
our laboratories. Selective hiCE inhibitors are envisioned as
adjuvant therapy for the modulation of diarrhea, potentially allowing for higher dosing of the drug and more effective
tr開館lentof colorectal cancer.
Several molecular structural scaffolds of CE inhibitors
exist, which include, sulfonamides, benzils, benzoins, carba-mates, isatins, organophosphates, oxysterols, pyrethoids, acridines, trazines, trifluromethylketones, piperidines, serine specific agents, and inorganic compounds. 1n general, most of these inhibitors show limited selectivity or specificity among
lsozymes or across specles.
Over the last several years, we have developed a number of
specific or semi-specific hiCE inhibitors. However, one diffi-culty that has persisted among these inhibitors is poor water
solubility. This review gives a brief overview of previously
described molecular scaffolds of CE inhibitors, followed by a
description of recent developments in the in silico methodolo-gies we are using to design new selective and specific in-
hibitors with greater water solubility and overall “drugability" of their chemical properties. Other, more detailed reviews of CE inhibitors have appeared recent1y.14,15) Here, our focus is
on computer-based development of selective inhibitors of
hiCE with the specific purpose of modulating irinotecan acti-
vation in the small intestine. However,仕lemethodology used
is general enough that it could be applied to the development
of inhibitors of any enz戸ne.
Carboxylesterase Inhibitors: Scaffolds, Selectivity, Specificity and Mechanism ollnhibition
1. Acetylcholinesterase lnhibitors and their CE inhibi司
tion. We begin this review by looking at selectivity for CEs by sev-
eral known groups of AChE inhibitors, starting with the
al匂lphosphonic esters, also known as organophosphate
(OPs), which may be the most well kn
ln si/ico design and evaluation of carboxylesterase inbibitors 241
nofluoridate), soman (Opinacolylmethylphosphonofluoridate) and tabun (ethyl dimethylamidocyanophosphate), which demonstrate high affinity for human AChE, have been used as
chemical warfare agents.
Carboxylesterases can also be irreversibly inhibited by
OPs. The mechanism of inhibition involves the attack from
the enzyme 's serine 0γon the phosphate atom of the OP. This
creates a covalent bond ending the mechanism at an acyl-e任
zyme intermediate. S仕ategiesto develop CEs to combat
chemical warfare compounds have been pursued by the mili-
tary. Essentially, CEs could be used as “bioscavengers," which work by sequestering or hydrolyzing a toxic subs仕ate.16)Re-
cent work shows that hCE1 shows a preference for binding
the PR enatiomers of soman and cyclosarin analogues (1700-,
2900田foldrespectively) and a slight preference for the P s
enantiomer of sarin analogues (5・fold).17)However, only one
group of OPs has been found to be semi-selective for CEs: the
benzodioxaphosphorines (Bomins; a町 ibutedto Patent USSR
06.22.1985. No. 1187444). Their selectivity however is only
about 10-fold greater than for AChE, and hence the problem-
atic toxicity of OPs make them an unlikely scaffold for devel司
opment of clinically useful compounds.
The CBs contain a central amide ester group and two alkyl
or紅ylsubstituents located on the nitrogen atom. CBs are not
as toxic as the OPs but they still induce the same cholinergic
effect. The CBs are reversible inhibitors of AChE and, like the
OPs, have been used as insecticides (e.g., Carbaryl (1・naph-
thyl methy1carbamate)). The CBs are also used in many clini-
cal applications. For example rivastigmine Cめ-N-Ethyl-N-
methyl・3・[ト(dimethylamino)ethyl]-phenyl carbamate is used
to treat Alzheimer's disease. Rivastigmine is a selective, re-versible brain AChE inhibitor.18)
Irinotecan also contains a carbamate moiety (Fig. 1), which is primarily responsible for its initial cholinergic activity.19,20)
Carbamates for CE inhibition have been explored by the Pot-
ter and Danks groups, who showed that four nitrophenyl de-rivativωwith carbamate linked side chains could selectively
inhibit hiCE and rCE.21) These derivatives were the first at-
tempt at developing specific hiCE inhibitors. However, inhibi-
tion by these compounds is also confounded by their AChE
inhibition, and hence has the potential problems associated with all cholinergic drugs.
Trifluorom
242 S. V. Stoddard et al.
to treat Alzheimer's disease. Tacrine itselfwas not an inhibitor
of hCE1, but 6,9・diamino之幽巴thoxyacridineand 9開 amino-6-
chloro-2-methoxyacridine did inhibit hCEl selectively over
hiCE. These derivatives are low μM inhibitors ofhCE1.23)
2. More司pecificCE inhibitors The AChE/CE cross inhibitors listed above came primarily
from studies that emphasized the similar catalytic activity of
the members of theα:/ s-hydrolase fold family. Indeedヲ the
very first collaboration between the Potter and Wadkins labo-
ratories was on molecular modeling of the interaction of
irInotecan with AChE and the related butyry1cholinesterase.24)
In the subsequent decade, the quest for isozyme-specific CE
inhibitors has produced several molecular scaffolds that do
not possess anti同AChEactivity. The design of many of the
analogs was a combination of chemical library screens to iso-
late reasonably selective CE inhibitors, followed by chemical intuition and plausible synthetic schemes.
Telik's Target Related Affinity Profiling (TRAP) method
was originally employed in the search for novel CE inhibitors.
In this method, compounds were screened for their binding
affinities toward a panel of protein targets. The binding affini-
ties were subsequently used to create an“affinity fingerprint," which was subsequently used to identifシnovelinhibitors.
Telik's methodology has the advantage of needing few initial
compounds to generate several new scaffolds of inhibitors.
The TRAP analysis had been utilized in the identification of
novel inhibitors for cyc1ooxygenase-l (COX_l).25) Hsu and
coworkers used 19 known COX-l inhibitors, all reversible competitive inhibitors of COX -1, comprising 8 structurally
dissimilar c1asses, to create an affinity fingerprint for COX-l inhibition. Using TRAP analysis, they derived 3 new COX-l
inhibitors. We used this method to identi今 novelCE irト
hibitors. The sulfonamides and benzils were both discovered through this methodology.26,27)
3. Sulfonamides The initial screening of a library of compounds isolated 9 sul-
fonarnide derivatives (Fig. 2) as specific hiCE inhibitors vs.
other human hydrolases.28) Using a limited quantitative struc司
Benzils Benzoins
。メPlbcトFig. 2. Chemical s仕uctureof 4 distinct c1asses of inhibitors that show selectivity for carboxylesterase isoforms.
Journal of Pesticide Science
知re-activityrelationship (QSAR) analysis of these 9 com-
pounds, a number of other sulfonamides were synthesized or
obtained from commercial sources. Examination of this larger
group of sulfonamides determined that the ring at the cen仕al
core moieザ couldaccommodate both benzene and fluo回
rene戸29)The fluorene sulfonamides, in general, are more po・tent than the benzene sulfonamides with inhibition constants
ranging企om41 to 3240 nM for benzene sulfonamides and
from 14 to 91 nM for the飢lOrenesulfonamides. The m司jority
of sulfonamides do not inhibit AChE or butyry1cholinesterase
(BChE), and hence are highly selective CE inhibitors.
The mechanism of inhibition for the sulfonamides is par-
tially competitive. However, unlike the majority ofthe CE in-
hibitors, there is no carbonyl carbon atom or electron deficient
atom that would be susceptible to attack from the serine Oy
residue. Attack on the sulfur atom of the sulfonamide is an
energetically disfavored process due to the stability of the sul-
fonamide. The sulfonamides could potentially hydrogen bond
to the enzyme and lock it into a stable complex, or they may bind to the opening of the active site, blocking the en仕 組ceto
the gorge. The extended conformation of the sulfonamides
matches the shape of the active site gorge of a homology
model of hiCE, so it is entirely possible that they occupy the binding site of the en勾岨le,giving rise to isoform specificity.
However, the sulfonamides as a whole suffer from very poor
water solubility. Evaluation of over 50 sulfonamides29) re-
vealed an inverse correlation of c10g P and log Ki・Hence,the least soluble compounds were the best inhibitors of the en同
zyme. This is the m司jordi伍cultywith using sulfonamides as
scaffolds for a potential drug application.
4. Benzils The diphenylethane四 1,2-dione(benzil; Fig. 2) analogues are
another c1ass of isotype-selective mammalian CE i吐ubitors
that we have examined after the initial drug screening. Benzil
itself is not a new compound (discovered in the late 1800s).
However, it was not until 2005 that is was discovered to be a
selective inhibitor for human CES.26) Inhibition constants (K)
r佃 ged企om4 to 18μM for 31 benzil analogues that were
evaluated, with no inhibition of. AChE. The analogs were
found to be a competitive reversible inhibitor of the CEs. The
proposed mechanism of inhibition involves the inability of the
enzyme to release the aldehyde as a leaving group. With no
appropriate leaving group after the formation of the te仕ahe-
dral intermediate, the initial carbonyl is reformed. The crystal
s仕uc旬reof hCEl has been solved with benzil in the active
site, suggesting that c1eavage of the dione moiety could occur, consequently generating a benzoic acid or benzaldehyde.30) In
con仕astto the sulfonamides, there is no correlation between c10gP values for these compounds and their Ki values, making them a much more interesting platform for drug development.
Their selectivity appears to arise企omthe diliedral angle of
the dione moie匂r.When the carbonyl oxygen atoms are cis-coplanar, greater selectivity for hCEl occurs, while non-pla-
Vol. 35, No. 3, 240ー249(2010)
narity results in selectivity for hiCE.31)
5. Benzoins and Fluorobenzoins.: ,
During the exploration of the ben:zil scaffold, compounds of
similar structure were. alsote'sted .for activity ag<iinst the
mammalian CEs. The cO}llpound, 1,2-diphe吋1ふhYdr9XY-
ethanone (be回 oin;Fig. 2) wasfOl.md.to be a weak but selec-
tive inhibitor ofCEs, having aKi of2.7μM for hiCE.and. 7.2
μM for hCE1. Subsequent additiori ofelec仕oniyithdrawing
groups to th巴benzenerings inboth beru.;ils and benZoins pro-duced more potent, highly selective inhibitors 1泊ιparticular,
addition of fluorine significantly increased their ability to in-
hibit mammalian CEs withoutresulting in inhibition of AChE
or BcChE. The inhibition constants for .the fluorinated ana-
logues ranged from 8 to 1.3μM.32)
In Silico Methods and Development of Isatins
1. Computational approaches
One conceivable m巴thodof computationally deriving selec-
tive inhibitors for CEs might be to dock small molecule li-
braries into the activ巴 siteof CEs in order to predict new in-
hibitors. However, in practice there are complications with that strategy that limit its effectiveness. The subs仕atespeci-
ficity of CEs is dependent on two structural features: the di-
mensions of their active site gorge and the external opening to
the gorge. We have gathered preliminary data on these impor-
tant parameters using molecular dynamics ca1culations of CEs
仕omrabbit, human liver, human intestine, and a bacterial CE
(rCE, hCEl, hiCE, and pNB, respectively). In addition, we have used normal mode ca1culations to examine low-fre-
quency motions of the CEs (large conformational changes).
Both the active site gorge diameter and the opening to the ac-
tive site fluctuate significantly with time (Fig. 3), so determin-
8.0
7.0
二~ 6.0
司a g国 5.0
曲 4日
z 。3.0
2.0
6 8
time (n5)
Fig. 3. Fluctuation in the diameter of the active site gorge of a CE
企omB. subtilis. The analysis was performed with a procedure modi-fied 企omthe work ofMcCammon and colleagues.64
) The solvent-ac-
cessible surface was ca1culated with an increasing probe radius until it no longer made contact with the active site Ser and His residues. The s仕ucturewas taken企omPDB code lQE3.65)
In silico design and evaluation of carboxylesterase inhibitors 243
ing which s仕ucturethe known inhibitors are binding to is
complicated. The basie rat~onale for the need to include mo-
lecular dynamics .in.tl1fdevelopment of e回 ymeinhibitors for
the related AChE hぉbeenrecently reviewed.33) This rationale
山 oapplies to句li'Brie臥 enzymesare in constant motion
at tempera旬res.riear 3,?oC,.and the understanding of the fluc-tuation isの cialやrin silico dσcking or ぉsemblyof in-
hibitors,'ln theヘease'oftheai' shydrolase fold family, the ac-tive site:reSidue~ areat the boftom ofa ca. 22 A gorge, the walls:of whic4 are :also"fluctuating. The crystal structure of
hiCE has. nofbeendetermined, and so by necessity a homol-
ogy model would needtote used for this enzyme (although, it should be noted thatearlier homology models of rCE20)
based on the folding"of AChE'were remarkably similar to the
subsequently-determinedcrystal structure34l;αcarbon RMSD
ca. 2 A). The crystaLstructures for the other 3 e回 ymes(rCE, hCEl, pNB) have been determined and hence MD ca1cula-
tions are easily accomplished. Even though the crystal struc-
tures exist, there is an additional reason MD is an important
tool for docking ligands into these molecules. As with other
enzymes, the crystal structures containing known subs仕atesor inhibitors in the active site have an active site that is too
small to accommodate other known, larger subs位ates.For ex司
ample, the structure of hCEl containing a product of benzil
hydrolysis would be too close-packed to allow placement of
CPT-ll in the same locale?O) This can be resolved by allow-
ing the enzyme structure to fluctuate; An example of this is
shown in Fig. 3, where the active site gorge diameter size of
the pNB CE is ca1culated throughout a lengthy 10 ns MD sim-
ulation. Note that access to the active site can fluctuate from
as little as 3.0 A to as wide as 7.5 A over a relatively short pe-
riod of 1 ns. Other regions of structural fluctuation in CEs are
the loops that form a putative lid over the entrance to the ac-
tive site gorge. Normal mode analysis (NMA) of hCEl and a
homology model of hiCE (modeled using hCEl as a tem-
plate) was performed with the EINemo web server,35) which is a web interface to the Elastic Network Model hat irnplements
the‘rotation-translation-block' (RTB) approximation. Th巴
lowest non-zero frequency mode for the enzymes having a
high degree-of-collectivity (mode 7) are shown in Fig. 4. It is
this fluctuation that makes MD a critical component of in-
hibitor design by com
244 S. V Stoddard et al Journal 01 Pesticide Science
Fig. 4. Fluctuation of the loop forming part of the“lid" over the active site in CEs (yellow residues) determined from normal mode calcula-
tions for (A) hCEl and (B) hiCE homology model. Th巴“lid"is oriented toward the bo仕omof each molecule. Arrows indicate the extent of mo-
tion for the entire e田 ymefor the lowest合equencymode (mode 7). Th巴viewis into the active site gorg巴 Theactive sit巴residuesSer, Glu and His are shown in green. While the e仔ecton catalysis of these loops is unknown, they may serve to either bind subs甘ateand guide it toward the
active site gorge or to cover the active to prevent di航路ionof substrate out ofth巴gorgebefore hydrolysis
tory involv巴susing not just one static structure of CE for
docking potential inhibitors, but rather numerous CE struc-
tures taken企oma molecular dynamics simulation.36) How-
ever, given the complications inherent in this approach, we developed a computationally-simpler multi-dim巴nsional
QSAR model as a reduced representation of the inhibitor
binding site. This has the advantage over crystal structure
docking approaches in that it does not require us to know the
molecular details of the inhibitor binding site, just the chemi-
cal properties and K; values for the inhibitors.
The idea for the indole-2,3-diones (isatin compounds; Fig. 2) was developed from this QSAR approach using biochemi-
cal data on the sulfonamide and benzil inhibitors. Our data
suggested th巴 pr巴senceof aromatic moieti巴sw巴r巴 important
for inhibition.31,37) Other earlier work found that there was a
size constraint on the entranc巴 toth巴 activesite gorge.20)
Using these two considerations as a parameter guide, a data-
base search of commercially available compounds related to
benzil was initiatecl, resulting in isatins as potential i吐libitors
of CEs. Simultaneously, a combination of QSAR and comput-
erized model building using the sulfonamide data led to the
prediction that indo1e-containing compounds would be CE in-
hibitors, and would also lead to selectivity for hiCE (Fig. 5)
This was ultimately borne out by analysis of 74 compounds
related to isatin, and the discovery of several that were selec-
tive for hiCE,38) with inhibition constants as low as 6 nM.
Below, we describ巴 indetail the computational analysis that
led to th巴 predictedstructures containing indole. Further, we describe the QSAR“grand model" that combines all com-
pounds that we have evaluated for inhibition of CEs.
2. QSAR
QSAR correlates the molecular structure and properties of a
set of compounds with their activity. The parameters used for
QSAR are molecular descriptors that can range from a simple
count of atoms to HOMO and LUMO calculations; elec-
tronegativity; and other quan印mmolecular features. A QSAR
model can also be modeled as a thr閃 -dimensionalstructure,
which will show visually the nature of the relationship be-
tween the inhibitors and the receptor. QSAR has long been
popular in assisting in the determination of essential interac-
O q
=0
O
O
HO
u くつ
り川、ノ
Fig. 5. Selected indole-containing compounds originally predicted
by the de 110νo design software LigBuilder to be good inhibitors of
hiCE using a QSAR model based entirely on sulfonamides. Th巴pre-
diction led to discovery and evaluation of isatins38)
Vol. 35, No. 3, 240-249 (2010) In silico design and evaluation of carboxylesterase inhibitors 245
tions between the receptor and inhibitor. In our previous s旬d-
ies, almost all of the CE inhibitors have been investigated
through QSAR. These studies generated suggestions for im-
proving the activities of inhibitor compounds (e.g., the addi-tion of halogens, and inclusion of a larger aromatic moiety in the core ofthe inhibitor structure.28,39,40)
QSAR reveals the important interactions between the lig-
ands and the receptor site by using ligands that are known to
be active inhibitors of the receptor of interest. The de novo
design is an approach to s位ucture司baseddrug discovery that
utilizes a binding site pocket to build ligands specifically for
the receptor.41,42) Common de novo design programs that are
used today are GRID,43) SPROUT,44,45) CONCERTS,46) SYN-
OPSIS,47) LeapFrog,48) and LigBuilder.42)
Using QSAR models as pocket sites for de novo design is
an approach that can be utilized when no experimental recep-
tor structure is available. Combining QSAR and de novo de-
sign has been used by several investigators.49-53
) For example, Gueto and coworkers49) developed a comparative molecular
fields analysis (CoMFA) model for aromatase inhibitors with
45仕ainingset compounds and used a test set of 10 sulfo-
nanilide compounds. This CoMFA model was used to gener-
ate new inhibitors in silico with the NEW module of
LeapFrog, followed by calculation of their predicted activity. As another example, Kapou and coworkers50) combined
CoMFA and CoMSIA with LeapFrog to study and design
steroidal mustard esters using a仕ainingset of 26 compounds
and test set of 12 compounds. This model was then subse-
quently used to design new inhibitors using the OPTIMIZE
module ofLeapFrog.
CoMFA uses a grid-based approximation to develop 3D-
QSAR models, and includes parameters such as steric and el即位ostaticeffects by using both a Lennard-Jones and
Coulombic potential. CoMSIA and LeapFrog also use a grid-
based approximations to develop new compounds with good
binding energies. In our laboratory, we have used the Quasar program54,55) to develop a 6D四 QSARmodel for hiCE in-
hibitors, and the de novo design program LigBuilder to gener-ate new scaffolds of hiCE inhibitors (Table 1). The Quasar
program is a grid-based technique as well, and it employs a
genetic algorithm for model generation and induced fit. In ad-
dition of the 3 spatial dimensions of Quasar, the 4th dimension
Table 1. Potential selective hiCE inhibitors output by LigBuilder using the QSAR structure shown in Fig. 6. While many of these com司
pounds are synthetically unfeasible, they do present a series of scaffolds that, combined with chemical intuition, may produce selective in司
hibitors in much the way the isatins were discovered.
Structures企omDicarbonyl I Structures企omPara amino I Structures企omPara amino I Structures from Benzene seed I aniline seed-l I aniline seed-2 I seed
dq ケ。
除
附。ば。ず。
ofrも4タ
O N
均 作p
百司、川
H
246 S. V. Stoddard et al
allows for analysis of different conformations of ligands (4D-
QSAR), while the 5th dimension takes into account the poten-
tial for induced fit (5D-QSAR).54) The 6th dimension of
Quasar added the ability to investigate different solvation ef-
fects (6D-QSAR).55) The following equation is used for ca1cu-
lation ofbinding affinity in Quasar.
E.._..__ = E..___. _____.__ -E..___. .___,.._..__ -E..___. _._._ -T /';.S binding -.LIligand-receptor .LIligand desolvation .L...Iligand strain
Einduced fit
The terrn EJjgand-receptor is calculated by the following equation,
E_,__.___._.._ + E____ .__ ,,,__,_ + E....,_____ .___..__ + E trostatic I Llvan der Waals I .LJhydrogen bonding I .L...Ipolari
Spreafico and coworkers have successfully used Quasar to de-
velop models that inc1ude several c1ass巴sof compounds.56)
Their data indicate that Quasar is effective when combining
steroids, quinoline derivatives f1uorophenylindazole d巴nva-
tives, and spirocyc1ic derivatives as inhibitors of glucocorti-
coid receptor.
The QSAR model developed in our study inc1uded sulfon-
amide, benzil, f1uorobenzoin, and isatin inhibitors (Fig. 2).
The TFKs were omitted because their mechanism of binding
is different from the rest of these inhibitors, and requires a
pre-incubation time to be most e汀ective.57)A more thorough
investigation of TFK inhibition has recently appeared.40) Our
previous studies have us巴dQSAR for development of pseudo-
receptor site models in an effort to delineate pertinent infor-
mation about the active site that could be useful in the design of new inhibitors.26,27,29,3 I ,57-59) However, these studies only
somewhat used the pseudo-receptor site models for de novo
design of potential inhibitors and were derived from limited
data sets. Here we report our results on predicted structures
usmg a “grand mod巴1"of CE inhibition based on data 企om
210 CE i山 ibitorscomprising four inhibitor families. Our ex-
Journal 01 Pesticide Science
pectatlOns wer巴thatusing this pseudo-receptor site as a hypo-
thetical binding site might yield inhibitors other than indoles
with improved drug-like properties (e.g., better water solubiト
ity).
The 6D-QSAR mode1ing of hiCE inhibitors was performed
using Quasar 6.2 software running under Mac OS X. The 210
structures used inc1uded 4 diverse scaffolds; benzils, f1uo-
robenzoins, isatins,組dsulfonamides. Each analog had been
previously drawn using Chemdraw, imported into Chem3D,
and minimized first by using the }..仏12molecular mechanics
force field, followed by the PM3 semi-empirical method
within MOPAC.60) The solvation energies and charges were
ca1culated using AMSOL and the SM5.42R solvation
method.61) SM5.42R is a rigid solvation mode1, which opti-
mizes a compound's strucωre in the gas phase but optimizes
only its elec甘onicstructure in the solvent phase. Gas phase
charges were used for all QSAR analysis.
A仕ainingset of 133 compounds and a test s巴tof 77 com-
pounds w巴reus巴dto build the QSAR model. Th巴 K;values
that were used for these computations were those d巴rived
from the inhibition of o-nitrophenylacetate hydrolysis. As
with any QSAR model that uses structurally divergent lig旬
ands, the complication in this proc巴ssis th巴choiceof how to
align the structures with one another. We chose the central
benzene ring of the sulfonamide inhibitors as the template to
which all the other compounds would be aligned. The result-
ing 3D-pseudo-receptor site model describing the interactions
between the active site and the ligands is shown in Fig 6, and
is referred to as the “grand model" for hiCE inhibitors. The r2
(squared correlation coefficient of model) and q2 (predicted
squared correlation coefficient, which describes the predictive
quality of the model) generated were both 0.84, and the pr巴ー
dicted vs. experimental /';.Go for inhibition constant values are
shown in Fig. 7. This QSAR model was fairly robust in pre-
diction of inhibitor binding, and therefore we used it as a tem-
Fig. 6. St巴reovi巴wof the 3-dimensional“grand model" for hiCE i凶libitorsis depicted as colored spheres on a hydrophobic gray grid. Areas
that are hydrophobic ar巴indicat巴din gray, whereas dark blue spheres represent areas that are positively charged (+O.25e) and light blue spheres
correspond to lesser charg巴(+O.le).Dark red spheres repr巴sentareas that ar巴negativelycharged (一O.25e),light red spheres indicate less nega-
tive charge (一O.le).In all cases, e is the charge of the proton. The structure of representative sulfonamides (black), isatins (blue), benzils
(green), and benzoinsωink) are shown. The figur巴wasgenerated using Molscript66) and Rast巴r3D67)
Vol. 35, No.3, 240-249 (2010)
-2
-4
i e gu
s-a E !::! -10
冨a..
.a
• b
一一一-v=-1.3431+O.83541x R'=O.83896 ・14I
・12 ・11 ・10 ・9 -8 ・7 ・6 ・5
Experimental AGo (kcaVmol)
Fig. 7. Predicted vs. experimental L¥Go values (in kcaVmol) for in-hibition constants of 4 c1asses of mole氾ules白atinbibit the hiCE hy-drolysis of o-nitrophenylace旬旬.Ki valωs were determined using a partially-competitiv官 inhibitormodel. The training set is indicated by the filled ovals, while the test set is represented by open boxes. The compound labeled “a" is a disulfide and is the lone memb巴rhaving this moiety. The compound labeled “b" is a 2,5-bis(tri畳間romethyl)benzil analog. Its surprising lack of activity is under investigation. For c1arity, compounds with Ki values > 1 00μM ar巴notincluded on this plot.
p1ate upon which to bui1d new mo1ecu1es.
3. De Novo ligand design
The next step in the process was to have LigBui1der synthe-
size potentia1 inhibitors based on the 3D-QSAR s仕ucture.
LigBui1der begins with a user-defined seed s仕ucturethat is
the starting point for bui1ding new ligands by adding mo1ecu-
1ar fragments to the seed unti1 the binding site is削 1yoccu-
pied. Each compound derived in this manner is eva1uated via
the Lipinski“ru1es,吋2)and compounds vio1ating these ru1es
are rejected. LigBui1der uses an empirica1 scoring function to
eva1uate binding a伍nity,which is much different than that
used by Quasar. LigBuilder a10ne has been combined with
docking and pharmacophore mode1ing to design inhibitors for
勿rosinekinase 2,63) but to our know1edge has not been com-
bined with QSAR mode1s for 1ead compound deve1opment.
To account for the other 3・・dimensionsof 6・DQSAR, the ver-tices of the mode1 shown in Fig. 6 were assigned pseudo司
atomic properties within LigBui1der based on the correspon-
ding property indicated in the 1egend of Fig. 6. With this
mode1 as a hypothetica1 active sit巴, potentia1 inhibitors for
hiCE were cons仕ucted企omthe seed structures 1,2・dione,p司
aminoani1ine, and benzene. For benzene, growth was allowed from all carbons in the ring. For p-aminoaniline, two seeds were used. The first allowed growth on1y off the amino group
ni仕ogens,whi1e the second allowed growth off both the
amino groups and all unsubstituted ring carbons.
In silico design and evaluation of carboxylesterase inbibitors 247
The results of this process is shown in Tab1e 1 for the dif-
ferent starting seeds. Once the structures were generatedヲthey
were eva1uated in the 6D-QSAR shown in Fig. 6, and the top 5 ranked structures (lowest predicted Ki va1ues) are shown.
All of these computationally-derived structures were pre-
dicted to have good activities against hiCE, with企巴eenergy
scores in the range of -10 to -13 kca1/mo1 (Ki合om46.73 to
0.33nM).明司u1eon1y a se1ect few compounds are shown in
Tab1e 1, over 40 new structura1 c1asses of inhibitors emerged 企omthis in silico process. These c1asses show new features
such as a 1arge aromatic or p1anar groups attached to a 10ng
a1ky1 chain, the inc1usion of a 1arge part of the po1ar groups
within cyc1ic ring systems, two aromatic group join together by a cen凶 1a1防1group, and hybrid compounds that are a
cross between two or more groups of inhibitors.
Tab1e 1 a1so illus仕atesa prob1em with computer-generated
1igands. C1early, some of the predicted compounds are not feasib1e as biochemically active mo1ecu1es, particu1arly the anhydrides that wou1d be high1y reactive with water. However, ignoring such unfeasib1e compounds, water solubility of most of the predicted structur巴susing ALOGPS 2.1 indicated they
have greater solubility than the su1fonamides, and many have
solubility comparab1e to the anticancer drug irinotecan. This
suggests, that the solubility can be enhanced whi1e maintain-
ing or even improving the activity when a combined approach
is used. Synthesis of a subset of these new c1asses of irト
hibitors is underway to verifシthepredicted results.
Conclusions
Over the 1ast decade, QSAR has allowed a detailed ana1ysis of
known CE inhibitors and he1ped to generate CE inhibitors
with greater specificity. As an examp1e, tetrafluorine substi-tuted su1fonamide ana10gs were synthesized when QSAR
ana1ysis of nine su1fonamides suggested the addition of ha1o-
gens wou1d increase potency.27) The observed results con-
c1uded that this new inhibitor had greater se1ectivity for hiCE
versus hCEl than the previous nine. Another examp1e is the
fluorene su1fonamides,29) which were pursued because results
仕ompseudo-receptor sites suggested that the active site of
hiCE cou1d accommodate a 1arger aromatic moiety. The fluo・
rene su1fonamides proved to be much more potent than the
structurally-simi1ar benzene su1fonamide. The specificity was
a1so not a貧民tedby inc1usion of the fluorene moiety in the
core. Hence, QSAR (particu1arly, the 6D-QSAR methodo1ogy used by Quasar) is an inva1uab1e too1 for deve10ping specific
hiCE inhibitors.
Whi1e QSAR ana1ysis has aided in the design to-date of
more potent and specific inhibitors, it has not effective1y ad-dressed the issue that p1agues most of the CE inhibitors de-
signed theoretically: 10w aqueous solubi1ity. The ana1ysis and
d田 igndescribed in this artic1e suggest features of potentia1
inhibitors that will increase their water solubi1ity and yet re-
tain or enhance potency. Further, our QSAR mode1s are bene-
ficia1 in understanding how the inhibitors are interacting
248 S. V. Stoddard et al.
within their binding site, which is presumed to be the enzyme active site. Such studies are useful in pointing toward opti-
mization of lead compounds for structural scaffolds that may
be discovered through means other than computer-generated
structures.
Acknowledgements
This work has been suppo討edby the US National Science Founda-
tion EPSCoR grant EPS・0903787,NIH grant CAI08775, the Ameri-
can Lebanese Syrian Associated Charities (ALSAC), and St. Jude
Children's Research Hospital (SJC悶).
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1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111
英文編掲載報文・短報等の要旨1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111
総説(スペシャルトピック:カルポキシルエステ
ラーゼ)
カルボキシルエステラーゼの分子構造と機能調節並びに新
分類法
佐藤哲男,細川正清
本総説では,カルボキシルエステラーゼの分子構造と機
能について概説した.カルボキシルエステラーゼには複数
の分子種があり,従来それらは基質特異性の違いに基づい
て分類されていたが,その方法では個々の分子種間で重複
が多いために明確に区別する事が困難であっfこ.それを解
消する目的で,著者らは各分子種の分子構造や機能の違い
に基づく新たな分類法を提唱した. 2010年に著者らが提唱
した分類法を基本とするカルボキシルエステラーゼ分子種
の新分類法が研究者間で国際的に承認された.また,動物
および人の各臓器に特有のカルボキシルエステラーゼ分子
種の遺伝子発現と,その調節機構についても明らかにした.
さらに,カルボキシルエステラーゼ分子種の一種であるエ
ガシンが,有機リン剤に極めて高い親和性を有する性質を
利用して,有機リン剤暴露時における新たなバイオマーカー
を開発した. この方法は,従来のコリンエステラーゼ阻害
法に比べてはるかに鋭敏であることが,動物および人にお
ける有機リン剤暴露時の結果から明らかになった.
カルボキシルエステラーゼ活性を利用したプロドラッグの
開発:哨乳動物組織におけるカルボキシルエステラーゼの
触媒特性と発現調節
今井輝子,細川正清
プロドラッグはそれ自体は薬理学的に不活性であり,生
体内で薬理効果の強い親薬物に変換される.プロドラッグ
化の長所は,標的臓器への薬物の到達,治療効果の最適化,
そして,副作用の回避を可能にすることである.プロドラッ
グ化のための化学修飾には,エステル結合やアミド結合が
利用されることが多く,そのため,プロドラッグの生体内
変換にはカルボキシルエステラーゼ (Carboxylesterase,CES)
が重要な役割を果たしている. CESには基質特異性の異な
る複数の IS0勾岨eが存在し,その発現組織は異なる.例え
ば, ヒト肝臓と小腸には,それぞれ hCElとhCE2が主に発
現し,臓器特異的な加水分解活性に寄与する. したがって,
これらの酵素の基質認識性の相違を利用することによって,
プロドラッグは理論的にデザインすることができるはずで
日本農薬学会誌 35(3),373-376 (2010)
ある. しかしながら, CESの発現レベルは個人差があり,
その結果,薬理効果の個人間差異を惹起することがある.
また,動物種によって CESの発現分子やその発現量は異な
るため,前臨床の動物実験で得られた結果からヒトにおけ
る効果を予測することは困難である. したがって,プロド
ラッグ創薬においては,代謝活性化の中心的役割を担って
いる CESの基質特異性,種差,臓器差,個人差を把握する
ことは非常に重要である.
カルボキシルエステラーゼ阻害剤のインシリコデザインと
評価
Shana V. Stoddard, Xiaozhen Yu, Philip M. Potter,
Randy M. Wadkins
カルボキシルエステラーゼ (CE)はさまざまな基質分解
や薬剤代謝にかかわる重要な酵素である. CE阻害剤の開発
は,薬剤の寿命延長や体内分布の調節,代謝された薬物の
毒性の軽減や除去,殺虫剤耐性害虫の低減などに役立つこ
とが期待される.ここでは,晴乳類 CEの既知の阻害剤の
主要なクラスについて概説するとともに,特異性のある新
規阻害剤を開発するための計算化学的なアプローチについ
ても述べる.インシリコにおける阻害剤開発において,構
造のドッキング,データベース検索,多次元 QSAR,そし
てdenovoドラッグデザインと結びついた QSARを使った
新規手法を含む一連の方案を議論する.本研究では, ヒト
小腸のカルボキシルエステラーゼ (hiCE)阻害剤をデザイ
ンしたが,その手法は他の組織や生体からの CEを含む多
くの酵素阻害剤の開発に広く応用できるであろう.
(文責:編集事務局)
ヒトカルボキシルエステラーゼ 1による農薬分解とその構
造
Andrew C. Hemmert, Ma抗hewR. Redinbo
ヒトカルボキシルエステラーーゼ 1(hCE1)は主な肝臓の
カルボキシルエステラーゼである.第 I相薬物代謝経路に
おいて,広範囲な生体内物質,生体外異物および農薬は解
毒される.これまで,有機リン剤を含むさまざまなリガン
ドと複合体を形成している hCElのX線結晶構造体が十数
種類あまり解析され, hCElによる農薬の代謝分解に有用情
報を与えてきた.例えば,触媒的トリアッドを構成してい
るさまざまな結合部位,およびこの部位を取り囲んでいる
長くてフレキシブルなループが基質特異性に関与している
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