Design and synthesis of 2,6-di(substituted phenyl)thiazolo[3,2-b]-1,2,4-triazoles as α-glucosidase and α-amylase inhibitors, co-relative Pharmacokinetics and 3D QSAR and risk analysis

Article abstract of DOI:10.1016/j.biopha.2017.07.139

Ten fused heterocyclic derivatives bearing the 2,6-di(subsituted phenyl)thiazolo[3,2-b]-1,2,4-triazoles as central rings were synthesized and structures of the compounds were established by analytical and spectral data using FTIR, EI-MS, ¹H NMR and ¹³C NMR techniques. In vitro inhibitory activities of synthesized compounds on α-amylase, α-glucosidase and α-burylcholinesterase (α-BuChE) were evaluated using a purified enzyme assays. Compound 5c demonstrated strong and selective α-amylase inhibitory activity (IC₅₀?=?1.1?μmol/g). 5?g exhibited excellent inhibition against α-glucosidase (IC₅₀?=?1.2?μmol/g) when compared with acarbose (IC₅₀?=?4.7?μmol/g) as a positive reference. Compound 5i was found to be most potent derivative against α-BuChE with the IC₅₀ of 1.5?μmol/g which was comparable to the value obtained for (4.7?μmol/g) positive control (i.e. galantamine hydrobromide). Molecular dockings of synthesized compounds into the binding sites of human pancreatic α-amylase, intestinal maltase-glucoamylase and neuronal α-butrylcholinesterase allowed to shed light on the affinity and binding mode of these novel inhibitors. Preliminary structure–activity relationship (SAR) studies were carried out to understand the relationship between molecular structural features and inhibition activities of synthesized derivatives. These data suggested that compounds 5c, 5?g and 5i are promising candidates for hitto- lead follow-up in the drug-discovery process for the treatment of Alzheimer's disease and hyperinsulinamia.

Full text of DOI:10.1016/j.biopha.2017.07.139

Biomedicine & Pharmacotherapy 94 (2017) 499–513
Available online at
ScienceDirect
www.sciencedirect.com
Design and synthesis of 2,6-di(substituted phenyl)thiazolo[3,2-b]-
1,2,4-triazoles as
a-glucosidase and a-amylase inhibitors, co-relative
Pharmacokinetics and 3D QSAR and risk analysis
a,
b
a
Pervaiz Ali Channara, Aamer Saeeda, , Fayaz Ali Larik , Sajid Rashid , Qaiser Iqbal ,
*
*
Maryam Rozib, Saima Younisb, Jamaluddin Mahara
a
Department of Chemistry, Quaid-I-Azam University, Islamabad 45320, Pakistan
National Centre for Bioinformatics, Quaid-I-Azam University, Islamabad 45320, Pakistan
b
A R T I C L E I N F O
A B S T R A C T
Article history:
Ten fused heterocyclic derivatives bearing the 2,6-di(subsituted phenyl)thiazolo[3,2-b]-1,2,4-triazoles as
central rings were synthesized and structures of the compounds were established by analytical and
spectral data using FTIR, EI-MS, 1H NMR and 13C NMR techniques. In vitro inhibitory activities of
Received 28 May 2017
Received in revised form 19 July 2017
Accepted 27 July 2017
synthesized compounds on
evaluated using a purified enzyme assays. Compound 5c demonstrated strong and selective
inhibitory activity (IC50 = 1.1 mol/g). 5 g exhibited excellent inhibition against -glucosidase (IC50
1.2 mol/g) when compared with acarbose (IC50 = 4.7 mol/g) as a positive reference. Compound 5i was
found to be most potent derivative against -BuChE with the IC50 of 1.5 mol/g which was comparable to
the value obtained for (4.7 mol/g) positive control (i.e. galantamine hydrobromide). Molecular dockings
of synthesized compounds into the binding sites of human pancreatic -amylase, intestinal maltase-
glucoamylase and neuronal -butrylcholinesterase allowed to shed light on the affinity and binding
mode of these novel inhibitors. Preliminary structure–activity relationship (SAR) studies were carried out
to understand the relationship between molecular structural features and inhibition activities of
synthesized derivatives. These data suggested that compounds 5c, 5 g and 5i are promising candidates for
hitto- lead follow-up in the drug-discovery process for the treatment of Alzheimer’s disease and
hyperinsulinamia.
a
-amylase,
a
-glucosidase and
a
-burylcholinesterase (
a
-BuChE) were
Keywords:
Thiazole
Triazolo
a
-amylase
m
a
=
m
m
Anti-diabetic
a
m
a-Glucosidase and a-amylase inhibitors
m
Butyrylcholinesterase
3D QSAR
Pharmacokinetics
Risk analysis
a
a
© 2017 Elsevier Masson SAS. All rights reserved.
1. Introduction
nucleus is unarguably one of the most significant heterocycles
found in numerous natural products and bioactive molecules [2].
Heterocyclic compounds are potentially important nuclei for
drug discovery as they can interact with diverse molecular targets
with wide range of binding interaction possibilities. They are
important building blocks in variety of areas, such as many natural
products, medicines and functional material [1]. Thiazole and
triazole motif bears sulphur and nitrogen atoms in their five
membered rings and are key structural units in many pharmaceu-
tical preparations. A scaffold bearing two fused rings of thiazole
and triazolo is a condensed heterocyclic compound with one of
two isomeric forms naming thiazolo[3,2-b][1,2,4]triazole and
thiazolo [2,3-c][1,2,4]triazole. The thiazolo [3,2-b-1,2,4]triazole
Triazole derivatives are the promising heterocycles in the field
of medicine. They are the most explored clinical entities both in
single and fused forms with other biologically active heterocycles
[3]. Most notable isomers are 1H-[1,2,4]-triazoles as they form a
part of a number of biologically active pharmaceutical products [4].
A large number of [1,2,4]-triazole derivatives exhibit antibacterial
[5–8] antifungal [9–11], antitubercular [12–14], analgesic [15–17],
anti-inflammatory [18–20], anticancer [21,22], anticonvulsant
[23–25], antiviral [26,27], antimalarial [28,29] and other activities.
In this context, thiazole derivatives also have a variety of
applications such as bacteriostatics [30–32], antibiotics [33],
antifungal [34], CNS regulants of high selling diuretics [35], local
anaesthetics [36], anti-inflammatory [37,38], analgesic and anti-
pyretics [39,40], HIV infections [41,42], anti-allergic [43], anti-
hypertensive [44], against schizophrenia [45], anti-diabetic [46],
anthelminthic [47], anticancer [48,49] and antioxidant [50,51].
* Corresponding authors.
E-mail addresses: aamersaeed@yahoo.com (A. Saeed),
fayazali@chem.qau.edu.pk (F.A. Larik).
http://dx.doi.org/10.1016/j.biopha.2017.07.139
0753-3322/© 2017 Elsevier Masson SAS. All rights reserved.

500
P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
Furthermore, the thiazole ring is also found in many potent
bioactive molecules. Meloxicam is a new NSAID with a thiazolyl
group in its structure. Some other thiazole derivatives such as
Niridazole and Ritonavir are antiulcer and antiretroviral agents.
Previously, thiazole and triazole have been reported as potent
2.2. Procedure for synthesis of thiazolo [3,2-b] [1,2,4] triazoles (5a-5j)
The aryl thiazole [3,2-b] [1,2,4] triazoles were synthesized by
refluxing 0.001 mol of the respective ethanone in 4 ml of
phosphorous oxychloride. The products were purified by recrys-
tallization from ethanol, column chromatography or TLC. The
structures of all compounds were established through EI-MS and
HNMR. Spectral data of the synthesized compounds are described
below.
a
-glucosidase inhibitors for controlling blood sugar levels in
diabetes mellitus [52]. series of 1,3-thiazoles have been
synthesized and evaluated for their anti-diabetic activity by
-amylase inhibition assay and few triazole compounds exhibited
a reversible inhibition of the competitive and non-competitive
types for both -glucosidase and -amylase [53,54]. Triazole-
containing berberine derivatives were inhibitors of both acetyl-
cholinesterase (AChE) and butyrylcholinesterase ( -BuChE) and
A
a
6-(4-bromophenyl)-2-(3-chlorophenyl) thiazolo [3,2-b]
[1,2,4]triazole (5a)
a
a
a
most of the compounds exhibiting AChE inhibition consisted of
heterocyclic ring systems such as 1,2,4-triazole [55–57].
white crystalline solid; yield; 60%; m.p:
In view of above facts, the fused thiazolo[3,2-b]1,2,4-triazoles
are interesting classes of compounds possessing broad spectrum of
biological activities, such as antimicrobial [58,59], anticancer [60],
anti-inflammatory [61], antipyretic [62] and analgesic as well as
antihypertensive actions. However, their inhibition action against
225–228 ꢁC; Rf; 0.69 (n-hexane:ethylacetate, 8:2); FTIR (neat,
cmꢂ1); 3094 (Csp2-H), 1425 (C
¼
N), 1578 (C
8.10-8.12 (m,1H, Ar-H), 7.90-8.04 (m,1H,
Ar-H), 7.93-7.96 (m,1H, Ar-H), 7.56-7.63 (m, 3H, Ar-H), 7.26-7.34 (m,
2H, Ar-H); 6.9 (s, 1H) 13C NMR (75 MHz, DMSO):
161.57, 139.52,
¼
C), 1501 (C
¼
C); 1H
NMR (300 MHz, DMSO):
d
human starch digesting enzymes and a-BuChE for the treatment of
d
type II diabetes and Alzheimer’s disease has not been investigated
yet. Our recent study proved for the first time that thiazolo[3,2-b]
[1,2,4]-triazoles derivatives demonstrate significant inhibitory
136.97,133.16,131.64,131.28,129.42,129.34,129.33,128.84,126.34,
122.76, 120.96, 118 Anal. Calcd. For C16H9BrClN3S: C, 49.19, H, 2.32,
N, 10.76, S, 8.21 found: C, 50.48, H, 3.1, N, 11.8, S, 9.1. Found: 388.94
2-(4-nitrophenyl)-6-(m-tolyl) thiazolo [3,2-b] [1,2,4]triazole
(5b)
action against human pancreatic
-glucosidase (N-terminal maltase-glucoamylase abbreviated as
N-MGAM) and neuronal -BuChE.
a-amylase and intestinal
a
a
To this extent, several new condensed heterocyclic compounds
with phenyl moiety and bridgehead nitrogen from thiazolo [3,2-
b] [1,2,4] triazole class were designed and evaluated for their
inhibition potential in suppressing hyderglycemia and Alz-
heimer’s disease in present study. Previously reported these type
of compounds were exploited for uni target bioevaluation but
herein, we have explored the multi-target biological potential of
title compounds. Thiazole and triazole are well recognized
medicinally active heterocyclic units and this prompted us to
design molecules based on these two motifs and seek their multi-
target biological potential. Molecular docking studies were
performed to define the models for comprehension of binding
interactions and to delineate the binding affinity of the molecules
in the active sites of target proteins. To a step further, quantitative
structure-activity relationship (QSAR) correlated molecular
properties with antidiabetic and anticholinesterase activities of
the synthesized compounds.
yellow crystalline solid; yield; 70%;
m.p: 235–238 ꢁC; Rf; 0.51 (n-hexane: ethylacetate, 8:2); FTIR (neat,
cmꢂ1); 3084 (Csp2ꢂꢂH), 1435 (C
¼
N), 1570 (C
¼
C), 1520 (C
C); 1H
¼
NMR (300 MHz, DMSO): d 8.10-8.12 (m,1H, Ar-H), 7.90-8.04 (m,1H,
Ar-H), 7.93-7.96 (m,1H, Ar-H), 7.56-7.63 (m, 3H, Ar-H), 7.26-7.34 (m,
2H, Ar-H), 6.8 (s,1H),2.34 (s, 3H, CH3); 13C NMR (75 MHz, DMSO):
d
161.57, 139.52, 136.97, 133.16, 131.64, 131.28, 129.42, 129.34, 129.33,
128.84, 126.34, 122.76, 120.96, 119, 30 Anal. Calcd. For
17H12N4O2S: C, 60.70, H, 3.60, N, 16.66, S, 9.53 found: C, 61.48,
H, 3.9, N, 17.8, S, 10.2 Found: 336.07
6-(3-nitrophenyl)-2-(m-tolyl) thiazolo [3,2-b] [1,2,4]triazole
(5c)
C
brown crystalline solid; yield; 75%; m.p:
2. Methods and materials
2.1. Chemistry
240 ꢁC; Rf; 0.54 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
3073 (Csp2-H), 1430 (C
(300 MHz, DMSO): 8.12-8.15 (m, 1H, Ar-H), 7.80-8.08 (m, 1H, Ar-
H), 7.93-7.96 (m,1H, Ar-H), 7.56-7.63 (m, 3H, Ar-H), 7.26-7.34 (m,
2H, Ar-H), 6.6 (s,1H), 2.37 (s, 3H, CH3); 13C NMR (75 MHz, DMSO):
¼
N), 1575 (C
¼
C), 1525 (C
¼
C); 1H NMR
Commercially available reagents and solvents, purchased from
Merck and Sigma Aldrich, were dried and distilled according to
standard procedures prior to use. Melting points were determined
using a digital Gallenkamp (SANYO) model MPD.BM 3.5 apparatus
and are uncorrected. FTIR spectra were recorded with tetrame-
thylsilane as internal standard using Bio-Rad-Excalibur Series
Mode FTS 3000 MX spectrophotometer. NMR spectra were
obtained with AVANCE AV 300 MHZ spectrometers using DMSO
and acetone as solvent for accurate NMR analysis. TMS was used as
internal standard. The Finnegan MAT-311A spectrometer was used
for electron impact mass spectra (EI-MS) analysis. An internal
standard cesium iodide (CsI) was used for mass measurement.
Column chromatography was performed using silica gel (E. Merck,
type 60, 70–230 mesh). Pre-coated silica gel aluminum plates
(Kieselgel 60, 20 ꢀ 20 and 0.5 mm thick, E. Merck, Germany) were
used for TLC analysis. Light of wavelength 254 and 365 nm were
used to visualize the chromatogram.
d
d
164.57, 140.52, 134.97, 133.18, 131.84, 131.28,129.42, 129.34, 129.33,
128.84, 126.34, 122.76, 120.96, 119, 28 Anal. Calcd. For
C17H12N4O2S: C, 60.70, H, 3.60, N, 16.66, S, 9.53 found: C, 61.48,
H, 3.9, N, 17.8, S, 10.2 found: 336.07
6-(4-chlorophenyl)-2-(4-fluorophenyl)
[1,2,4]triazole (5d)
thiazolo
[3,2-b]
pink crystalline solid; yield; 78%; m.p:
243 ꢁC; Rf; 0.44 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
3077 (Csp2ꢂꢂH), 1433 (C
¼
N), 1573 (C
¼
C), 1528 (C
C); 1H NMR
¼

P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
501
(300 MHz, DMSO):
8.08 (m, 1H, Ar-H), 7.90-7.98 (m,1H, Ar-H), 7.52-7.65 (m, 3H, Ar-H),
7.23-7.34 (m, 2H, Ar-H) 6.7 (s,1H); 13C NMR (75 MHz, DMSO):
d
8.15 (s, 1H, SCH), 8.14-8.18 (m, 1H, Ar-H), 7.70-
2H, Ar-H); 6.9 (s, 1H), 2.32 (s, 3H);13C NMR (75 MHz, DMSO):
d
168.57, 142.52, 136.97, 134.18,131.84,131.28,129.42, 129.34, 129.33,
128.84, 126.34, 122.76, 120.96, 119,29. Anal. Calcd. For
d
C
18H14BrN3S: C, 56.27, H, 3.67, N, 10.93, S, 8.34 found: C, 57.35,
168.57, 142.52,136.97,134.18,131.84,131.28,129.42, 129.34, 129.33,
128.84, 126.34, 122.76, 120.96, 119. Anal. Calcd. For C16H9ClFN3S: C,
58.27, H, 2.70, N, 12.74, S, 9.73 found: C, 59.48, H, 2.9, N, 12.8, S, 9.9
found: 329.07
H, 3.4, N, 11.23, S, 8.57 found: 384.29
6-(4-chlorophenyl)-2-(4-methoxy-3-methylphenyl) thiazolo
[3,2-b] [1,2,4]triazole (5i)
6-(4-chlorophenyl)-2-(3, 4, 5-trimethoxyphenyl) thiazolo
[3,2-b] [1,2,4]triazole (5e)
white crystalline solid; yield; 78%; m.p:
yellow crystalline solid; yield; 88%; m.p:
220 ꢁC; Rf; 0.74 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
3073 (Csp2ꢂꢂH), 1439 (C
¼
N), 1573 (C
¼
C), 1528 (C
C); 1H NMR
¼
(300 MHz, DMSO): 8.25-8.49 (m, 1H, Ar-H), 7.74-8.12 (m, 1H, Ar-
d
247 ꢁC; Rf; 0.74 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
H), 7.92-7.98 (m,1H, Ar-H), 7.55-7.69 (m, 3H, Ar-H), 7.25-7.38 (m,
C); 1H NMR
2H, Ar-H); 6.9 (s, 1H),3.4 (s,3H), 2.32 (s, 3H);13C NMR (75 MHz,
3079 (Csp2ꢂꢂH), 1445 (C
(300 MHz, DMSO): 8.44-8.58 (m, 1H, Ar-H), 7.70-8.08 (m, 1H, Ar-
H), 7.90-7.98 (m,1H, Ar-H), 7.52-7.65 (m, 3H, Ar-H), 7.23-7.34 (m,
2H, Ar-H),6.5 (s, 1H), 3.33 (s, 9H, CH3); 13C NMR (75 MHz, DMSO):
¼
N), 1579 (C
¼
C), 1538 (C
¼
d
DMSO):
129.33, 128.84, 126.34, 122.76, 120.96, 119,53,29. Anal. Calcd. For
C18H14ClN3OS: C, 60.76, H, 3.97, N, 11.81, S, 9.01 found: C, 61.35, H,
d 164.57, 144.52, 137.97, 135.18, 132.84, 130.28, 129.34,
d
168.57, 142.52,136.97,134.18,131.84,131.28,129.42, 129.34, 129.33,
128.84, 126.34, 122.76, 120.96, 119, 55. Anal. Calcd. For C19H16Cl
N3O3S: C, 58.27, H, 2.70, N, 12.74, S, 9.73 found: C, 59.48, H, 2.9, N,
12.8, S, 9.9 found: 329.07
3.79, N, 11.81, S, 9.01 found: 355.29
2-phenyl-6-(3, 4, 5-trimethoxyphenyl) thiazolo [3,2-b]
[1,2,4]triazole (5j)
6-(4-bromophenyl)-2-(3-fluorophenyl)
thiazolo
[3,2-b]
[1,2,4]triazole (5f)
white crystalline solid; yield; 74%; m.p:
210 ꢁC; Rf; 0.64 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
yellow crystalline solid; yield; 81%; m.p:
3078 (Csp2ꢂꢂH), 1447 (C
(300 MHz, DMSO): 8.35-8.49 (m, 1H, Ar-H), 7.74-8.12 (m, 1H, Ar-
H), 7.92-7.98 (m,1H, Ar-H), 7.55-7.69 (m, 3H, Ar-H), 7.25-7.38 (m,
2H, Ar-H); 6.9 (s,1H),3.4 (s,9H);13C NMR (75 MHz, DMSO):
164.57,
¼
N), 1578 (C
¼
C), 1538 (C
¼
C); 1H NMR
d
229 ꢁC; Rf; 0.54 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
3066 (Csp2ꢂꢂH), 1434 (C
(300 MHz, DMSO): 8.25-8.39 (m, 1H, Ar-H), 7.70-8.08 (m, 1H, Ar-
H), 7.92-7.98 (m,1H, Ar-H), 7.55-7.69 (m, 3H, Ar-H), 7.25-7.38 (m,
2H, Ar-H) 6.5 (s, 1H);13C NMR (75 MHz, DMSO):
168.57, 142.52,
¼
N), 1563 (C
¼
C), 1522 (C
¼
C); 1H NMR
d
d
144.52, 137.97, 135.18, 132.84, 130.28, 129.34, 129.33, 128.84,
126.34, 122.76, 120.96, 119,53,29. Anal. Calcd. For C19H17N3O3S:
C, 62.27, H, 4.67, N, 11.44, S, 8.73 found: C, 62.35, H, 4.8, N, 11.57, S,
8.57 found: 367.10
d
136.97,134.18,131.84,131.28,129.42,129.34,129.33,128.84,126.34,
122.76, 120.96, 119. Anal. Calcd. For C16H9BrFN3S: C, 51.27, H, 2.42,
N,11.23, S, 8.57 found: C, 51.35, H, 2.4, N,11.23, S, 8.57 found: 374.97
6-(3-bromophenyl)-2-(4-chlorophenyl) thiazolo [3,2-b]
[1,2,4] triazole (5 g)
2.3. Biological assays
2.3.1.
The compounds were tested for their enzyme inhibition activity
against -amylase by the previously reported method. For assay
l of the extract with the final concentration of 200, 100 and
g/ml was mixed with 40 l of starch (0.05%) and 30 l of
potassium phosphate buffer (pH 6.8) in 96-well micro titer plate
followed by the addition of 10 l of -amylase enzyme (0.2 U/
a-Amylase assay
a
yellow crystalline solid; yield; 88%;
5
m
50
m
m
m
m.p: 232 ꢁC; Rf; 0.46 (n-hexane: ethylacetate, 8:2); FTIR (neat,
m
a
cmꢂ1); 3073 (Csp2ꢂꢂH), 1439 (C
¼
N), 1573 (C
¼
C), 1528 (C
C); 1H
¼
well). Standard drug Acarbose and DMSO were used as positive and
negative controls respectively. The plates were incubated for
NMR (300 MHz, DMSO): d 8.14-8.18 (m,1H, Ar-H), 7.70-8.08 (m,1H,
Ar-H), 7.90-7.98 (m,1H, Ar-H), 7.52-7.65 (m, 3H, Ar-H), 7.23-7.34 (m,
30 min at 50 ꢁC and 20
Then100
m
l HCl (1 M) as stopping reagent was added.
2H, Ar-H),6.8(s, 1H); 13C NMR (75 MHz, DMSO):
d
166.57, 141.52,
m
l of iodine reagent (5 mM KI and 5 mM I2) was added to
137.97,135.18,132.84,130.28,128.42,127.34,126.33,125.84,123.34,
122.76,120.96,119. Anal. Calcd. For C16H9BrClN3S: C, 49.19, H, 2.32,
N, 10.23, S, 8.21 found: C, 49.35, H, 2.34, N, 10.76, S, 8.21 found:
390.97
6-(3-bromophenyl)-2-(3, 4-dimethylphenyl) thiazolo [3,2-b]
[1,2,4] triazole (5 h)
check the presence and absence of starch and absorbance was
measured at 540 nm with microplate reader (Bio Tek, Elx800). The
experiments were performed in triplicate and IC50 was calculated
with Graph pad Prism 5.
2.3.2. Butyrylcholinesterase assay
Ellman’s method was used to determine the enzyme inhibition
potential of compounds against butyryl cholinestrase (BuChE) [31].
In experiment butyrylthiocholine iodide (BuChI) was used as
substrates and assay was performed in triplicate in 96-well plates.
white crystalline solid; yield; 84%; m.p:
247 ꢁC; Rf; 0.54 (n-hexane: ethylacetate, 8:2); FTIR (neat, cmꢂ1);
The compound (5
m
l) with final concentration of 200, 100 and
l of 100 M sodium phosphate
l BuChE enzyme (0.05U/ml). Then 10
l DTNB (3 mM) was added. Galantamine
50 g/ml was mixed with 20
m
m
m
3073 (Csp2ꢂꢂH), 1439 (C
(300 MHz, DMSO): 8.24-8.38 (m, 1H, Ar-H), 7.70-8.08 (m, 1H, Ar-
H), 7.92-7.98 (m,1H, Ar-H), 7.55-7.69 (m, 3H, Ar-H), 7.25-7.38 (m,
¼
N), 1573 (C
¼
C), 1528 (C
¼
C); 1H NMR
buffer (pH 8.0) and 5
BuChI (4 mM) and 60
m
m
ml
d

502
P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
hydrobromide (Sigma) and DMSO served as a positive and negative
control respectively. The reaction mixtures were then incubated
for 30 min at 37 ꢁC. After incubation absorbance was measured at
405 nm using a microplate reader (Bio Tek Elx-800, USA) and IC50
values were recorded using Graph pad Prism 5.
retrieved through online interfaces of ChemAxon’s Chemicalize
[68], Swiss ADME [69] and Molinspiration [70]. Furthermore,
optimized molecular structures were imported into standalone
Padel-descriptor software and 1445 diverse descriptors (spatial,
constitutional, geometrical, electronic, topological counts of
chemical substructures and electrotopological state etc.) for each
molecule were calculated [71].
2.3.3.
-Glucosidase enzyme inhibition assay was performed accord-
ing to the previously reported method. For experiment 25 l p-
nitrophenyl- -glucopyranoside, 65 l phosphate buffer (pH 6.8)
and 5 -glucosidase enzyme (0.05U/mL) were mixed in 96-well
microtiter plate. 5 l compound with final concentration 500, 250
and 125 g/ml was added in respective wells. Acarbose and DMSO
a-Glucosidase assay
a
m
2.5.2. Model development and validation
a
-D
m
Collected variables with larger values of negative or positive
correlation (greater than 0.70 and smaller than ꢂ0.50) were
considered and methods such as forward selection, backward
elimination and stepwise selection were performed to screen the
significant molecular descriptors, as done in our previous study
(Tegginamath et al., 2011). Subsequent to exclusion of non-
significant parameters, multiple regression analysis in IBM
statistical package for social sciences (SPSS) version 22 was used
to create regression models for predicting inhibition activity
ml a
m
m
were used as positive and negative controls respectively. Plates
were incubated at 37 ꢁC for 30 min, followed by the addition of
0.5 mM sodium bicarbonate (100 ml) as stopping agent. Absor-
bance was measured at 405 nm using microplate reader (BioTek
Elx-800, USA) and IC50 values were calculated using Graph pad
Prism 5.
against a-amylase, a-BuChE and mammalian a-glucosidase. Cross
validation for each model was carried out by inputting descriptor
values of the compounds in respective QSAR equations and by
comparing expected IC50 values from QSAR model with those
obtained from the experimental essays [72].
2.4. Molecular docking studies
The X-ray crystal structures of human maltase-glucoamylase
(MGAM) for N-terminal domain (PDB code: 3L4Z), human
a
-BuChE (PDB ID: 1P0I) and
a-amylase (PDB code: 1B2Y) were
2.6. Pharmacokinetics properties and ADMET analysis
downloaded from Protein Data Bank and processed subsequently
prior to docking. All the water molecules were removed whereas
kollman charges, missing residues and essential polar hydrogen
atoms were added by the AutoDock tools (Ver 4.2) [63]. Two
dimensional structures of synthesized compounds, acarbose
(Chembl ID: 1566) and galantamine hydrobromide (Chembl ID:
659) were sketched in ChemDraw [64] and followed by geometry
minimization in LigandScout [65]. Mol files of compounds were
converted to PDB coordinate files using OpenBabel [66].
Most of the drugs in discovery process fail to cross clinical trials
because of poor Pharmacokinetics (PK). PK determines human
therapeutic use of compounds and depends to absorption,
distribution, metabolism, excretion, and toxicity (ADMET) proper-
ties of compounds under consideration [73,74]. These properties
correlate well with pharmacokinetic properties such as molecular
weight, TPSA, permeability, octanol-water coefficient (logP) etc.
Likewise, 90% of orally active compounds follows Lipinski’s rule of
five [75]. These ADMET (Absorption, Distribution, Metabolism,
Excretion and Toxicity) were predicted through Toxicity checker
and Lazar toxicity server to hypothetically measure the positive
and negative biological effects of compounds [76,77]. Toxicity
parameters such as mutagenic and tumorigenic effects along with
drug-likeness values were evaluated through OSIRIS Data Warrior
and Chem Axon’s Chemicalize which were then later cross checked
for compliance with their standard ranges [78,79].
To access the lipophilicity of predicted hits, cLogP (activity/size)
values were predicted using ORSIS Data Warrior and compared
with pIC50 values. Ligand efficiency (LE) and lipophilic efficiency
(LipE or LLE) profiles of inhibitors were used to identify the hits
with higher activities using Equation 1 and 2 [80,81]. Ligand
efficiency indices give an indication of the binding energy per
heavy atom and better identify potential drug candidates.
Grid box of 66 * 52 * 82 points was used for
a-amylase with a
spacing 1.0 Å and the grid box center was put on x = ꢂ1.617,
y = ꢂ10.665, and z = ꢂ28.351.
a-BuChE was enclosed in a 70 * 64 *
74 grid box having 1.0ꢁA spacing and 137.90, 122.76 and 38.68 as
x, and y and z centres. A grid map of 68* 58 * 62 points in x, y, and
z directions were centered on the NMGAM with a spacing of
1.0ꢁA.
The Lamarckian genetic algorithm (LGA) was applied with the
following parameters: initial population of 100 randomly placed
individuals, a maximum number of 27,000 generations, a mutation
rate of 0.02, 2.5 ꢀ106 energy evaluations and a cross over rate of
0.80, while remaining docking parameters were set to default. The
ligands were allowed to move within the target proteins to achieve
the lowest energy conformations and the number of runs for each
docking procedure was set to 100. Dockings of all the synthesized
compounds and control drugs (Acarbose and galantamine
ꢀ
ꢁ
1:37
HA
hydribromide) with
a-amylase, a-BuChE and NMGAM were
LE ¼
ꢃ pIC50
ð1Þ
performed in AutoDock Vina 1.5.6 and most energetically favored
orientations were selected for subsequent analysis. Best docked
poses in each docking experiment were subjected to LigPlot
analysis to visualize receptor-ligand hydrophobic contacts and
hydrogen bonded interactions [67].
LipE = pIC50 ꢂ clogP
(2)
Due to variability in heavy atom counts of the ligands, LE values
were subsequently scaled as described by [83] to retrieve size-
independent ligand efficiency values (LEScale). This was achieved
by fitting the top LE values versus heavy atom counts to a simple
exponential function (Eq. (3)), as outlined by [82]. Subsequently,
“Fit Quality” or “FQ” scoring function (Eq. (4)) was computed to
detect the optimal ligand binding properties of synthesized
compounds through the ratio of LE and LEScale.
2.5. QSAR model generation
2.5.1. Molecular structural parameters selection
The compounds in our study were classified in decoy and active
datasets based on their strong to weak inhibitory potential against
a
-amylase, a-BuChE and a-glucosidase. Later on, their diverse
HA
LEScale = 0.104 + 0.65eꢂ0.037*
(3)
(4)
molecular properties were assessed to build a preliminary QSAR
models. 2D and 3D structural and physiochemical descriptors that
describe electronic and steric properties of compounds were
FQ = LE/LEScale

P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
503
Table 1
Yield of each step.
3. Results and discussion
3.1. Synthesis of compounds
Compound
2a-e
3a-e
4a-e
5a-e
Ethanones
5a-j
Step
Yield
1st
97%
92%
91%
90%
89%
The synthesis of two heterocycles fused together attached with
aromatic rings was carried by using Fischer esterification reaction
as the starting conversion from carboxylic acids into corresponding
esters and followed by routine transformations for the 5-exo-trig
cyclization POCl3 was the reagent selected [33]. Compounds were
synthesized in good to better yields (Fig. 1) and the yield of each
step is included in Table 1.
Compound 5a bears two different halogen atoms on different
phenyl rings and was obtained in minimum yield of 60% compared
to other derivatives. Compound 5e was obtained in excellent yield
of 88% and this was maximum yield compared to any other
compound. Overall, this is a multistep synthetic route and all the
steps involved in this synthetic outline are clean and high yielding.
Products showed single spot on the TLC plates and there was no
any prerequisite of using column chromatography to separate the
products.
2nd
3rd
4th
5th
6th
88ꢂ60%
with electron donating or electron withdrawing groups. The
downfield absorption of OꢂꢂCH3 carbon relative to methyl carbon
can be attributed to electronegativity effect exerted by oxygen
atom in the case of the latter.
3.2. Biological activities
The synthesized compounds were subjected to three different
activities. All the compounds showed great inhibition against three
enzymes and
a-amylase, a-glucosidase and BuChE. In case of
The compounds were fully characterized by physical techni-
ques. The synthesis of new triazole fused thiazoles was indicated in
the FTIR spectra by the presence of two strong peaks between
3078 cmꢂ1 that was assigned to sp2 CꢂꢂH and 1560 cmꢂ1(indicat-
a-amylase, selected compounds exhibited higher inhibition
potential than acarbose. Particularly, compound 5c was the most
active compound in the series due to presence of nitro group at the
meta position which enhanced charge separation by pulling
electron density from the ring (Fig. 2). Moreover, its methyl group
at meta position resulted in the donation of electron density
through no-bond resonance. The compounds showed significant
ing presence of aromatic ring) and the absorption bands for C N
¼
appeared at 1470 cmꢂ1. The synthesis of compounds was further
confirmed by 1H NMR spectra. The protons in the vicinity of
electron withdrawing groups (NO2, F) appeared more deshielded
(8.4 ppm) compared to the electron donating groups (7.5 ppm)
(OMe, Me). In the aromatic part of the spectrum multiplet were
observed for monosubstituted rings and doublets of doublets were
observed for para-substituted rings. The methyl groups appeared
at 2.34 ppm which is consistent with their environment being
directly attached with aromatic ring. The 13C NMR spectra
demonstrated that ipso carbons were found relatively deshielded
and the same electronic effect was observed for carbons attached
inhibition against
a-glucosidase enzyme, and derivative 5 g was
found to be the most potent compound in the series due to
possession of halogen atoms at aryl rings (Fig. 2). 5 g contains
bromine atom at meta position and chlorine atom at the para
position. However, few derivatives were found potent against
butyrylcholinesterase enzyme and compound 5i showed better
results in the series (Fig. 2). 5i contained chloro group at the para
position of one aryl ring and the other aryl ring was substituted
Fig. 1. Synthetic route to 6-Phenyl substituted thiazolo [3,2-b-1,2,4]-triazoles (5a-5j).

504
P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
Fig. 2. Binding energy scores of docked complexes vs IC50 values of compounds from inhibition essays. A) BuChE, B) maltase-glucoamylase and C)
a-amylase. Synthesized
compounds are indicated in triangular data labels in following colors: 5a, Yellow; 5b, Magenta; 5c, Dark blue; 5d, Light blue; 5e, Orange; 5f, Purple; 5 g, Red; 5 h, Firebrick; 5i,
Dark Green and 5j, Light green. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).
with methoxy and methyl group. Inhibitory activities of synthe-
sized compounds for -glucosidase, butrylcholinesterase and
-amylase are presented in Table 2.
association with docked ligand. The detailed residual contributions
of individual complexes were shown in Table 3. Generally,
a
a
structural insights of inhibitor binding to
and -glucosidase revealed predominant contributions of hydro-
phobic residues lying in the periphery of active sites.
a-amylase, a-BuChE
a
3.3. Molecular docking analysis
Comparative docking analysis of minimized protein structures
3.3.1. Molecular docking study on a-amylase
were performed with human
a
-amylase,
a
-BuChE and human
All the thiazolo[3,2-b]-1,2,4-triazole derivatives clustered
inside the active site in a deep depression near the center of
a
-glucosidase (N-terminal intestinal maltase-glucoamylase). Each
ligand-receptor complex was subjected to careful analysis for ideal
docked poses on the basis of least binding energy scores and
maximum number of cluster conformations. Binding energy values
of stable docked conformations were shown in Table 3. Positioning
a-amylase (Fig. 3). Side chains of Asp165, Asp197, Lys200, Glu233,
Asp300 and a number of aromatic or non-polar residues including
Trp58, Trp59, Tyr62, His101, Pro163, Ile235, His299 and His305
residues were actively engaged in association with tested
compounds as indicated in Fig. 3 [83,84].
of ligands onto the surface of
a-amylase, a-BuChE and maltase-
glucoamylase were keenly monitored to explore the binding
pocket dynamics and residual contributions of each protein in
Strong inhibitory activity of human a-amylase relies on the
formation of hydrogen bonds between the hydroxyl (OH) groups of
individual ligand and carboxylic acid side chains of binding cleft
residues (Asp197, Glu233 and Asp300). Moreover, the conjugated
Table 2
p
-system between Trp59 and Tyr62 indoles and heterocyclic rings
of ligands also contributes in binding, as described elsewhere
[85,86]. 9 out of 10 ligands constituted efficient interactions
Concentrations of the synthesized chemical derivatives for effectively inhibiting
a
-Amylase, Butrylcholinesterase and
a- Glucosidase are given as IC50 values. These
scores are received from biological assays described in Section 2.3.
p-p
with the aromatic side chains of Trp59 and Tyr62, while
hydrophobic interactions with the binding site residues (Asp197,
Glu233 and Asp300) were noticed in 8, 6 and 7 complexes,
respectively (Table). These data indicated the strong inhibitory
potential of compounds in current study.
Involvement of hydrogen bonding with the residues of catalytic
center (i.e with Gln63 and Asp305 respectively) was witnessed in
case of 5c and 5j. Paramount significance of Gln63 in the inhibition
mechanism was evident by its prominent contribution in making
hydrophobic contacts with all the least energy scoring compounds
(5b, 5e, 5 h and 5j). Furthermore, hydrogen bonding between
Compounds
a
-Amylase IC50 Butrylcholinesterase
a
(mM)
- Glucosidase IC50
(m
M)
IC50
(m
M)
5a
5b
5c
5d
5e
5f
5g
5h
5.5
6.4
1.1
7.2
5.3
3.2
4.7
6.3
8.3
9.6
17.4
–
2.2
1.9
5.3
4.2
7.3
9.4
7.4
1.8
1.5
7.6
–
7.6
8.8
2.7
3.8
3.6
6.9
1.6
9.8
1.8
7.8
4.7
–
5i
5j
Acarbose
Galantamine
Bromide
Gln63 and 5c may be responsible for lowest IC50 value (1.5
in -amylase inhibition assay.
mmol/g)
4.7
a

P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
505
Table 3
Binding energy profiles of
a-amylase,
a-BuChE and
a-glucosidase with 5a-5 j inhibitors. H-bonded residues are indicated in bold.
Ligands
a-amylase
a-BuChE Maltase-glycoamylase
Binding
Energy
Binding residues
Binding
Energy
Binding residues
Binding
Energy
Binding residues
(kcal/mol)
(kcal/mol)
(kcal/mol)
5a
5b
ꢂ8.4
ꢂ9.2
Leu162, Thr163, Asp197, Ala198,
Lys200, His201, Glu233, Ile235
Trp58, Trp59, Tyr62, Gln63,
ꢂ7.9
Phe227, Asn228, Pro303, Asp304, Glu404, ꢂ7.5
Asn212, Leu213, Tyr214, Glu446,
Ser448, Lys480, His497, Asn498
Asn212, Leu213, Tyr214, Gly215,
Ala216, Met241, Glu446, Ser448,
Leu477, Lys480, His497, Asn498
Asn212, Leu213, Gly215, Ala216,
Ala240, Met241, Glu446, Ile472,
Leu477, Lys480, His497, Asn498
Asn212, Leu213, Tyr214, Gly215,
Trp522, Thr523
ꢂ10.0
Asp70, Trp82, Gly115, Gly116, Glu197,
Pro285, Ala328, Phe329, Tyr332, Met437,
His438, Gly439, Tyr440
Asp70, Trp82, Gly115, Tyr128, Glu197,
Pro285, Ala328, Phe329, Tyr332, Trp430
ꢂ8.7
ꢂ8.4
ꢂ8.2
Gly104, Val107, Asp197, Asp300
5c
5d
5e
5f
ꢂ9.3
ꢂ8.6
ꢂ9.2
ꢂ8.6
ꢂ8.8
Trp59, Tyr62, Gln63, Tyr151,
Leu162, Asp197, His201, Glu233,
Ile235, His305
Trp58, Trp59, Tyr62, Leu162,
Asp197, His201, Glu233, Ile235,
His299, Asp300, His305
Trp59, Tyr62, Gln63, Tyr151,
Leu162, Leu165, Glu233, Ile235,
His305
Trp58, Trp59, Tyr62, Leu162,
Asp197, His201, Glu233, Ile235,
His299, Asp300, His305,
Trp58, Trp59, Tyr62, Gln63,
Gly104, Thr163, Leu165, Asp300,
His305
ꢂ8.9
ꢂ10.0
ꢂ8.2
ꢂ10.2
ꢂ8.6
Trp82, Gly116, Gly117, Glu197, Ser198,
Trp231, Leu286, Ala328, Phe329, Phe398,
His438
Glu446, Ile472, Leu477, His497, Asn498
Asn228, Pro230, Asp304, Leu307, Glu308, ꢂ7.6
Tyr396, Cys400, Pro401, Glu404, Trp522,
Thr523, Phe526, Pr0527
Asn207, Leu213, Tyr214, Gly215,
His538, Leu540, Trp552, Glu559,
Phe560, Phe563
Asn212, Leu213, Gly215, Met241,
Glu446, Ile472, Leu477, Lys480, His497,
Asn498
Asn212, Gly215, Ala216, Ala240,
Met241, Ile472,
Leu473, Leu477, Cys479, His497,
Asn498
Asp70, Trp82, Gly115, Gly116, Tyr128,
Glu197, Pro285, Ala328, Phe329, Tyr332
ꢂ7.7
5g
Asn228, Tyr396, Cys400, Pro401, Glu404,
Trp522,
ꢂ9.1
Thr523, Phe526, Pro527
5h
5i
ꢂ9.0
ꢂ8.8
ꢂ9.2
Trp58, Trp59, Tyr62, Gln63,
His101, Gly104, Thr163, Leu165,
Asp197, Asp300, His305
Trp59, Tyr62, Tyr151, leu162,
Asp197, Lys200, Ile235, Asp300
ꢂ10.4
ꢂ9.8
ꢂ9.5
Asp70, Trp82, Gly115, Tyr128, Glu197,
Pro285, Ala328, Phe329, Tyr332, His438
ꢂ8.2
ꢂ8.0
ꢂ8.9
Asn207, Leu213, Tyr214, Gly215,
His538, Leu540, Trp552, Phe560
Asp70, Trp82, Glu197, Pro285, Ala328,
Phe329, Tyr332, Met437, His438, Gly439
Asn207, Leu213, Tyr214, Gly215,
Gln217, His538, Leu540, Trp552,
Phe560
Leu213, Tyr214, Gly215, His538,
Leu540, Asn543, Asp549, Trp552,
Ser553, Glu559, Phe560
5j
Trp59, Tyr62, Gln63, Leu162,
Asp197, His201, Ile235, Glu233,
His305
Asp70, Trp82, Gly115, Tyr128, Glu197,
Pro285, Ala328, Phe329, Tyr332, His438
Addition of further ꢂꢂOH groups to the structural framework of
5c appears as a promising method to increase the number of
hydrogen bonded contacts with catalytic site residues and an
overall improvement of IC50 value.
resulted in high electrostatic potential that attracted the tested
compounds inside and down the gorge. Cation- interactions with
catalytic His438 near the bottom of the deep gorge were
prominently noticed and ligands actively formed -alkyl contacts
p
p
with Ala328 in the neighborhood of catalytic Glu325.
3.3.2. Molecular docking study for BuChE
In total, 7 least energy scoring triazole derivatives were
accommodated in the active gorge of BuChE, lined by aromatic
residues Tyr332, Ala328, Trp82, Tyr128, Gly116, Phe329, Gly115
and Pro285, featuring acidic residue Asp70 at the entrance
and Glu197 located at the bottom of gorge (Fig. 3). Potency of 3
hits (5b, 5d and 5 h) was confirmed by both lower IC50 values and
least docking scores. Exyanaion hole residues (Gly116, Gly117
and Ala199) stabilize the transition state of bound enzyme and
absence of interactions with these residues resulted in slightly
higher binding energy score for 5i. On contrary, interaction with
highly conserved NꢂꢂH dipole derived from the side chain of
Gly116 with 5f is accountable for excellent energy score of
ꢂ10.2 kcal/mol. Three poorly scored ligands (5a, 5e and 5 g) were
surrounded by Asn228, Glu404, Trp522 and Thr523 residues and
gathered inside a different pocket in the immediate vicinity of the
active site.
3.3.3. Molecular docking study for human NMGAM
All the binding modes for 5a–5 j hits were explored using
AutoDock Vina. The docked structures exhibited excellent binding
energies in the range of ꢂ7.5 to ꢂ9.1 Kcal/mol. Binding energy
scores of all the docked complexes for NMSAM are enlisted in
Table 1. Based on docking calculations, the synthesized com-
pounds 5 g, 5i, 5c, 5e and 5d showed better inhibition of human
maltase-glucoamylase as compared to standard drug acarbose
which is in a good agreement with the results of
a-glucosidase
assay. 5 g exhibited highest binding energy score of ꢂ9.1 Kcal/mol
and least IC50 value of 1.6Kcal/mol highlighting the significant
involvement of specially arranged negatively charged halo groups
in interacting with positively charged residues of NMGAM pocket
as given in Fig. 4. The synthesized compounds occupied two
closely adjacent sites within NMGAM surface as shown in Fig. 3.
Accommodation of top ranked potent compounds (5 g and 5c)
inside the same groove depicts the importance of basic
interacting residues Asn212, His497, Asn498 in establishing
contacts with NMGAM. Amino acids spanning the region
Asn212- Gly215 were actively interacting key residues in all
docked complexes (Table 1). The docking analysis revealed that
the van der Waals, electrostatic, and desolvation energies played
significant roles in binding. Hydrophobic interactions were
mainly donated by Asn212, Leu213, Tyr214, Gly215, Glu446,
Leu477, His497 and Asn498 with 6, 9, 7, 9, 5, 5, 6 and 6
compounds, respectively.
Asp70 and Tyr332 residues of peripheral anionic site facilitated
the entry of ligands in the active site gorge of enzyme [87].
Residues of the midgorge aromatic recognition region called
anionic site (Trp82, Tyr128 and Phe329) actively contributed in
binding to quaternary ammonium groups of the incoming ligands
via cation-
p interactions, thus providing a proper orientation to
the compounds inside the gorge. Interactions with aliphatic
residues (Leu286 and Pro285) maintained the hollow shape of
acyl pocket for stable binding of ligands within the groove of
BuChE. Asp197 adjoined to the catalytic triad residue (Ser198)

506
P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
Fig. 3. Superimposed conformations of best docked poses for respective ligands in the clefts of (A)
a-amylase pocket (B) butyrylcholinesterase binding site (C) a-glucosidase
binding pocket. Binding pocket is indicated by yellow colored surface onto -amylase, butyrylcholinesterase and maltase-glucoamylase while interacting residues are
a
labelled black. Alterantive binding location in BuChE is colored pink and bound comouunds are indicated by following colors in stick representations: 5a, Yellow; 5b, Magenta;
5c, Dark blue; 5d, Light blue; 5e, Orange; 5f, Purple; 5 g, Red; 5 h, Firebrick; 5i, Dark Green and 5j, Light green. (For interpretation of the references to colour in this figure
legend, the reader is referred to the web version of this article.).
3.4. QSAR modeling
dependent variable and selected parameters as independent
variables resulted in following optimal QSAR models:
QSAR regression models were developed using most significant
descriptors of the compounds as predictive variables. Molecular
descriptors screened on the basis of highest correlation with IC50
values, along with their physiochemical meanings are given in
Table 4. Multiple Linear Regression (MLR) analysis with IC50 as
IC50ðAmylaseÞ ¼ ꢂ6:842 þ ð0:736 ꢃ VR3 DzsÞ
ꢂ ð0:884 ꢃ VR2 DzvÞ þ ð345:454 ꢃ VE2 DzsÞ
þ ð0:069 ꢃ VR2 DzeÞ
þ ð14:551 ꢃ ETA Epsilon 2Þ ꢂ ð17:525 ꢃ JGI2Þ
ð5Þ

P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
507
Fig. 4. Detailed interactions of best docked complexes with (A) BuChE, (B)
a-amylase and (C) maltase-glucosidase. Proteins are styled in ribbon representations while
interacting residues are depicted in wired forms with labelled residues in black color. Bound compounds with minimum IC50 value are illustrated in sticks with meshed
surface in following colors (5c: Dark blue, 5i: Dark green and 5 g: Red). (For interpretation of the references to colour in this figure legend, the reader is referred to the web
version of this article.).
Table 4
Physical–chemical meanings of the descriptors used in the developed QSAR model.
Descriptors
Chemical Meanings
VR3_Dzs
VR2_Dzv
VE2_Dzs
VR2_Dze
ETA_Epsilon_2
JGI2
Logarithmic Randic-like eigenvector-based index from Barysz matrix/weighted by I-state
Normalized Randic-like eigenvector-based index from Barysz matrix/weighted by van der Waals volumes
Average coefficient sum of the last eigenvector from Barysz matrix/weighted by I-state
Normalized Randic-like eigenvector-based index from Barysz matrix/weighted by Sanderson electronegativities
A measure of electronegative atom count
Mean topological charge index of order 2
ETA_AlphaP
Mse
Sum of alpha values of all non-hydrogen vertices of a molecule relative to molecular size
Mean atomic Sanderson electronegativities (scaled on carbon atom)
Solubility
VE3_Dzv
VR1_Dzi
Aqueous solubility
Logarithmic coefficient sum of the last eigenvector from Barysz matrix/weighted by van der Waals volumes
Randic-like eigenvector-based index from Barysz matrix/weighted by first ionization potential
Logarithmic coefficient sum of the last eigenvector from Barysz matrix/weighted by first ionization potential
Graph energy from Barysz matrix/weighted by I-state
Maximum projection areas of the conformer, based on the van der Waals radius
Mean topological charge index of order 6
VE3_Dzi
SpAbs_Dzs
Maximum Projection Area
JGI6
adjusted R2 did not exceed 0.3, indicating no over-fitting of
predicted models.
IC50ðButrylcholinesteraseÞ ¼ ꢂ192:438
QSAR Eq-5 for prediction of IC50 value against
a-amylase
þ ð85:077 ꢃ ETA AlphaPÞ
showed that electronic parameters play dominating roles for
producing variation in the inhibitory activity. Estimates of the
equation suggest that electronegative atoms count, mean topolog-
ical charge and eigen values from Barysz matrix determine the
inhibition potential of a compound where total electronegativity
affects positively and mean topological charge correlates nega-
tively with the inhibition activity. The findings suggest the
incorporation of further halo groups to increase the net
electronegativity and reduce overall topological charge on the
molecules for yielding even better IC50 values.
Eq-2 proposed negative influence of aqueous solubility on IC50
while positive correlation of mean atomic electronegativity and
sum of alpha values of non-hydrogen vertices with inhibition
activity. The model recommended the incorporation of more
strongly electronegative atoms (e.g. fluorine) in the thiazolo[3,2-b]
[1,2,4]triazoles framework for possibly enhancing the inhibitory
þ ð150:774 ꢃ MseÞ
ꢂ ð0:125 ꢃ SolubilityÞ
ð6Þ
IC50ðMaltase ꢂ glucoamylaseÞ ¼ 42:443 þ ð2:955 ꢃ VE3 DzvÞ
ꢂ ð0:053 ꢃ VR1 DziÞ
ꢂ ð0:817 ꢃ VE3 DziÞ
ꢂ ð0:061 ꢃ SpAbs DzsÞ
ꢂ ð0:014 ꢃ MaximumProjectionAreaÞ
þ ð205:596 ꢃ JGI6Þ
ð7Þ
Statistical evaluation of QSAR models included goodness of fit
i.e. R2 (correlation coefficient) and adjusted R2 (goodness of fit)
values as shown in Table 3. The R2 values of QSAR models were
closer to 1 indicating excellent goodness-of-fit while adjusted R2
values approximating 1 implied robustness of the estimated
models. Residual error values depicting differences of R2 and
potential of designed compounds against
a-BuChE.

508
P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
Table 5
VE3_Dzi and VR1_Dzi are the thermodynamic parameters
Statistics of developed QSAR models against target proteins.
which depend on first ionization potential of the constituent atoms
in the compound. Eq-3 showed their inverse relation with IC50
indicating the likelihood inclusion of halo groups having small
atomic radius and higher first ionization potentials for improving
Target Proteins
N
R
R2
Adjusted R2
Amylase
Maltase-glucoamylase
BuChE
10
10
10
1
1
0.999
0.981
0.987
0.996
0.996
0.991
0.992
the inhibition against
a-glucosidase. Geometrical and electronic
parameters in addition to thermodynamic descriptors also
contributed to significant change in the IC50 value. The model
predicted that greater mean topological charge and reduced van
der wall radius/volume may produce the derivative with increased
inhibition against NMGAM.
Overall, the findings signify the importance of halo groups in
synthesized compounds for governing the inhibitory activity
against target proteins in the current study. External validation
was performed by predicting IC50 values of the compounds
through respective QSAR equations and were cross-validated
against the known activity values. Observed IC50 values of the
compounds were in consistency with the predicted values and the
data points in the scatter plots showed very less deviation from the
normal line (Fig. 5). 5c, 5 g and 5i exhibited best observed and
estimated IC50 values, therefore calculated QSAR models evidently
which eliminates the compound from the human body, depends
upon its molecular weight. Likewise, low molecular weight is a
primary determinant of functional absorption inside the body. All
the synthesized compounds weighted less than 500 Da, making
them likely to have high solubility and to pass through cell
membranes easily (Table 7).
Topological Polar Surface Area (TPSA) is another major factor for
determining the rate of molecular absorption and its values for all
the compounds lied in normal range (below the cut off 140 Å from
as given in Table 4. All the derivatives had polarities that enabled
better permeation and absorption, as revealed by lower than 12 cut
off value for the sum of H-bond donors and H-bond acceptors
(Table 4).
confirmed their potency for inhibiting
and -BuChE, respectively.
a-amylase, a-glucosidase
The hydrophilicity and lipophilicity (ratio of a molecule’s
solubility in octanol to solubility in water) of a compound is
measured through logP. High logP value is linked with poor
absorption, less blood-brain barrier permeability and increased
metabolism in liver while smaller logP values are linked with rapid
renal clearance and greater hydrophilicity. Compounds distribu-
tion and excretion also depends on logP and for a compound to be
well absorbed, its value must not be >5. All compounds in our
a
3.5. Pharmacokinetics profiling and toxicity risk analysis
Several physiochemical properties related to pharmacokinetics
of synthesized thiazolo[3,2-b-1,2,4]triazole derivatives were con-
sidered in our study (Tables 5 and 6). The process of excretion,
Fig. 5. Statistical cross validation of predicted QSAR models. Experimentally determined IC50 values are given on x-axis and predicted IC50 values predicted from QSAR
equations are on y-axis. Data points and data labels on the graphs are colored according to the types of synthesized compounds (5a, Yellow; 5b, Magenta; 5c, Dark blue; 5d,
Light blue; 5e, Orange; 5f, Purple; 5 g, Red; 5 h, Firebrick; 5i, Dark Green and 5j, Light green). (For interpretation of the references to colour in this figure legend, the reader is
referred to the web version of this article.).

P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
509
Table 6
Compliance of the synthesized derivatives with the Standard Intervals for Computational Toxicity Risk and drug-likeness parameters. MUT = Mutagenicity,
TUMO = Tumorogenicity, IRRI = Irritation, REP = Reproductive or developmental toxicity, LP=LogP, S=Solubility, DS = Drug score, DL=Druglikeness, MW = molecular weight,
HBD = Hydrogen-bond donors, HBA- Hydrogen-bond acceptors and RofV = Rule of five violations.
Compounds
Toxicity Risk Parameters
Drug-likeness Parameters
Mut
Tum
Irri
Rep
TPSA
LP
S
DL
MW
HBD
HBA
RoFV
5a
5b
5c
5d
5e
5f
5g
5h
5i
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Low
Low
Low
Low
Low
Low
Low
Low
Low
Low
56.01
104.25
104.25
58.43
86.12
58.43
58.43
58.43
67.66
86.12
5.57
4.62
4.91
5.2
4.59
5.37
5.83
6.25
5.42
3.98
ꢂ6.13
4.62
1.1578
396.73
342.42
338.38
331.8
403.88
376.25
392.7
386.31
357.86
369.44
2
2
0
0
0
0
0
0
0
0
3
6
6
3
6
3
3
3
4
6
1
0
0
1
0
1
1
1
0
0
ꢂ2.2898
ꢂ2.2898
1.6988
2.9457
ꢂ0.11801
1.2488
1.1303
ꢂ6.08
ꢂ6.21
ꢂ5.82
ꢂ6.47
ꢂ6.9
ꢂ7.19
ꢂ6.18
ꢂ5.15
2.8885
2.8993
5j
Table 7
Pharmacological Activities (pIC50), Ligand Efficiency (LE), Fit Quality (FQ), Partition coefficient (cLogP), Heavy atoms count (HA), Scaled Ligand Efficiency (LES), Lipophilic
Efficiency (LipE) Profiles of compounds against - Amylase, BuChE and Maltase- glucoamylase.
a
a
- Amylase
Α-BuChE
Maltase- glucoamylase
cLogP
LipE
HA
LES
pIC50
LE
FQ
pIC50
LE
FQ
pIC50
LE
FQ
5a
5b
5c
5d
5e
5f
5g
5h
5i
4.249
4.1227
5.5835
5.5835
4.1419
4.4858
4.0106
3.4577
3.3687
3.9514
5.1647
22
24
24
22
27
22
22
23
24
26
0.69
0.62
0.62
0.69
0.62
0.69
0.69
0.69
0.66
0.62
5.26
5.2
2.40
1.19
1.36
2.35
1.20
2.51
2.43
2.37
1.74
1.15
3.52
1.9
5.66
5.72
5.28
5.38
5.14
5.03
5.13
5.74
5.82
5.11
2.56
1.30
1.20
2.45
1.17
2.29
2.34
2.60
1.99
1.17
3.72
2.08
1.92
3.57
1.87
3.34
3.41
3.8
5.11
5.05
5.6
5.43
5.45
5.16
5.92
5.008
5.82
5.11
2.33
1.15
1.28
2.47
1.23
5.33
2.69
2.28
1.99
1.16
3.4
2.9471
2.9471
4.2316
3.9208
4.3508
4.856
4.9378
4.4047
3.3148
1.84
2.03
3.59
1.97
7.76
3.92
3.32
2.98
1.85
5.95
5.142
5.275
5.494
5.327
5.2
2.17
3.42
1.92
3.66
3.55
3.45
2.6
5.08
5.017
2.98
1.85
5j
1.834
study showed cLogP values less than 5 indicating aqueous
solubility and easier access to membrane surfaces (Table 5). In
summary, the results revealed that all of the compounds followed
Lipinski’s rule of five (i.e. Molecular weight: < 500, Octanol-water
coefficient (LogP): < 5, H-bond donors: < 5 and H-bond accept-
ors: < 10).
for a-BuChE while a sharp increasing trend was witnessed with
a
-amylase (Fig. 6b and c). On contrary, reduction of inhibition
potential correlated with higher cLogP values in the case of
-Amylase (Fig. 6a). These findings are exactly in agreement with
the fact that 5c with least, 5 g with relatively higher and 5i with
highest values of cLogP are good inhibitors of -amylase, -BuChE
and -glucosidase, respectively (Fig. 7).
a
a
a
The plots of cLogP and pIC50 showed that inhibition activity
gradually improved on increasing the lipophilicity of compounds
a
Table 8
Smiles and IC50 values of selected compounds from training sets, which were used to predict pharmacophoric features.
Target Protein
IC50
Smiles
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
6
7
1
2
3
4
5
6
7
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Amylase
- Glucosidase
- Glucosidase
- Glucosidase
- Glucosidase
- Glucosidase
- Glucosidase
- Glucosidase
9.28
12.65
11.08
9.79
9.64
4.3
4.8
5.3
4.8
14
O
O
O
O
O
OC1
OC1
OC1
¼
¼
¼
¼
¼
C(N/N
C(N/N
C(N/N
C(N/N
¼
¼
¼
¼
C/CC3
C/CC3
C/CC3
C/CC3
¼
¼
¼
¼
CC
CC
CC
CC
¼
¼
¼
¼
C(Cl)C
¼
C3)C1
C3)C1
C3)C1
C3)C1
C(O)C([H])
¼
CC
CC
CC
CC
¼
C(NC
C(NC
C(NC
C(NC
C3[H])C2)C1
¼
C2)C2
C2)C2
C2)C2
C2)C2
¼
C1
C1
C(C)C
CC(O)
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
C1
C1
CC(F)
¼
¼
¼
¼
¼
C(C([H])
¼
C(C3
¼
CC([H])
¼
¼
¼
C2C
¼
C(O)C(O)
¼
C1O
¼
¼
¼
CC(C3
CC(C3
CC
¼C(O)C(C2
C(O)C(C2
¼
C(O)C
C(O)C
¼
C(O)C
C(O)C
¼
C2O3)
¼
O)
O)
¼
¼
CC(O)
CC
¼
C1O
¼
¼
¼
¼
C2O3)
¼
¼
¼
¼
C1O
C1
¼
C(C3
¼C(O)C(C2
¼
C(O)C
C/C(O)
¼
C(O)C
C2O3)
O)C
¼
[H]C1
O
¼
C(OC)C(O)
¼
CC(/C
¼
¼
O)
¼
C1
¼
C(C([H])([H])C([H])([H])C(C([H])
¼C1[H])
¼
C([H])C(O[H]) C1O[H])O[H]
¼
5
8.48
7.6
OC1
C(N/N
OC1 CC(C3
¼
C(OC)C
C/CC4
C(OC(O4)C(O)C(O)C4O)C(C2
¼
C(/C
¼
¼
C/C(O)
¼
¼O)C
¼C1[H]
C
¼
¼
CC
CS4)C(C
¼
C3) CC
¼
¼
C3C2
¼
NC1
¼
CC
¼
CC
C2O3)
CC
CC
¼
C1S2
¼
¼
¼
C(O)C
¼
C3C2
C3C2
C(O)C
¼
¼
O)
C1S2
C1S2
¼
CC C1O
¼
11.29
5.55
12.75
5.58
8.37
4.287
4.987
1.142
3.936
4.2
O
O
O
O
O
¼
¼
¼
¼
¼
C(NN
C(NN
C(NN
C(NN
C(NN
¼
¼
¼
¼
¼
CC4
CC4
CC4
CC4
CC4
¼
¼
¼
¼
¼
CC
C(O)C
CC
C(O)C
C(O)C
¼
C(O)C
¼
C4)C(C
C4)C(C
¼
C3)
¼
CC
CC
¼
¼
NC1
¼
¼
¼
¼
CC
CC
¼
¼
¼
CC
¼
¼
C3)
¼
¼
¼NC1
¼
CO4)C(C
¼
C3)
¼
CC
¼
C3C2
¼
NC1
¼
CC
¼
CC
¼
C1S2
¼
C(O)C
¼
C4)C(C
C4O)C(C
CC
C(COC4
NN1C(C3 CC
C3N2N C(C4 CC
¼
C3)
C3)
C(OC)C
CC CC
C(OC)C
CC(C5
¼
CC
CC
C4)
C4C)S3)C
C3) NN
CC CC
C1.ClC(C
C1.BrC(C
C1.CNC3
¼
C3C2
C3C2
NN
¼
NC1
NC1
C2S3
C1
C1S2
C5) C4)CS3)
C3) CC C3NC
C3) CC C3NC
CC C(C(F)(F)F)C
¼
CC
¼
CC
¼
C1S2
¼
¼
C(O)C
¼
¼
¼
¼
¼
¼
CC
¼CC
C1S2
Butrylcholinesterase
Butrylcholinesterase
Butrylcholinesterase
Butrylcholinesterase
Butrylcholinesterase
Butrylcholinesterase
Butrylcholinesterase
OC1
¼
CC
¼
CC
¼
C1OCC3
¼
NN2C(C4
¼
¼
¼
¼
¼
COC1
COC4
COC1
ClC1
ClC1
ClC1
¼
CC
¼
¼
¼
C(C2
C(C
CC(C2
¼
NN
C4)OCC2
NN
¼
C3N2N
¼
¼
¼
¼
¼
¼
¼
CC
CC
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
C1
¼
CC
CC
CC
¼
¼
¼
C(OC(N(C2
C(OC(N(C2
C(OC(N(C2
¼
CC
CC
CC
¼CC
¼CC
¼CC
¼
¼
¼
C2)C)
C2)C)
C2)C)
¼
¼
¼
O)C(C(C)
O)C(C(C)
O)C(C(C)
¼
¼
¼
O)
O)
O)
¼
¼
¼
¼
¼
¼
4.3
1.97
¼
¼
¼
¼
¼
¼
¼
¼
¼
¼
C3

510
P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
The aqueous solubility(S) of a compound significantly affects its
dramatically with the increase of ligand size (Fig. 6). A similar
trend has been observed in the literature, with LE showing
generally a dependency on ligand size [88].
absorption and distribution characteristics and low solubility is
associated with poor absorption. The calculated values of the
studied compounds were within the acceptable interval (between
ꢂ6.5 and 0.5 suggested in Table 4. Number of heavy atoms between
20 and 7016, has been proposed to be useful in the prediction of the
pharmacokinetic drug-likeness of a compound. All the compounds
in our study satisfied this criterion.
We also employed the calculation of ligand efficiency (LE)
values for better characterization of the pharmacokinetic behavior
of the compounds (Table 5). For thiazolo[3,2-b]-1,2,4-triazole
derivatives, smaller ligands such as 5a, 5 g, 5f and 5d exhibited
higher efficiency values than the larger ligand. It was also observed
that ligands with same heavy atoms numbers (e.g. 5a, 5d, 5 g and
5f) clustered together in the graphs (Fig. 6d, e and f). For the whole
data set, it was observed that ligand efficiencies dropped
LipE is a parameter that combines both potency and lip-
ophilicity and is defined as a measure of how efficiently a ligand
exploits its lipophilicity to bind to a given target. It has been
reported that a lipophilic efficiency greater than 5 combined with
clogP values between 2 and 3 is considered optimal for a promising
drug candidate [89]. LipE profiles of the compounds 5b, 5c and 5 j
identified them as promising candidates as their values reached
the standard threshold of 5 (Table 5). However, other compounds
also displayed LipE values in acceptable ranges signifying their
likely effectiveness (Table 5).
Fit quality score close to 1.0 indicates optimal ligand binding,
while low fit quality scores are indicative of suboptimal binding.
Use of this criterion showed that all of the compounds under
Fig. 6. Correlation of pharmacokinetic properties of the compounds. Colors of data points are represent various target proteins (Grey: a-Amylase, Cyan: BuChE and Magenta:
Maltase- glucoamylase). A, B and C) Correlation of inhibitory potency of compounds (expressed as pIC50 values) vs cLogP values of the ligands. D, E and F) Plot of ligand
efficiency vs heavy atom count for all compounds. G, H and I) Fit quality scores vs heavy atom count. FQ score around 1 indicate a near optimal ligand binding affinity for a
given number of heavy atoms.

P.A. Channar et al. / Biomedicine & Pharmacotherapy 94 (2017) 499–513
511
Fig. 7. Pharmacophore feature mapping. Pharmacophoric features of selected inhibitors from training data sets are mapped for Butrylcholinesterase(A),
a-Amylase(B) and
Glucosidase(C). These features are depicted in green (hydrogen bond donor), pink (hydrogen bond acceptor), cyan (armatic) and golden (hydrophobic) colors. (For
interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).
present investigation showed FQ scores closer to 1, indicating that
synthesized compounds have better in vivo performance based on
their ligand binding, potency and lipophilicity profiles (Fig. 6g, h
and i).
We predicted toxicity risk parameters for example, mutagenic-
ity, tumorogenicity, irritation and reproductive or developmental
toxicities of the synthesized thiazolo[3,2-b-1,2,4]triazole deriva-
tives. The toxicity risk predicting softwares locate fragments
within a molecule which indicate a potential toxicity risk. Toxicity
results from Lazar, Toxicity Checker and ORSIS Data Warrior
confirmed that none of the presented compounds has any toxic
subcomponent which assures the safety of all compounds for
clinical and in-vitro trials.
Conflict of interest
The authors declare no any conflict of interest
Acknowledgement
We are thankful to Quaid-i-Azam University, Islamabad,
Pakistan
Appendix A. Supplementary data
Supplementary data associated with this article can be
found, in the online version, at http://dx.doi.org/10.1016/j.
biopha.2017.07.139.
The training set for QSAR model is included in the Supplemen-
tary data. We isolated 50 known thiazol and trizol derivatives for
each protein (a-Amylase,
a- Glucosidase and Butrylcholinester-
References
ase) with IC50 values and listed descriptors. On the basis of
descriptor similarity, selected hits were used for pharmacophore
generation. The pharmacophore hypothesis with maximized
features was tested for 10 compounds (test data set), synthesized
in this study. The purpose of 2D QSAR modeling was to elaborate
the inhibitory potential of listed hits, as their experimental and
predicted IC50 values (through QSAR modeling) are quite similar.
The training data set used in pharmacophore modeling has
been listed in Table 7. Predicted pharmacophoric features in
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