Design and development of pyrrole carbaldehyde: An effective pharmacophore for enoyl-ACP reductase

MEDICINAL

CHEMISTRY

RESEARCH

Med Chem Res

DOI 10.1007/s00044-016-1517-y

ORIGINAL RESEARCH

Design and development of pyrrole carbaldehyde: an effective

pharmacophore for enoyl-ACP reductase

Shrinivas D. Joshi¹Devendra Kumar¹Uttam A. More¹

•

Kap Seung Yang²Tejraj M. Aminabhavi¹

•

Received: 18 March 2014 / Accepted: 25 January 2016

Ó Springer Science+Business Media New York 2016

Abstract Enoyl-ACP reductase is the key enzyme

involved in FAS-II synthesis of mycolic acid in bacterial

cell wall and is a promising target for discovering new

chemical entity. The designed pharmacophores are the

possible better tools to combat mutation in enoyl-ACP

enzyme, which leads to a decrease in volume of triclosan

binding site. Compound 3a showed H-bonding interactions

similar to that of triclosan with enoyl-ACP enzyme and

with a better docking score (C score 8.81), while the

compound 3f showed additional interaction with MET98.H

amino acid residue. The 3D-QSAR computations also

support the docking study to develop novel pyrrole-based

derivatives.

Graphical abstract Molecular docking 3D-QSAR studies

and synthesis of active analogs of pyrrole carbaldehyde as

better receptor ﬁt pharmacophore for enoyl-ACP reductase

along with in vitro antitubercular activity.

Keywords Pyrroles Á Antitubercular activity Á

Molecular docking Á 3D-QSAR Á Enoyl-ACP reductase

Introduction

Tuberculosis (TB) is a leading cause of death worldwide,

despite the global efforts and ﬁnancial investment by the

government and non-governmental organizations in disease

control (Raviglione et al., 2012). According to WHO 2012

global report on TB, it was estimated that 3.7 % (range

2.1–5.2 %) of new cases and 20 % (range 13–26 %) of the

previously treated cases have multidrug-resistant tubercu-

losis (MDR-TB). In Eastern Europe and Central Asia,

9–32 % of the new patients and more than 50 % of the

previously treated patients are affected with MDR-TB

(WHO, Global Report, 2012). Such global increase in the

resistance of MDR-TB reﬂects inappropriate use of anti-TB

drugs during the treatment course of patients with drug-

susceptible strains (Espinal et al., 2001). Additional factors

like immigration, sex, age, HIV infection and

Electronic supplementary material The online version of this

article (doi:10.1007/s00044-016-1517-y) contains supplementary

material, which is available to authorized users.

& Shrinivas D. Joshi

shrinivasdj@rediffmail.com

Kap Seung Yang

ksyang@chonnam.ac.kr

1

Novel Drug Design and Discovery Laboratory, Department

of Pharmaceutical Chemistry, S.E.T’s College of Pharmacy,

Sangolli Rayanna Nagar, Dharwad 580 002, India

2

Department of Polymer and Fiber System Engineering,

Chonnam National University, 300 Yongbong-Dong, Bukgu,

Gwangju 500 757, Korea

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Med Chem Res

socioeconomic factors have shown to be associated with

the increased prevalence of MDR-TB (Faustini et al.,

2006). Almost half of the global MDR-TB cases have been

reported from the heavily populated areas of China and

India (WHO, Global Report, 2010).

et al., 2013b, 2014a, b; More et al., 2014). Continuing our

study on enoyl-ACP reductase, herein we report docking

and 3D-QSAR studies of the newly synthesized com-

pounds having antitubercular activity. The drug design

concept of this study is based on the reported data of

marketed drug containing pyrrole core (Aloracetam),

developed by Aventis for the treatment of neurodegenera-

tive disease (Fischer et al., 2004) as well as the well-known

antibacterial agent triclosan along with antimycobacterial

agent BM212 (see Fig. 1).

Isoniazid (INH), a frontline antitubercular agent, is a

pro-drug that requires activation to form the active

metabolite (INH-NAD adduct), which exerts its lethal

effect on intracellular target (Zhang et al., 1992; Johnsson

and Schultz, 1994; Johnsson et al., 1995). The INH-NAD

adduct inhibits mycolic acid biosynthesis in Mycobac-

terium tuberculosis by affecting the InhA, an enoyl-ACP

reductase enzyme of the type II fatty acid synthesis (FAS-

II) system, which catalyzes the last step of fatty acid

elongation cycle (Quemard et al., 1991). Among these,

fatty acid biosynthesis-I (FabI) constitutes a single isoform

in the majority of pathogens such as Staphylococcus aureus

(Heath et al., 2000), Escherichia coli (Heath and Rock,

1995) and M. tuberculosis (Banerjee et al., 1994). The

clinical success of InhA inhibitor INH (Quemard et al.,

1995) and numerous reports of FabI inhibitors (Lu and

Tonge, 2008) involving the diazaborines (Baldock et al.,

1996), 4-pyridones (Kitagawa et al., 2007), naphthyridi-

nones (Seefeld et al., 2003), triclosan and analogs

(McMurry et al., 1998; Chhibber et al., 2006; Park et al.,

2007; Sivaraman et al., 2004; Sullivan et al., 2006; Tip-

paraju et al., 2008) have validated this target as one of the

most attractive of the FASII pathway. This enzyme is

recognized and validated as an important drug target in M.

tuberculosis, since its homolog in the humans is absent.

Several azole compounds containing imidazole, pyrrole,

and toluidine or methanamine group were tested for anti-

myobactrial activity against drug-resistant and intra-

macrophagic mycobacteria (Biava et al., 1997; Fioravanti

et al., 1997). Among these, pyrrole derivatives BM212

seem to be endowed with potent and selective antimy-

cobacterial properties (Deidda et al., 1998). Recently,

spontaneous mutants resistant to BM212 and SQ109

compounds with anti-TB activities have shown to contain

mutations mapping to mmpL3 (for mycobacterium large

membrane protein) (La Rosa et al., 2012). The mmpL3 was

found to be essential in mycobacteria and conditional

depletion of mmpL3 in Mycobacterium smegmatis that

resulted in the loss of cell wall mycolylation (Varela et al.,

2012).

Molecular modeling/docking studies

The 3D structures were generated using the Chem draw 3D

software. By using the standard bond lengths and bond

angles, the geometry optimization was carried out with the

help of standard Tripos force ﬁeld (Clark et al., 1989) with

a distance-dependent dielectric function, energy gradient of

0.001 kcal/mol and Gasteiger–Huckel as the electrostatics.

Conformational analyses of 23 compounds were performed

using repeated molecular dynamics-based simulated

annealing approach as implemented in Sybyl-X 2.0 (Tripos

Inc., St. Louis, USA). All the conformations were mini-

mized with Gasteiger–Huckel charges.

Data set and structures

The in vitro antitubercular activity (expressed as minimum

inhibitory concentration, MIC) was converted into pMIC

(log MIC) values, which were used to construct the 3D-

QSAR models. Structures and biological activities of the

compounds are summarized in Table 1. The 3D-QSAR

models were generated using a training set of 18 mole-

cules; the predictive power of the resulting models was

evaluated using a test set of ﬁve molecules. Test com-

pounds were selected randomly such that the data set

included diverse structures and a wide range of activity

(diversity method).

Alignment rule

A common substructure-based alignment was adopted,

wherein molecules were aligned to the template molecule

on a common backbone as illustrated in Fig. 2. For data-

base alignment of the inhibitors, the structure of compound

3a (bioactive conformation of the compound 3a) was used.

Of late, due to the availability of computational methods

including 3D-QSAR tools like CoMFA and CoMSIA are

being increasingly employed in rational drug discovery to

understand the drug–receptor interactions for designing

new molecules. In our previous work, we have reported the

pyrrole analogs as antimycobacterial, antifungal and

antibacterial agents (Joshi et al., 2008, 2013a) on which

docking 3D- and 2D-QSAR studies were performed (Joshi

CoMFA and CoMSIA settings

In order to better understand and explore the contributions

of electrostatic and steric ﬁelds in the binding afﬁnity and

potency of pyrrole scaffold as well as to build the

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Med Chem Res

Fig. 1 Searching for better receptor ﬁt ligand in comparison with triclosan in enoyl-ACP receptor

˚

2.0 A in each direction. The CoMFA region focusing

predictive 3D-QSAR models, the CoMFA studies were

performed based on molecular alignment. The contribu-

tions of steric and electrostatic ﬁelds were calculated using

the Lennard–Jones and Coulombic potentials, respectively

(Cramer et al., 1989). The aligned training set of molecules

was then placed in a 3D grid box to include the entire set.

The CoMFA steric and electrostatic ﬁelds were generated

at each grid point with Tripos force ﬁeld using sp³carbon

atom probe carrying (a ? 1) net charge.

method was applied to increase the resolution of CoMFA

models. The default value of 30 kcal/mol was the maxi-

mum steric and electrostatic energy cutoff. The CoMSIA

was used in which similarity indices were calculated at

different points on a regularly spaced grid for pre-aligned

molecules. In this approach, four different similarity ﬁelds,

viz, steric, electrostatic, hydrophobic and H-bond acceptor,

were selected to cover major contributions to the ligand

binding. In CoMSIA ﬁelds, singularities were avoided at

atomic positions because the Gaussian type distance

dependence of each physicochemical property was

˚

The CoMFA grid spacing of 2.0 A in x, y and z direc-

tions and the grid regions were generated by the CoMFA

routine to encompass all the molecules with an extension of

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Med Chem Res

Table 1 Data set of chemical structures and their antitubercular activity against Mycobacterium tuberculosis H₃₇Rv (3a–w and 2a)

Comp.

no.

n

R

R₁

R₂

MIC (lg/

ml)

3a

3b

3c

3d

3e

3f

0

1

0

1

0

3NO₂

4NO₂

4Cl

H

CHO

H

3.12

6.25

25.0

12.5

25.0

6.25

3.12

6.25

12.5

6.25

50.0

6.25

12.5

25.0

12.5

25.0

6.25

H

3Cl

H

4Br

H

2NO₂

4OCH₃

3Br

H

3g

3h

3i

H

2Br

H

3j

4Cl

H

3k

3l

3Cl

H

3NO₂

4NO₂

4Cl

CHO

H

3m

3n

3o

3p

3q

3r

3s

3Cl

4Br

2NO₂

4OCH₃

4Cl

3t

2Cl

3u

3v

3w

2a

3OCH₃

3Br

CHO

H

2Br

3NO₂

adopted, and thus, no arbitrary cutoffs were necessary,

and default value of 0.3 was used as the attenuation

factor (a).

Partial least squares (PLS)

Partial least squares regression (PLS regression) is a sta-

tistical method that bears some relationship to the principal

components regression; instead of ﬁnding hyperplanes of

minimum variance between the response and the inde-

pendent variables, it ﬁnds a linear regression model by

projecting the predicted variables as well as the observable

variables to a new space. All the latent variable path

Fig. 2 Database alignment against most active conﬁrmation of

compound 3a

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models in PLS consist of three sets of relationships: (a) the

inner model, which speciﬁes the relationship between

latent variables (LVs), (b) the outer model, which speciﬁes

the relationship between LVs and their association

observed or manifest variables (MVs), and (c) the weight

relations upon which the case values for LVs can be esti-

mated. Without loss of generality, it can be assumed that

LVs and MVs are scaled to zero means and unit variance

such that location parameter (i.e., constant parameter

terms) can be eliminated (Chin, 1998).

value of [0.5 were sought, since at this value, the proba-

bility of chance correlation was\5 % (Clark et al., 1990).

Predictive ability of CoMFA and CoMSIA models

(r²_pred

)

In assessing a PLS model, we start by looking at the r²for

each dependant LV provided by PLS for the structural

model. This is obtained because the case value of the LVs

is determined by the weight relations. The change in r²can

be explored to see whether the impact of particular inde-

pendent LV on a dependent LV has substantive impact.

Speciﬁcally, the effect size, f²can be calculated as (Chin,

1998):

Inner model

The inner model depicts the relationship among the latent

variables based on substantive theory,

r_i²_ncludedÀ r_e²_xcluded

f²¼

ð4Þ

1 À r_i²_ncluded

g ¼ b₀þ bg þ n þ f

ð1Þ

where g represents the vector of endogenous latent vari-

ables, n is a vector of the exogenous latent variables and f

is the vector of residual variable (Chin, 1998).

The value of r²is a measure of % data that can be

satisfactorily explained by the regression analysis

(Thomas, 2007). The application of special multivariate

statistical analysis such as PLS analysis and L_OOcross-

validation ensures statistical signiﬁcance of the ﬁnal

CoMFA equation. The outcome of this procedure is a

cross-validated correlation coefﬁcient, q², which is

calculated as:

Outer model

The outer model deﬁnes how each block of indicators

relates to its latent variable. The MVs are partitioned into

non-overlapping blocks. For those blocks with reﬂective

indicators, the relationship can be deﬁned as:

P

2

ðy_iÀ y^Þ

i

q²¼ 1 À

ð5Þ

P

2

ðy_iÀ yꢀÞ

x ¼ K_xn þ e_x

y ¼ K_yg þ e_y

ð2Þ

ð3Þ

ˆ

where y_i, y_iand yꢀ are actual, estimated and averaged

activities, respectively. However, the statistical meaning of

q²is different from the conventional r²that is a q²value

[0.3 is often considered signiﬁcant (Agarwal et al., 1993).

By PLS analysis, r²predicted for CoMFA and CoMSIA

were 0.81 and 0.56, respectively. Cross-validated and non-

cross-validated statistical parameters of CoMFA and

CoMSIA models are summarized in Table 2.

where x and y are the MVs for exogenous and endogenous

LVs, n and g, respectively. The terms K_xand K_yare the

loading matrices, representing the simple regression coef-

ﬁcients connecting the LV and their measures. The resid-

uals for the measure e_xand e_yin turn can be interpreted as

measurement error (Chin, 1998).

The optimal number of components was determined

with samples-distance partial least squares (SAMPLS)

(Bush and Nachbar, 1993) and cross-validation was carried

out by the leave one out (L_OO) method. The model with an

optimum number of components (highest q²) and with the

lowest standard error of prediction (SDEP) was considered

for further analysis. Equal weights were assigned to steric

and electrostatic ﬁelds by CoMFA_STD scaling option. To

speed up the analysis and reduce the noise, columns with r

value of \2.0 kcal/mol were ﬁltered off to compute the

conventional r²using the optimum number of components.

To further assess the robustness and statistical conﬁdence

of the derived models, cross-validation and bootstrapping

(Cramer et al., 1988) analysis for 100 runs was performed.

Statistical calculation was performed on each of these

bootstrap samplings. Models with a cross-validation (q²)

Molecular docking and scoring

The protein coordinate of enoyl-ACP reductase from M.

tuberculosis (2X22) bound to PT70 was downloaded from

the Protein Data Bank (Luckner et al., 2010). The ligand

was separated from the protein, and hydrogens were added

to free templates for protein residues. All the compounds

were docked using Sybyl-X 2.0 software (Tripos Inc., St.

Louis, USA). Compounds that were docked in this study

contain Gasteiger–Huckel charge, while the biopolymer

contains Amber7FF99 charges; the geometry of the

enzyme was optimized using the Tripos molecular

mechanics force ﬁeld. Docking was carried on 2X22 (A

chain) protein using the default setting of Sybyl-X 2.0

program, in which all the water molecules were removed

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CoMSIA

Table 2 Statistical parameters of CoMFA and CoMSIA models by the PLS analysis

Method

Parameters

CoMFA

Cross-validation

Optimal components

2

r²_loo

r²_pred

r²_bs

0.81

0.87

0.02

0.58

0.86

0.13

98.13

0.56

0.54

0.73

0.05

0.53

0.72

0.19

40.00

SD_bs

q²

r²

Non-cross-validation

PLS parameters

SEE

F

Norm coefﬁcient

Fraction

Norm coefﬁcient

Fraction

Steric

0.74

0.75

–

0.28

0.29

–

0.13

0.16

0.01

0.17

0.21

0.12

0.22

Electronic

H-bond donor

H-bond acceptor

–

and essential H atoms were added randomly and then the

Dock scores were evaluated by the consensus score (C

score) (Clark et al., 2002). The C score integrates a number

of popular scoring functions for ranking the afﬁnity of

ligand bound to the active site of a receptor. The strengths

of individual scoring functions combine to produce a

consensus that is more robust and accurate than any single

function for evaluating the ligand–receptor interactions.

Moreover, the D score, PMF score (potential of mean

force) (Muegge and Martin, 1999), G Score (Kuntz et al.,

1982) and Chem Score (Eldridge et al., 1997) were also

calculated to get better insights.

Conversion of 2a–w to different mono-substituted and di-

substituted pyrrole carbaldehydes follows the Vilsmeier–

Haack mechanism, which is the reaction between substi-

tuted amide and phosphrous–oxychloride along with an

electron-rich arene to produce aryl aldehyde or ketone

(Vilsmeier and Haack, 1927; Mallegol et al., 2005). For

formylation of aromatic compound, it is necessary to have

electron donating group either by resonance or by inductive

effect. Compounds 3a–w were synthesized using POCl₃

and DMF in a solvent-free medium at 45–110 °C for 1–4 h

to obtain improved yields of pure compounds.

All the compounds were puriﬁed by column chro-

matography and characterized by FTIR, ¹H NMR, ¹³C

NMR, mass spectrometry and elemental analysis. FTIR

spectra of compounds suggest characteristic features of all

the synthesized compounds (3a–w) that contained C=O

stretching at 1648–1715 cm^-1along with the stretching

band due to Fermi-resonance around 2800–2850 and

Results and discussion

Chemical synthesis

1

Compounds 2a–w were synthesized (Scheme 1) using the

well-known Paal–Knorr pyrrole synthesis with different

substituted anilines 1a–w and a,b-diacetyl compound

(hexane-2,5-dione) in a polar protic solvent medium.

2700–2750 cm^-1due to aldehydic group. The H NMR

and ¹³C NMR spectra showed a singlet around 9.5–10.2

and 164–185 ppm, respectively, further conﬁrming the

presence of aldehydic group. In addition, elemental

Scheme 1 Synthesis of 2,5-

dimethylsubstitutedphenyl/

benzyl-1H-pyrrole-3/4-mono/

dicarbaldehydes. Reagents and

conditions: a acetic acid, reﬂux

110–120 °C, 30 min. b DMF,

POCl₃, 2–4 h

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Med Chem Res

analysis in conjunction with mass spectra conﬁrmed the

incorporation of aldehydic group at the 3rd and 4th posi-

tions of pyrrole with the major protonated molecular ion

peak observed at their corresponding m/z value as assumed

theoretically.

with the hydrogen of Tyr158.OH amino acid as well as the

interaction with cofactor NAD1270.H21. Oxygen atom of

aldehydic group at the 3rd carbon of pyrrole (compound 3f)

showed interaction with MET68.H amino acid residue, but

aldehydic group of compound 3a did not show any inter-

action similar to that of compound 3f (Figs. 3, 4).

The C score that ranks the afﬁnity of ligands bound to

the active site of a receptor (Table 3) showed better afﬁnity

to compounds 3a, 3j, 2a, 3k, 3f and 3e (C score 8.81, 7.81,

7.70, 7.06, 6.87 and 6.40, respectively) than triclosan (C

score 6.01). Only 3w showed C score below 3 (C score

2.77) suggesting that the compounds in this study are the

better hit molecules. Compound 3a and triclosan showed

the same pattern of interaction in the active site of the

enzyme.

Antitubercular activity

The MIC values of the compounds versus selected M.

tuberculosis H₃₇Rv are given in Table 1. Antitubercular

activity was performed by Alamar Blue dye method

(Franzblau et al., 1998; Lourenco et al., 2007); standard

values for antitubercular tests were performed, and these

values are: 3.125 (Pyrazinamide), 6.25 (Streptomycin) and

3.125 lg/ml (Ciproﬂoxacin). Compounds 3a, 3b and 3k

exhibited antitubercular activity at MIC of 3.12 lg/ml.

Compounds 3a, 3b and 3k inhibited the mycobacterium

growth quite effectively compared to others in the series.

These compounds are evolved to be the most active in the

series investigated. MIC values of all other compounds are

around 6.25–50 lg/ml.

CoMFA and CoMSIA models

Data sets of the newly synthesized pyrrole carbaldehydes

were used to perform the 3D-QSAR studies, wherein all

compounds were aligned to the most active conformation

of compound 3a (Fig. 2).

Molecular modeling

Contour maps

Earlier, we have reported on the molecular docking study

of pyrrolyl hydrazones, using MMFF94 charges and found

6.18 C score for triclosan (TCL) (More et al., 2014). In the

present study, we have used Amber7FF99 for the

biopolymer and Gasteiger–Huckel charges for small

molecules to carry out the docking study; with this charge,

TCL showed 6.01 C score, but retained its interaction with

Tyr158 and cofactor NAD^?was used as a standard drug to

compare other molecules in the series. The synthesized

compounds, 3a and 3f, occupy the same binding site as that

of TCL (Fig. 3). Oxygen atom of NO₂group at the meta

position to benzene (compound 3a) showed interaction

The CoMFA contours map analysis for steric favored and

disfavored regions are shown in Fig. 5a. The giant green

contour map at the benzene ring showed increase in steric

bulk with an increase in the activity. In case of electro-

static contour map (Fig. 5b) analysis, bunch of red

counter near benzene showed the region favoring the

negatively charged substituent. In case of CoMSIA anal-

ysis, the patterns of steric and electrostatic counter map

are nearly identical (Fig. 6a, b) as observed in CoMFA.

Due to these patterns of counter map of benzene, steri-

cally favored electronegative substitution showed better

MIC, CoMFA and CoMSIA pMIC values as shown in

Tables 1 and 4 (compounds 3a, 3b and 3k with the MIC

of 3.12 lg/ml CoMFA Predicted = 5.6024, 5.5002,

5.4772 and CoMSIA Predicted = 5.5963, 5.5027, 5.4863,

respectively). In both CoMFA and CoMSIA analysis, a

yellow counter over the ortho position of benzene

(Figs. 5a, 6a) is due to dwindling in the activity of

compounds containing bulky substitution at this position

(compounds 3f, 3i, 3q, 3t and 3w). Both CoMFA and

CoMSIA analysis conﬁrmed our prediction that the size of

a pharmacophore should be lesser (Figs. 5a, 6a). Bunch of

yellow contour maps over the 3rd and 4th positions of

pyrrole (Figs. 5a, 6a) deﬁned the cause of hampering of

activity in those compounds containing 2 aldehydic

groups at the 3rd and 4th positions of pyrrole along with

the electropositive substitution at the benzene ring

(Figs. 5b, 6b) (compound 3r, MIC 50 lg/ml).

Fig. 3 Docking poses of triclosan and highly active molecules 3a

(green) and 3f (red) (Color ﬁgure online)

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Fig. 4 Docking poses of

triclosan and highly active

molecules 3a (green) and 3f

(red) showing pattern of

interaction (Color ﬁgure online)

The CoMSIA counter map analysis to understand the

effect of hydrophobic and hydrophilic descriptors on the

activity of compounds (Fig. 6c) suggested the linker to be

hydrophilic in nature. In Fig. 6d, magenta contour over the

3rd and 4th positions of benzene and the same counter map

over the 3rd position of pyrrole conﬁrmed that H-bond

acceptors at this position are favorable for the activity.

In both CoMFA and CoMSIA, a green contour map over

the substituted benzene showed the requirement of steric

bulk, favoring the activity (Figs. 5a, 6a). In the electrostatic

ﬁeld analysis (Fig. 5b), the electronegative group at the

benzene ring has boosted the activity, but in case of 3a, the

nitro group is involved in H-bonding with Tyr158.HH

(Fig. 4). Oxygen of aldehydic group at the 3rd position of

pyrrole in 3f exerts an interaction with Met 98.H amino

acid residues. In CoMFA contour map analysis (Fig. 5a),

steric bulk at the 3rd position of pyrrole showed strong

interaction with the amino acid residue. Aldehydic group at

the 3rd position of pyrrole is responsible for this additional

interaction with the enzyme that would help to improve the

anti-tuberculosis activity.

indicating that only one aldehydic group at the pyrrole

moiety favors the activity.

In this work, main aim of our study is to develop those

molecules that have better ﬁt into the enoyl-ACP receptor.

Crash score, which will be a sign of penetration of ligand to

receptor cavity showed a comparable score of -1.98 for 3j

with triclosan (-2.08) and superior score of -2.62 for

compound 3k. On the basis of Crash score of 3k as shown

in Fig. 7, one can speculate that such hit molecules may

easily get access to the active site of the enoyl-ACP

reductase enzyme. Steric clash in between enoyl-ACP

reductase enzyme cavity and triclosan due to the mutation

of glycine 93 to valin would cause the resistance of tri-

closan to E. coli (Levy et al., 1999). Such mutations in case

of either E. coli or M. tuberculosis may be handled by the

compounds evolved in this study.

Experimental section

Melting points were determined using Shital-digital pro-

grammable apparatus and are uncorrected. FTIR spectra in

KBr pellets were recorded on a Bruker FTIR spectropho-

From the receptor-based drug designing (Figs. 3, 4)

CoMFA (Fig. 5a) and CoMSIA (Fig. 6a), it can be con-

cluded that aldehyde at the 3rd position of pyrrole is

essential to increase the inhibitory potency of a drug and

the MIC value of such aldehydic compounds (at the 3rd

position of pyrrole) along with the electronegative substi-

tution at the benzene ring fall in the range 3.12–6.25 lg/ml

(except for compounds, 3g, 3h and 3i). If we try to increase

the number of aldehydic groups at the pyrrole 3rd and 4th

positions to induce better interaction with the receptor

pocket, but due to its unacceptable orientation and steric

disfavoring region in the double aldehydic compounds,

they lost their H-bonding interactions with Met 98. H

(Figs. 5a, 6a) and the MIC values increased to 50 lg/ml,

1

tometer. The H and ¹³C NMR spectra were recorded on a

Bruker AVANCE II at 400 and 100/75 MHz, respectively;

chemical shifts are expressed in parts per million (ppm)

relative to TMS. The abbreviations used to describe the

peak patterns are: (b) broad, (s) singlet, (d) doublet,

(t) triplet, (q) quartet and (m) multiplet. Some of the ¹³C

NMR spectra were recorded at Chonnam National

University, Gwangju, Korea (Courtesy of Prof. K. S.

Yang).

Mass spectra (MS) were recorded in a JEOL GCMATE

II GC-Mass spectrometer and Shimadzu QP 20105 GC-

Mass spectrometer. Elemental analysis data (performed on

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Table 3 Docking score, C score, crash value, polar area and different scores of all studied compounds

Comp. no.

C score^a

Crash^b

Polar^c

D score^d

PMF score^e

G score^f

Chem score^g

3a (template)

8.81

7.81

7.70

7.06

6.87

6.40

6.01

5.77

5.71

5.22

5.17

5.11

4.96

4.81

4.32

4.41

4.12

4.01

3.84

3.83

3.62

3.41

3.02

2.77

0.59

-1.98

-2.28

-2.62

-2.57

-2.62

-2.08

-2.72

-3.06

-3.28

-2.78

-2.81

-4.17

-4.90

-0.95

-4.09

-4.61

-3.95

-4.26

-4.48

-4.77

-4.90

-0.86

-0.85

-1.24

2.27

0.00

1.35

0.00

1.05

0.01

2.55

0.00

0.38

0.00

0.26

0.03

0.08

0.00

0.43

0.34

0.03

0.00

0.25

0.00

0.76

0.00

-218.39

-198.46

-126.65

-236.39

-232.01

-136.51

-143.32

-138.06

-130.46

-137.17

-136.09

-139.85

-158.76

-154.85

-100.64

-142.88

-149.89

-155.67

-151.19

-146.64

-147.74

-164.44

-93.47

-47.09

-32.66

-24.28

-22.89

-4.24

-140.37

-167.38

-222.66

-273.94

-144.15

-217.51

-222.35

-232.66

-208.52

-227.21

-226.20

-242.18

-284.79

-252.10

-165.71

-234.70

-279.36

-256.26

-260.02

-242.54

-233.36

-254.40

-148.45

-143.10

-146.41

-37.45

-32.10

-33.33

-34.48

-24.43

-34.96

-39.86

-31.88

-34.13

-34.31

-34.61

-32.08

-36.62

-34.62

-31.43

-36.55

-36.70

-34.37

-37.27

-36.18

-33.73

-37.40

-31.42

-31.89

-32.91

3j

2a

3k

3f

3e

TCL

3g

3c

3h

3d

3b

3t

-22.89

-29.63

-18.76

-11.49

-8.18

-11.88

-17.39

-17.23

-37.77

-62.42

-19.48

-17.57

-14.77

-21.11

-14.69

-6.18

3r

3u

3n

3s

3m

3p

3o

3l

3q

3v

3i

-25.16

-33.87

-49.44

-55.27

-89.69

3w

-95.76

a

C score (consensus score) scoring functions for ranking the afﬁnity of ligands bound to the active site of a receptor

b

Crash score revealing the inappropriate penetration into the binding site. Crash scores close to 0 are favorable. Negative numbers indicate

penetration

c

Polar indicating the contribution of the polar interactions to the total score

d

D score for charge and van der Waals interactions between the protein and the ligand (Kuntz et al., 1982)

e

PMF score indicating Helmholtz free energies of interactions for protein–ligand atom pairs (Potential of Mean Force, PMF) (Muegge and

Martin, 1999)

f

G score for hydrogen bonding, complex (ligand–protein), and internal (ligand–ligand) energies (Jones et al., 1997)

g

Chem score points for H-bonding, lipophilic contact, and rotational entropy, along with an intercept term (Eldridge et al., 1997)

Leco TruSpec CHNS Analyzer) for C, H and N fall within

0.4 % of the theoretical data. Thin-layer chromatography

(TLC) was performed on pre-coated TLC sheets of silica

gel 60 F254 (Merck, Darmstadt, Germany) visualized by

long- and short-wavelength UV lamps. Chromatographic

puriﬁcations were done on Merck aluminum oxide (70–230

mesh) and Merck silica gel (70–230 mesh).

containing 2,5-hexanedione (0.1 mol) and reﬂuxed for

45 min at 100–115 °C. The mixture was cooled and poured

slowly onto crushed ice cubes under stirring. The mixture

was ﬁltered, washed with water, dried and recrystallized

using a suitable solvent.

General procedure for synthesis of 2,5-dimethyl-

substitutedphenyl-1H-pyrrole-3-carbaldehydes 3a–k

and 3u

General procedure for synthesis of 2,5-dimethyl-

substitutedphenyl-1H-pyrrole derivatives 2a–w

Vilsmeier–Haack reagent was prepared by adding phos-

phoryl chloride (10.5 equivalent) in dimethyl formamide

(25 equivalent) at 0 °C with stirring. Then, 1 equivalent of

An equimolar quantity of different substituted aniline

(0.1 mol), 1a–w was dissolved in dry acetic acid

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˚

Fig. 5 CoMFA contour map of ﬁnal analysis with 2 A grid spacing

region where positively charged substituents are favored; red

contours indicate the regions where negatively charged substituents

are favored (Color ﬁgure online)

(compound 3f). a Steric contour map. Green contour refers to

sterically favored regions; yellow contour indicates sterically disfa-

vored areas. b Electrostatic contour map. Blue contours refer to the

˚

Fig. 6 Contour maps of ﬁnal CoMSIA analysis with 2 A grid spacing

refer to regions where hydrophilic substituents are favored; yellow

contours (1.59 level) indicate the regions where hydrophobic

substituent’s favored. d H-bond acceptor contour map, magenta

contours (0.59 level) encompass regions where hydrogen-bond donors

on the receptor are expected. Red contours (2.51 level) refer to areas

where hydrogen-bond on the receptor decrease the afﬁnity (Color

ﬁgure online)

(compound 2f). a Steric contour maps, green contours (0.07 level)

refer to sterically favored region; yellow contours (0.14 level) indicate

disfavored areas. b Blue contours (2.43 level) refer to regions where

negatively charged substituents are disfavored; red contours (10.95

level) indicate the regions where negatively charged substituent are

favored. c Hydrophobic contour maps, white contours (1.05 level)

2a–k and 2u was added to the reagent and stirred at 0 °C

for 30 min. The mixture was further stirred for 3–4 h at

100 °C (45–50 °C for 2 h in case of compound 3g). After

cooling, the mixture was diluted with cold water and

basiﬁed with 1 M NaOH solution. The separated solid was

collected, washed with water, dried and puriﬁed by col-

umn chromatography (pet. ether/chloroform/methanol

6:3:1).

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Table 4 Actual and predictive (Pred.) activities (pMIC) with residual (d) values for training and test set compounds using the 3D-QSAR model

Actual

CoMFA

Pred.

CoMSIA

Pred.

D

d

Training set compounds

3a

5.5052

5.2041

4.9031

5.2041

5.5052

5.2041

4.9031

5.2041

4.9031

4.6021

5.2041

4.9031

4.301

5.6024

5.5002

5.0300

5.2061

5.0558

5.2130

5.4772

5.1884

4.7519

4.7800

5.1073

5.0862

4.6936

4.5285

5.0169

5.1128

4.5622

4.7795

4.7716

-0.0972

0.0050

5.5963

5.5027

5.0276

5.1058

5.0483

5.2089

5.4863

5.2057

4.7567

4.7794

5.1173

5.0993

4.6751

4.5377

5.0149

5.0995

4.5495

4.7785

4.7737

-0.0911

0.0025

3b

3c

0.1741

0.1765

3f

-0.0020

-0.1527

-0.0089

0.0280

0.0983

3h

-0.1452

-0.0048

0.0189

3j

3k

3m

0.0157

-0.0016

0.1464

3n

0.1512

3o

0.1231

0.1237

3q

0.0968

0.0868

3t

-0.1831

-0.0915

0.0736

-0.1962

-0.073

0.0644

3u

3w

3e

0.1872

0.1892

3h

-0.2097

-0.2612

0.1236

-0.1964

-0.2485

0.1246

3r

3v

4.9031

4.6021

3i

-0.1695

-0.1716

Test set compounds

3d

3s

3l

5.2041

4.9031

4.6021

5.0615

5.0496

5.2885

4.7406

4.8295

0.1426

0.1545

5.0193

4.9694

5.3325

5.0324

4.4898

0.1848

0.2347

-0.0844

0.1625

-0.1284

-0.1293

0.1123

3p

3g

-0.2274

1646 (C=O), 1485 (asym NO₂), 1315 (sym NO₂) cm^-1; ¹H

NMR (CDCl₃, 400 MHz): d = 2.00 (s, 3H, pyrrole-C₅–

CH₃), 2.29 (s, 3H, pyrrole-C₂–CH₃), 6.33 (d, 1H, pyrrole-

C₄–H), 7.85–8.38 (m, 4H, phenyl-C₂, C₄, C₅, C₆–H), 9.83

(s, 1H, pyrrole-C₃–CHO); ¹³C NMR (CDCl₃, 75 MHz):

d = 11.33 (pyrrole-C₅–CH₃), 12.75 (pyrrole-C₂–CH₃),

106.91 (pyrrole-C₃and C₄), 122.53 (phenyl-C₂), 123.29

(phenyl-C₄), 123.90 (phenyl-C₆), 130.64 (phenyl-C₄),

130.68 (pyrrole-C₅), 134.17 (pyrrole-C₂), 138.17 (phenyl-

C₃), 148.87 (phenyl-C₁), 185.36 (pyrrole-C₃–CHO); MS

(ESI): m/z found 245.10 [M^?? 1]; calcd. 244.24; Anal.

Calcd. for C₁₃H₁₂N₂O₃: C, 63.93; H, 4.95; N, 11.47.

Found: C, 63.91; H, 4.94; N, 11.45.

Fig. 7 Comparison of size of pharmacophore which shows better

ﬁtting of compound 3k than triclosan in receptor cavity

2,5-Dimethyl-1-(4-nitrophenyl)-1H-pyrrole-3-

carbaldehyde (3b)

2,5-Dimethyl-1-(3-nitrophenyl)-1H-pyrrole-3-

carbaldehyde (3a)

Compound 3b was obtained as yellow solid. Yield 65 %;

M.p. 133–135 °C; IR (KBr) m_max3077, 1595, 1496 (Ar–H),

1656 (C=O), 1492 (asym NO₂), 1325 (sym NO₂) cm^-1; ¹H

NMR (CDCl₃, 400 MHz): d = 2.03 (s, 3H, pyrrole-C₅–

Compound 3a was obtained as yellow solid. Yield 70 %;

M.p. 140–142 °C; IR (KBr) m_max3084, 1530, 1482 (Ar–H),

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2,5-Dimethyl-1-(2-nitrophenyl)-1H-pyrrole-3-

carbaldehyde (3f)

CH₃), 2.32 (s, 3H, pyrrole-C₂–CH₃), 6.43 (s, 1H, pyrrole-

C₄–H), 7.41–7.45, 8.40–8.43 (m, 4H, phenyl-C₂, C₃, C₅,

C₆–H), 9.90 (s, 1H, pyrrole-C₃–CHO); MS (ESI): m/z

found 245.01 [M^?? 1]; calcd. 244.24; Anal. Calcd. for

C₁₃H₁₂N₂O₃: C, 63.93; H, 4.95; N, 11.47. Found: C, 63.91;

H, 4.93; N, 11.45.

Compound 3f was obtained as yellow solid. Yield 55 %;

M.p. 88–90 °C; IR (KBr) m_max3046, 1604, 1491 (Ar–H),

1655 (C=O), 1490 (asym NO₂), 1331 (sym NO₂) cm^-1; ¹H

NMR (CDCl₃, 400 MHz): d = 1.93 (s, 3H, pyrrole-C₅–

CH₃), 2.24 (s, 3H, pyrrole-C₂–CH₃), 6.41 (d, 1H, pyrrole-

C₄–H), 7.38–8.10 (m, 4H, phenyl-C₃, C₄, C₅, C₆–H), 9.87

(s, 1H, pyrrole-C₃–CHO); ¹³C NMR (CDCl₃, 75 MHz):

d = 10.93 (pyrrole-C₅–CH₃), 12.21 (pyrrole-C₂–CH₃),

106.78 (pyrrole-C₃and C₄), 122.67 (phenyl-C₆), 125.38

(phenyl-C₃and C₄), 130.53 (pyrrole-C₅), 131.28 (phenyl-

C₁), 133.96 (pyrrole-C₂and phenyl-C₅), 138.84 (phenyl-

C₂), 185.35 (pyrrole-C₃–CHO); MS (ESI): m/z found

245.10 [M^?? 1]; calcd. 244.24; Anal. Calcd. for

C₁₃H₁₂N₂O₃: C, 63.93; H, 4.95; N, 11.47. Found: C, 63.92;

H, 4.90; N, 11.41.

1-(4-Chlorophenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3c)

Compound 3c was obtained as dark yellow solid. Yield

72 %; M.p. 190–200 °C; IR (KBr) m_max3077, 1596, 1496

(Ar–H), 1655 (C=O), 790 (Ar–Cl) cm^-1; ¹H NMR (CDCl₃,

400 MHz): d = 1.98 (d, 3H, pyrrole-C₅–CH₃), 2.27 (s, 3H,

pyrrole-C₂–CH₃), 6.38 (d, 1H, pyrrole-C₄–H), 7.13–7.52

(m, 4H, phenyl-C₂, C₃, C₅, C₆–H), 9.87 (s, 1H, pyrrole-C₃–

CHO); MS (ESI): m/z found 234.06 [M^?? 1]; calcd.

233.69; Anal. Calcd. for C₁₃H₁₂ClNO: C, 66.81; H, 5.18;

N, 5.99. Found: C, 66.79; H, 5.10; N, 5.95.

1-(4-Methoxyphenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3g)

1-(3-Chlorophenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3d)

Compound 3g was obtained as yellow solid. Yield 82 %;

M.p. 136–138 °C; IR (KBr) m_max3056, 1608, 1466 (Ar–H),

Compound 3d was obtained as yellow solid. Yield 70 %;

M.p. 150–154 °C; IR (KBr) m_max3068, 1606, 1477 (Ar–H),

1651 (C=O), 1255 (C–O) cm^-1

;

¹H NMR (CDCl₃,

;

1668 (C=O), 786 (Ar–Cl) cm^-^{1 1}H NMR (CDCl₃,

400 MHz): d = 1.97 (s, 3H, pyrrole-C₅–CH₃), 2.27 (s, 3H,

pyrrole-C₂–CH₃), 3.88 (s, 3H, OCH₃), 6.37 (d, 1H, pyrrole-

C₄–H), 7.00–7.26 (m, 4H, phenyl-C₂, C₃, C₅, C₆–H), 9.85

(s, 1H, pyrrole-C₃–CHO); ¹³C NMR (CDCl₃, 75 MHz):

d = 11.20 (pyrrole-C₅–CH₃), 12.64 (pyrrole-C₂–CH₃),

55.56 (OCH₃), 105.51 (pyrrole-C₄), 114.70 (pyrrole-C₃),

121.74 (phenyl-C₃and C₅), 128.97 (pyrrole-C₅), 129.58

(phenyl-C₂and C₆), 131.33 (phenyl-C₁), 139.30 (pyrrole-

C₂), 159.72 (phenyl-C₄), 185.26 (pyrrole-C₃–CHO); MS

(ESI): m/z found 230.11 [M^?? 1]; calcd. 229.27; Anal.

Calcd. for C₁₄H₁₅NO₂: C, 73.34; H, 6.59; N, 6.11. Found:

C, 73.32; H, 6.55; N, 6.15.

400 MHz): d = 1.93 (s, 3H, pyrrole-C₅–CH₃), 2.23 (s, 3H,

pyrrole-C₂–CH₃), 6.41 (s, 1H, pyrrole-C₄–H), 7.26–7.78

(m, 4H, phenyl-C₂, C₄, C₅, C₆–H), 9.89 (s, 1H, pyrrole C₃–

CHO); MS (ESI): m/z 234.10 [M^?? 1], 236.02 [M^?? 2];

calcd. 233.69; Anal. Calcd. for C₁₃H₁₂ClNO: C, 66.81; H,

5.18; N, 5.99. Found: C, 66.78; H, 5.14; N, 5.97.

1-(4-Bromophenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3e)

Compound 3e was obtained as yellow solid. Yield 71 %;

M.p. 183–186 °C; IR (KBr) m_max3061, 1651, 1491 (Ar–H),

1668 (C=O), 684 (Ar–Br) cm^-1

;

¹H NMR (CDCl₃,

1-(3-Bromophenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3h)

400 MHz): d = 1.56 (s, 3H, pyrrole-C₅–CH₃), 2.30 (s, 3H,

pyrrole-C₂–CH₃), 6.30 (s, H, pyrrole-C₄–H), 7.08–7.72 (m,

4H, phenyl-C₂, C₃, C₅, C₆–H), 10.36 (s, 1H, pyrrole-C₃–

CHO); ¹³C NMR (CDCl₃, 75 MHz): d = 11.66 (pyrrole-

C₂and C₅–2CH₃), 106.50 (pyrrole-C₃and C₄), 120.51

(phenyl-C₄), 124.11 (phenyl-C₂and C₆), 129.63 (pyrrole-

C₅), 132.90 (phenyl-C₅), 133.38 (phenyl-C₃), 134.46

(pyrrole-C₂), 139.45 (phenyl-C₁), 187.22 (pyrrole-C₃–

CHO); MS (ESI): m/z found 279.10 [M^?? 1], 281

[M^?? 2]; calcd. 278.14; Anal. Calcd. for C₁₃H₁₂BrNO:

C, 56.14; H, 4.35; N, 5.04. Found: C, 56.16; H, 4.32; N,

5.02.

Compound 3h was obtained as yellow solid. Yield 68 %;

M.p. 80–82 °C; IR (KBr) m_max3061, 1651, 1491 (Ar–H),

1668 (C=O), 698 (Ar–Br) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 1.93 (s, 3H, pyrrole-C₅–CH₃), 2.23 (s, 3H,

pyrrole-C₂–CH₃), 6.41 (s, 1H, pyrrole-C₄–H), 7.26–7.78

(m, 4H, phenyl-C₂, C₄, C₅, C₆–H), 9.89 (s, 1H, pyrrole-C₃–

CHO); MS (ESI): m/z found 278.01 [M^?], 280.04

[M^?? 2]; calcd. 278.14; Anal. Calcd. for C₁₃H₁₂BrNO:

C, 56.14; H, 4.35; N, 5.04. Found: C, 56.13; H, 4.31; N,

5.00.

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Med Chem Res

found 248.08 [M^?? 1], 250.04 [M^??2]; calcd. 247.72;

Anal. Calcd. for C₁₄H₁₄ClNO: C, 67.88; H, 5.70; N, 5.65.

Found: C, 67.84; H, 5. 68; N, 5.61.

1-(2-Bromophenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3i)

Compound 3i was obtained as yellow solid. Yield 50 %;

M.p. 68–70 °C; IR (KBr) m_max3034, 1584, 1479 (Ar–H),

1-(3-Methoxyphenyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3u)

1653 (C=O), 695 (Ar–Br) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 1.93 (s, 3H, pyrrole-C₅–CH₃), 2.23 (s, 3H,

pyrrole-C₂–CH₃), 6.41 (d, H, pyrrole-C₄–H), 7.26–7.78 (m,

4H, phenyl-C₃, C₄, C₅, C₆–H), 9.89 (s, 1H, pyrrole-C₃–

CHO); ¹³C NMR (CDCl₃, 75 MHz): d = 10.93 (pyrrole-

C₅–CH₃), 12.30 (pyrrole-C₂–CH₃), 105.86 (pyrrole-C₃),

113.40 (pyrrole-C₄and phenyl-C₂), 122.12 (phenyl-C₆),

128.66 (phenyl-C₄and pyrrole-C₅), 130.09 (phenyl-C₅),

130.84 (phenyl-C₃), 133.78 (pyrrole-C₂), 139.10 (phenyl-

C₁), 185.32 (pyrrole-C₃–CHO); MS (ESI): m/z found

278.01 [M^?], 280.21 [M^?? 2]; calcd. 278.14; Anal.

Calcd. for C₁₃H₁₂BrNO: C, 56.14; H, 4.35; N, 5.04. Found:

C, 56.15; H, 4.34; N, 5.00.

Compound 3u was obtained as yellow solid. Yield 89 %;

M.p. 119–122 °C; IR (KBr) m_max3056, 1600, 1470 (Ar–H),

1668 (C=O), 1261 (C–O) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 1.92 (s, 3H, pyrrole-C₅–CH₃), 2.27 (s, 3H,

pyrrole-C₂–CH₃), 3.51 (s, 3H, OCH₃), 7.65–8.30 (m, 4H,

phenyl-C₃, C₄, C₅, C₆–H), 10.35 (s, 1H, pyrrole-C₃–CHO);

MS (ESI): m/z found 230.11 [M^?? 1]; calcd. 229.27;

Anal. Calcd. for C₁₄H₁₅NO₂: C, 73.34; H, 6.59; N, 6.11.

Found: C, 73.31; H, 6.57; N, 6.10.

General procedure for the synthesis of 2,5-

dimethylsubstitutedphenyl-1H-pyrrole-3,4-

dicarbaldehydes 3l–t and 3v–w

1-(4-Chlorobenzyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3j)

Phosphoryl chloride (25 equivalent) was added drop wise

to DMF (23 equivalent) at 0 °C and the reaction was stirred

for 1 h to which 1 equivalent of 2l–t, 2v–w was added. The

ﬁnal mixture was stirred to 100 °C for 3–4 h (45–50 °C up

to 2 h in case of 3r). Solution thus obtained was cooled and

poured in cold water. Basic workout was performed with

1 M NaOH. The separated solid was collected, washed

with water, dried and puriﬁed by column chromatography

(pet. ether/chloroform/methanol 6:3:1).

Compound 3j was obtained as yellow solid. Yield 71 %;

M.p. 78–80 °C; IR (KBr) m_max3099, 1536, 1477 (Ar–H),

1643 (C=O), 797 (Ar–Cl) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 2.12 (s, 3H, pyrrole-C₅–CH₃), 2.41 (s, 3H,

pyrrole-C₂–CH₃), 5.01 (s, 2H, benzyl-CH₂), 6.36 (s, 1H,

pyrrole-C₄–H), 6.82–7.31 (m, 4H, phenyl-C₂, C₃, C₅, C₆–

H), 9.84 (s, 1H, pyrrole-C₃–CHO); ¹³C NMR (CDCl₃,

75 MHz): d = 11.23 (pyrrole-C₅–CH₃), 12.67 (pyrrole-

C₂–CH₃), 106.16 (pyrrole-C₃and C₄), 122.11 (phenyl-C₂

and C₆), 129.31 (pyrrole-C₅), 129.90 (phenyl-C₃and C₅),

130.86 (phenyl-C₄), 135.02 (pyrrole-C₂), 138.61 (phenyl-

C₁), 185.29 (pyrrole-C₃–CHO); MS (ESI): m/z found

248.08 [M^?? 1], 250 [M^?? 2]; calcd. 247.72; Anal.

Calcd. for C₁₄H₁₄ClNO: C, 67.88; H, 5.70; N, 5.65. Found:

C, 67.82; H, 5.72; N, 5.63.

2,5-Dimethyl-1-(3-nitrophenyl)-1H-pyrrole-3,4-

dicarbaldehyde (3l)

Compound 3l was obtained as brown solid. Yield 71 %;

M.p. 148–150 °C; IR (KBr) m_max3077, 1595, 1496 (Ar–H),

1655 (C=O), 1496 (asym NO₂), 1340 (sym NO₂) cm^-1; ¹H

NMR (CDCl₃, 400 MHz): d = 2.32 (s, 6H, pyrrole-C₅,

C₂–CH₃), 7.79–8.47 (m, 4H, phenyl-C₂, C₄, C₅, C₆–H),

10.32 (s, 2H, pyrrole-C₃, C₄–CHO); MS (ESI): m/z found

273.08 [M^?? 1]; calcd. 272.25; Anal. Calcd. for

C₁₄H₁₂N₂O₄: C, 61.76; H, 4.44; N, 10.29. Found: C, 61.74;

H, 4.41; N, 10.27.

1-(3-Chlorobenzyl)-2,5-dimethyl-1H-pyrrole-3-

carbaldehyde (3k)

Compound 3k was obtained as yellow solid. Yield 65 %;

M.p. 88–90 °C; IR (KBr) m_max2920, 1594, 1475 (Ar–H),

;

1647 (C=O), 788 (Ar–Cl) cm^-^{1 1}H NMR (CDCl₃,

400 MHz): d = 2.13 (s, 3H, pyrrole-C₅–CH₃), 2.42 (s, 3H,

pyrrole-C₂–CH₃), 5.02 (s, 2H, benzyl-CH₂), 6.37 (d, 1H,

pyrrole-C₄–H), 6.73–7.26 (m, 4H, phenyl-C₂, C₄, C₅, C₆–

H), 9.85 (s, 1H, pyrrole-C₃–CHO); ¹³C NMR (CDCl₃,

75 MHz): d = 10.52 (pyrrole-C₅–CH₃), 12.18 (pyrrole-

C₂–CH₃), 106.66 (pyrrole-C₃and C₄), 121.93 (phenyl-C₂

and C₆), 125.73 (phenyl-C₄), 127.97 (pyrrole-C₅), 130.39

(phenyl-C₅), 135.12 (phenyl-C₃and pyrrole-C₂), 138.58

(phenyl-C₁), 185.19 (pyrrole-C₃–CHO); MS (ESI): m/z

2,5-Dimethyl-1-(4-nitrophenyl)-1H-pyrrole-3,4-

dicarbaldehyde (3m)

Compound 3m was obtained as brown solid. Yield 76 %;

M.p. 110 °C; IR (KBr) m_max3071.56, 1602.16, 1484.36

(Ar–H), 1672.33 (C=O), 1496.65 (asym NO₂), 1340.54

1

(sym NO₂) cm^-1; H NMR (CDCl₃, 400 MHz): d = 2.31

(s, 6H, pyrrole C₅, C₂–CH₃), 7.70–8.47 (m, 4H, phenyl-C₂,

C₃, C₅, C₆–H), 10.31 (s, 2H, pyrrole-C₃, C₄–CHO); ¹³C

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Med Chem Res

NMR (CDCl₃, 75 MHz): d = 11.73 (pyrrole-C₂and C₅–

2CH₃), 107.66 (pyrrole-C₃and C₄), 120.84 (phenyl-C₂and

C₆), 124.83 (phenyl-C₃and C₅), 134.05 (pyrrole-C₂and

C₅), 139.08 (phenyl-C₁and C₄), 187.11 (pyrrole-C₃and

C₄–2CHO); MS (ESI): m/z found 273.14 [M^?? 1]; calcd.

272.25; Anal. Calcd. for C₁₄H₁₂N₂O₄: C, 61.76; H, 4.44;

N, 10.29. Found: C, 61.74; H, 4.44; N, 10.27.

308.21 [M^?? 2]; calcd. 306.15; Anal. Calcd. for C₁₄

H₁₂BrNO₂: C, 54.92; H, 3.95; N, 4.58. Found: C, 54.92; H,

3.94; N, 4.55.

2,5-Dimethyl-1-(2-nitrophenyl)-1H-pyrrole-3,4-

dicarbaldehyde (3q)

Compound 3q was obtained as brown solid. Yield 48 %;

M.p. 85–90 °C; IR (KBr) m_max3057, 1601, 1475 (Ar–H),

1668 (C=O), 1490 (asym NO₂), 1324 (sym NO₂) cm^-1; ¹H

NMR (CDCl₃, 400 MHz): d = 2.56 (s, 6H, pyrrole-C₅,

C₂–CH₃), 7.88–8.32 (m, 4H, phenyl-C₃, C₄, C₅, C₆–H),

10.39 (s, 2H, pyrrole-C₃, C₄–CHO); MS (ESI): m/z found

273.14 [M^?? 1]; calcd. 272.25; Anal. Calcd. for

C₁₄H₁₂N₂O₄: C, 61.76; H, 4.44; N, 10.29. Found: C, 61.74;

H, 4.39; N, 10.27.

1-(4-Chlorophenyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3n)

Compound 3n was obtained as brown solid. Yield 80 %;

M.p. 112–115 °C; IR (KBr) m_max2921, 1594, 1495 (Ar–H),

;

1650 (C=O), 783 (Ar–Cl) cm^-^{1 1}H NMR (CDCl₃,

400 MHz): d = 2.30 (s, 6H, pyrrole-C₅, C₂–CH₃),

7.14–7.57 (m, 4H, phenyl-C₂, C₃, C₅, C₆–H), 10.36 (s, 2H,

pyrrole-C₃, C₄–CHO); MS (ESI): m/z found 262.06

[M^?? 1], 264.01 [M^?? 2]; calcd. 261.70; Anal. Calcd.

for C₁₄H₁₂ClNO₂: C, 64.25; H, 4.62; N, 5.35. Found: C,

64.24; H, 4.61; N, 5.31.

1-(4-Methoxyphenyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3r)

Compound 3r was obtained as brown solid. Yield 88 %;

M.p. 90–93 °C; IR (KBr) m_max3057, 1601, 1475 (Ar–H),

1-(3-Chlorophenyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3o)

1668 (C=O), 1265 (C–O) cm^-^{1 1}H NMR (CDCl₃,

;

400 MHz): d = 1.97 (s, 3H, pyrrole-C₅–CH₃), 2.27 (s, 3H,

pyrrole-C₂–CH₃), 3.88 (s, 3H, OCH₃), 7.00–7.26 (m, 4H,

phenyl-C₃, C₄, C₅, C₆–H), 9.84 (s, 2H, pyrrole-C₃, C₄–

CHO); ¹³C NMR (CDCl₃, 75 MHz): d = 11.21 (pyrrole-

C₂and C₅–2CH₃), 55.56 (OCH₃), 114.70 (pyrrole-C₃and

C₄), 121.75 (phenyl-C₃and C₅), 128.98 (phenyl-C₂and

C₆), 129.59 (phenyl-C₁), 131.31 (pyrrole-C₂and C₅),

159.72 (phenyl-C₄), 185.26 (pyrrole-C₃and C₄–2CHO);

MS (ESI): m/z found 257.01 [M^?]; calcd. 257.28; Anal.

Calcd. for C₁₅H₁₅NO₃: C, 70.02; H, 5.40; N, 5.44. Found:

C, 70.00; H, 5.41; N, 5.42.

Compound 3o was obtained as brown solid. Yield 72 %;

M.p. 177–180 °C; IR (KBr) m_max3074, 1592, 1484 (Ar–H),

1670 (C=O), 798 (Ar–Cl) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 2.31 (s, 6H, pyrrole-C₅, C₂–CH₃),

7.11–7.57 (m, 4H, phenyl-C₂, C₄, C₅, C₆–H), 10.36 (s, 2H,

pyrrole-C₃, C₄–CHO); ¹³C NMR (CDCl₃, 75 MHz):

d = 11.67 (pyrrole-C₂and C₅–2CH₃), 113.66 (pyrrole-C₃

and C₄), 120.50 (phenyl-C₂), 126.23 (phenyl-C₆), 128.23

(phenyl-C₄), 130.26 (phenyl-C₅), 131.07 (phenyl-C₃),

135.80 (pyrrole-C₂and C₅), 139.45 (phenyl-C₁), 187.24

(pyrrole-C₃and C₄–2CHO); MS (ESI): m/z found 262.06

[M^?? 1], 264.24 [M^?? 2]; calcd. 261.70; Anal. Calcd.

for C₁₄H₁₂ClNO₂: C, 64.25; H, 4.62; N, 5.35. Found: C,

64.24; H, 4.61; N, 5.31.

1-(4-Chlorobenzyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3s)

Compound 3s was obtainedas brown solid. Yield 72 %; M.p.

78–80 °C; IR (KBr) m_max3099, 1536, 1477 (Ar–H), 1643

1-(4-Bromophenyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3p)

1

(C=O), 781 (Ar–Cl) cm^-1; H NMR (CDCl₃, 400 MHz):

d = 2.12 (s, 6H, pyrrole-C₅, C₂–CH₃), 5.08 (s, 2H, benzyl-

CH₂), 7.29–7.34 (m, 4H, phenyl-C₂, C₃, C₅, C₆–H), 9.84 (s,

1H, pyrrole-C₃–CHO), 10.35 (s, 1H, pyrrole-C₄–CHO); MS

(ESI): m/z found 276.07 [M^?? 1], 278.01 [M^?? 2]; calcd.

275.73; Anal. Calcd. for C₁₅H₁₄ClNO₂: C, 65.34; H, 5.12; N,

5.08. Found: C, 65.31; H, 5.14; N, 5.05.

Compound 3p was obtained as brown solid. Yield 78 %;

M.p. 109–110 °C; IR (KBr) m_max3047, 1587, 1490 (Ar–H),

1653 (C=O), 695 (Ar–Br) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 1.98 (s, 3H, pyrrole-C₅–CH₃), 2.28 (s, 3H,

pyrrole-C₂–CH₃), 7.08–7.67 (m, 4H, phenyl-C₂, C₃, C₅,

C₆–H), 9.86 (s, 2H, pyrrole-C₃, C₄-CHO); ¹³C NMR

(CDCl₃, 75 MHz): d = 11.24 (pyrrole-C₂and C₅–2CH₃),

106.20 (pyrrole-C₃and C₄), 122.14 (phenyl-C₄), 123.03

(phenyl-C₂and C₆), 132.90 (phenyl-C₃and C₅), 136.00

(pyrrole-C₂and C₅), 138.55 (phenyl-C₁), 185.30 (pyrrole-

C₃and C₄–2CHO); MS (ESI): m/z found 306.12 [M^?],

1-(2-Chlorobenzyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3t)

Compound 3t was obtained as brown solid. Yield 68 %;

M.p. 128–130 °C; IR (KBr) m_max2917, 1584, 1479 (Ar–H),

123

Med Chem Res

Fig. 8 Pictorial presentation of

structural activity relationship

1653 (C=O), 785 (Ar–Cl) cm^-1

;

¹H NMR (CDCl₃,

(pyrrole-C₃and C₄–2CHO); MS (ESI): m/z found 306.01

[M^?], 308.21 [M^?? 2]; calcd. 306.15; Anal. Calcd. for

C₁₄H₁₂BrNO₂: C, 54.92; H, 3.95; N, 4.58. Found: C, 54.92;

H, 3.92; N, 4.54.

400 MHz): d = 2.45 (s, 6H, pyrrole-C₅, C₂–CH₃), 5.15 (s,

2H, benzyl-CH₂), 7.19–7.46 (m, 4H, phenyl-C₃, C₄, C₅,

C₆–H), 10.36 (s, 2H, pyrrole-C₃, C₄–CHO); ¹³C NMR

(CDCl₃, 75 MHz): d = 10.63 (pyrrole-C₂and C₅–2CH₃),

44.59 (CH₂), 108.00 (pyrrole-C₃and C₄), 125.81 (phenyl-

C₅), 127.79 (phenyl-C₄), 129.38 (phenyl-C₃), 129.88

(phenyl-C₆), 131.97 (pyrrole-C₂and C₅), 132.55 (phenyl-

C₂), 138.98 (phenyl-C₁), 187.14 (pyrrole-C₃and C₄–

2CHO); MS (ESI): m/z found 276.07 [M^?? 1], 278.25

[M^?? 2]; calcd. 275.73; Anal. Calcd. for C₁₅H₁₄ClNO₂:

C, 65.34; H, 5.12; N, 5.08. Found: C, 65.31; H, 5.14; N,

5.06.

1-(2-Bromophenyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3w)

Compound 3w was obtained as brown solid. Yield 60 %;

M.p. 65–68 °C; IR (KBr) m_max3001, 1600, 1474 (Ar–H),

1654 (C=O), 684 (Ar–Br) cm^-1

;

¹H NMR (CDCl₃,

400 MHz): d = 2.31 (s, 6H, pyrrole-C₅, C₂–CH₃),

7.11–7.58 (m, 4H, phenyl-C₃, C₄, C₅, C₆–H), 10.36 (s, 2H,

pyrrole-C₃, C₄–CHO); MS (ESI): m/z found 306.01 [M^?],

308.52 [M^?? 2]; calcd. 306.15; Anal. Calcd. for C₁₄

H₁₂BrNO₂: C, 54.92; H, 3.95; N, 4.58. Found: C, 54.91; H,

3.97; N, 4.57.

1-(3-Bromophenyl)-2,5-dimethyl-1H-pyrrole-3,4-

dicarbaldehyde (3v)

Compound 3v was obtained as brown solid. Yield 65 %;

M.p. 67–70 °C; IR (KBr) m_max2917, 1585, 1478 (Ar–H),

1653 (C=O), 690 (Ar–Br) cm^-1

;

¹H NMR (CDCl₃,

Biological activities

Antitubercular activity

400 MHz): d = 2.31 (d, 6H, pyrrole-C₅, C₂–CH₃),

7.15–7.72 (m, 4H, phenyl-C₂, C₄, C₅, C₆–H), 10.36 (s, 2H,

pyrrole-C₃, C₄–CHO); ¹³C NMR (CDCl₃, 75 MHz):

d = 11.68 (pyrrole-C₂and C₅–2CH₃), 113.10 (pyrrole-C₃

and C₄), 120.47 (phenyl-C₂), 123.48 (phenyl-C₆), 126.69

(phenyl-C₃), 130.85 (phenyl-C₄), 133.18 (phenyl-C₅),

136.72 (pyrrole-C₂and C₅), 139.49 (phenyl-C₁), 187.23

The MIC values were determined for 2,5-dimethyl-1-(o/m/

p-substitutedphenyl)-1H-pyrrole-3/4-carbaldehydes (3a–i,

3l–r and 3u–w), 2,5-dimethyl-1-(o/m/p-substitutedbenzyl)-

1H-pyrrole-3/4-carbaldehydes (3j–k, 3s and 3t) against M.

123

Med Chem Res

tuberculosis strain H₃₇Rv using the microplate Alamar

Blue assay (MABA) (Franzblau et al. 1998). For MIC

measurement, 200 ll of sterile deionzed water was added

to all outer perimeter wells of sterile 96-well plate to

minimize the evaporation losses of the medium during

incubation. The 96-wells plate received 100 ll of the

Middlebrook 7H9 broth, and serial dilution of compounds

were made directly on the plate. The ﬁnal drug concen-

trations tested were 100–0.2 lg/ml. Plates were covered

and sealed with paraﬁlm and incubated at 37 °C up to

5 days. Then, 25 ll of freshly prepared 1:1 mixture of

Almar Blue reagent and 10 % Tween 80 was added to the

plate and incubated for 24 h. A blue color in the well was

interpreted as no bacterial growth and pink color was

scored as growth. Table 1 reveals antitubercular activity in

terms of MIC data.

volume, total surface area from the Crash score and steric

counter map analysis, we can ﬁrmly presume that the

pharmacophores designed in this study are better ﬁt to

enoyl-ACP reductase. The 3D-QSAR studies, CoMFA and

CoMSIA models showed the high correlative and predic-

tive power. A high bootstrapped r²value along with a small

standard deviation indicated that a similar relationship

exists in all the compounds. From our work, it can be

speculated that the hit molecule 3k can serve as a better

candidate, which can be easily ﬁt into the mutant enoyl-

ACP reductase enzyme. Due to aldehydic group on pyrrole,

compound 3f is able to generate an extra interaction with

the enzyme, while other molecules retain the usual inter-

actions as that of TCL.

Acknowledgments Authors immensely thank research support

from the Board of Research in Nuclear Sciences (BRNS), Bhabha

Atomic Research Centre (BARC), Mumbai (File No. 2013/37B/17/

BRNS/0417 dated-14/05/2013). We also thank Dr. V. H. Kulkarni,

Principal and Mr. H. V. Dambal, President, S.E.T’s College of

Pharmacy, Dharwad, India for providing the facilities. The authors are

grateful to Mr. Ravindra N. Nadagir and Mr. Shrikant A. Tiwari for

their technical assistance.

Summary of structure–activity relationship

During the development of drug design concept, our main

aim was to design such type of hit molecule, which may

easily penetrate to the enoyl-ACP reductase enzyme.

Docking and 3D-QSAR models brought us closer to our

hypothesis to conclude that ﬁve-membered rings are better

choices than six-membered rings to improve antitubercular

activity. To some extent, steric bulk at the 3rd position of

pyrrole has increased the activity of compounds 3a, 3b and

3k. To increase the interaction between drug and receptor,

the orientation of aldehyde at the 3rd position of pyrrole

was very signiﬁcant (compound 3b). The 3D-QSAR study

helped us to conclude that increase in steric bulk at the 4th

position of pyrrole is responsible to cause a dip in MIC

values (compound 3l–q) and also the electropositive group

at the benzene ring connected with dialdehydic pyrrole has

decreased the antitubercular activity up to its lowest limit

(Compounds 3g, 3r and 3u). The interactions of the syn-

thesized compounds with the surrounding amino acids

involved in the receptor are depicted in the structure–ac-

tivity relationships as shown in Fig. 8.

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Design and development of pyrrole carbaldehyde: An effective pharmacophore for enoyl-ACP reductase

DOI: 10.1007/s00044-016-1517-y

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