Synthesis, Characterization, In vivo, Molecular Docking, ADMET and HOMO-LUMO study of Juvenile Hormone Analogues having sulfonamide feature as an Insect Growth Regulators

Article abstract of DOI:10.1016/j.molstruc.2021.129945

The search for a simple and efficient method for the synthesis of sulfonamide derivatives as an Insect Growth Regulators (IGRs) under mild and eco-friendly conditions is of our interest. Here, we report a simple, efficient, and eco-friendly method for the

Full text of DOI:10.1016/j.molstruc.2021.129945

Journal of Molecular Structure 1231 (2021) 129945
Contents lists available at ScienceDirect
Journal of Molecular Structure
journal homepage: www.elsevier.com/locate/molstr
Synthesis, Characterization, In vivo, Molecular Docking, ADMET and
HOMO-LUMO study of Juvenile Hormone Analogues having
sulfonamide feature as an Insect Growth Regulators
Priyanka Sharma, Pamita Awasthi∗
Department of Chemistry, National Institute of Technology, Hamirpur, H.P.-17 7005
a r t i c l e i n f o
a b s t r a c t
Article history:
The search for a simple and efficient method for the synthesis of sulfonamide derivatives as an In-
sect Growth Regulators (IGRs) under mild and eco-friendly conditions is of our interest. Here, we re-
port a simple, efficient, and eco-friendly method for the synthesis of sulfonamide derivatives. A series
of sulfonamides containing aniline derivatives have been synthesized. L-amino acid has been added in
the intermediate steps which increase the bioactivity of the synthesized analogs. The structure eluci-
dations of the synthesized analogs have been done using spectroscopic tools like - FTIR, NMR-1H, 13 C,
ESI-MS. In vivo efficacy of the synthesized analogs has been investigated under laboratory conditions.
Galleria mellonella has been chosen as a model insect, commonly known as honeycomb pest. G. mel-
lonella causes a huge loss to beekeeping industries. All synthesized analogs showed insect growth regu-
latory action against the model species. Calculated LC50 and LC90 of all the analogs (T1-T8) against the
fourth instar larvae were 9.99, 10.12, 13.70, 13.59, 13.94, 21.69, 13.28, 12.80 ppm and 153.27, 131.69,
113. 23, 161.70, 141.48, 205.75, 110.93, 96.91 ppm, respectively. Among these analogs, N-(1-isopropyl-
2-oxo-2- p-nitroanilino-ethyl) toluene-p-sulphonamide (T8) and N-(1-isopropyl-2-oxo-2- p-nitroanilino-
ethyl) benzene-sulphonamide (T7) exhibited the good pest larval mortality in comparison to in use IGR
like- Pyriproxyfen (T1) and Fenoxycarb (T2). Docking using AutoDock 4.2 has been carried out to identify
the potential binding affinities and mode of interaction of the synthesized analogs (T3-T8) with Juve-
nile Hormone Binding Protein (JHBP) of G. mellonella in comparison to in use IGRs Pyriproxyfen (T1) and
Fenoxycarb(T2). Additionally, in silico ADMET (absorption, distribution, metabolism, excretion, and toxi-
city) filtration has been used to predict the properties of the analogs. Quantum chemical calculations
like Density Functional Theory have been performed to calculate different global reactivity descriptors.
A small difference between HOMO and LUMO energy signifies the electronic excitation energy which is
essential to calculate molecular reactivity and stability of the aniline based sulfonamides (T3-T8).
Received 26 February 2020
Revised 30 November 2020
Accepted 11 January 2021
Available online 20 January 2021
Keywords:
Juvenile Hormone (JH)
Juvenile Hormone Analogues (JHAs)
Insect growth regulators (IGRs)
Juvenile hormone binding proteins (JHBPs)
Docking
Galleria mellonella
larval mortality
lethal concentration (LC)
ADMET (Absorption, Distribution,
Metabolism, Excretion, and Toxicity)
HOMO-LUMO
© 2021 Elsevier B.V. All rights reserved.
Introduction
been categorized into a) terpenoid b) non-terpenoid series of com-
pounds. The non-terpenoid Phenoxy derivatives were found to be
The overuse of conventional pesticides/Insecticides has caused
a major threat to an environment. The use of these chemicals has
created an imbalance in the ecosystems. Insects have developed
resistance against them and soil has lost fertility. Need has been
felt by the chemist worldwide to look for safer alternatives. In-
sect growth regulators (IGRs) are considered to be third genera-
tion pesticides and have the potential to replace the conventional
pesticides/Insecticides from the market. These IGRs are safer to
use, species-specific, target in action, biodegradable, environment-
friendly, and non-toxic to humans. This class of chemicals has
more bioactive against different insect pest species [54].
Insects have a very fast multiplication rate. Sudden arrest in in-
sect and pest populations may cause an imbalance in the ecosys-
tem by affecting directly/indirectly processes like food web, food
chain, pollination, etc. Therefore, it is advisable to control insect
and pest populations slowly and steadily without disturbing the
ecosystem [61]. Insect species exhibit a distinct phenomenon of
metamorphosis (Egg-Larva-Pupa-Adult). This process is under the
control of two important hormones that are released by the en-
docrine system of the insects namely –Juvenile Hormone & Ecdys-
teroid Hormone. A slight variation in the amount and secretion
of these hormones results in the physical deformities in insect
species which result in reduced population growth [49,61]. Juve-
∗
Corresponding author.
E-mail addresses: pamita@nith.ac.in, pamitawasthi@gmail.com (P. Awasthi).
https://doi.org/10.1016/j.molstruc.2021.129945
0022-2860/© 2021 Elsevier B.V. All rights reserved.

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 1. (a) Natural Juvenile Hormones; (b) Synthetic Insect Growth Regulators (T1-T2); (c) Structure of parent analog of synthesized series (T3-T8).
nile Hormone after release from the endocrine system combined
with carrier proteins present in the hemolymph (Fig. 1a). These
carrier proteins have a strong binding affinity and stereoselectiv-
ity for JH molecules [14,32,45,33] and known as Juvenile Hor-
mone Binding Proteins (JHBPs). JHBPs undergo a profound con-
formational transition upon binding to JH [79]. Juvenile hormone
analogs (JHAs) are believed to be JH mimics. JHA’s are proposed to
act by interacting with various proteins present in the hemolymph
[47,46,77,69,67,30]. JH analogs are reported to keep the insects in
an immature and potentially injurious stage longer than normal
time and ultimately affect insect population.
grated pest management program. Further, Fenoxycarb is mainly
used to control Lepidoptera species in fruit orchards and vineyards
[12,34,51]. Fenoxycarb (T2) also finds its applications to control the
population of G. mellonella as it altered male gonad physiology,
causing germ cell death at different stages of differentiation. Treat-
ment of G. mellonella larvae with Fenoxycarb resulted in larval di-
apause, mainly immediately after its application [10]. Several JHAs
with different structural features have been reported in the liter-
ature and exhibited antagonist effect against most of the harmful
insect species [6,29,36,43,48,54,68,76,75].
The greater wax moth, Galleria mellonella Linnaeus, is a ubiq-
uitous pest of the honeybee mainly Apis mellifera and Apis cer-
ana worldwide. G. mellonella causes the greatest damage in api-
aries which leads to huge financial losses every year. Almost all the
colonies of Asian honeybees are prone to moth infestation. Wax
moth belongs to the subfamily Galleriinae of the family Pyralidae,
order Lepidoptera. Wax moth infestation is at its peak during the
monsoon season from July to August during summer and Decem-
ber to January during the winter season [13,50]. Therefore, there is
a need for more studies to find sustainable integrated pest man-
agement strategies. The population of G. mellonella can be con-
trolled by biological and chemical methods. The successful and
sustainable biological control agent for G. mellonella is still lacking.
Chemical control involved the use of fumigants in most beekeeping
regions. Various types of fumigants have been used and found to
be effective against wax moth include sulfur, acetic acid, ethylene
bromide, calcium cyanide, phosphine, paradichlorobenzene (PDB),
naphthalene, and carbon dioxide. More importantly, they are poi-
sonous to honeybee colonies and non-target species [58,74,16].
Sulfonamides, the most common scaffolds in sulfur-containing
molecules, are well studied in synthesis and application during the
past decades, is the subject of our interest. Sulfur-containing com-
Among all synthetic IGR’s, Pyriproxyfen (Pyridine based IGR)
showed highly inhibitory reproductive and metamorphic action
against agricultural, household, and public hygiene insects and
pests. It is effective against mosquitoes, Sunn pest (Eurygaster inte-
griceps Puton), onion thrips (Thripstabaci Lindeman), the mealworm
(Tenebrio molitor), house flies (Musca domestica), etc. It has been
proposed to exhibit low mammalian toxicity. The mode of action,
as well as the environmental behavior of Pyriproxyfen completely
differs from organo-chlorinated and organo-phosphorous com-
pounds (Fig. 1b) [4,37,44,3,11]. In the present study, Pyriproxyfen
(T1) is chosen as the standard. It is an important IGR against Gal-
leria mellonella as it causes physiological and pathological changes
in G. mellonella hemocytes. The toxic effect of Pyriproxyfen on en-
docrine glands resulted in the reduction of total hemocyte count
which is due to the clumping of hemocytes. Pyriproxyfen also
causes damage to the plasma membrane of hemocytes of Galleria
mellonella. A combination of Pyriproxyfen and B. thuringiensis af-
fected the antioxidant defense system of G. mellonella larvae even
at low doses [64,65]. Fenoxycarb (T2), a carbamate feature contain-
ing the class of IGR, exhibits ovicidal activity. It is effective against
flea, mosquito, and cockroach control. It is also used in an inte-
2

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
pounds have shown diverse biological activity and serve an impor-
tant function in the pharmaceutical industry [27]. Sulfur is consid-
ered to be a general-use pesticide in agriculture. Benzene sulfon-
amides with low cost and low toxicity are popularly used as insec-
ticide/Pesticide in the agrochemical field [21,63,71]. The presence
of a nucleophilic group on this compound allows further chemi-
cal modifications to obtain novel sulfonamide derivatives. A vari-
ety of aniline derivatives as a nucleophilic agent are allowed to re-
act with benzene sulfonamide carboxylic acid chlorides to obtain
a new series of analogs. Aniline and its derivatives find vast ap-
plication in drugs, pesticides, rubber azo dyes photographic chem-
icals, etc. [70,39]. Four analogs were further modified by replac-
ing Hydrogen atom at position 11’ with chlorine or nitro group in
the aryl ring B (Fig. 1c). The nitro group/chloro group with various
electronic properties and spatial characteristics were considered to
explore the relationship between structure and pesticide activity.
The results indicate that the electron-withdrawing group at posi-
tion 11’ on the aryl ring B plays a unique role in enhancing the
pesticide activity [35,39,42,18,78].
formula [1].
Corrected mortality =
Observed mortality in treatment − observed mortality in control
100 − Control mortality
×100
Number of dead larvae
Number of larvae introduced
Percentage mortality =
× 100
The LC50 and LC90 were calculated from toxicity data using pro-
bit analysis [28].
2.2.2. Efficacy of Analogs (T1-T8) for anti-Juvenile hormone activity
(Pesticidal action)
When the pest crop is on full destruction to the host; the need
is felt for the immediate action of in use IGRs. The diverse con-
centration of these in use IGRs; Pyriproxyfen (T1) and Fenoxycarb
(T2) ranging from 1000 ppm to 10,0000 ppm, in acetone on a w/v
basis, has been used for testing against lepidopteran insect species
to show pesticidal effects [3,25,31,52].
The work presented here is a part of the pest management pro-
gram carried out in our laboratory. In this paper, we report synthe-
sis, characterization, in vivo testing, Docking, ADMET, and HOMO-
LUMO study of JHAs having sulfur group, L-amino acid, and aniline
derivative having lipophilic group along with hydrophobic termi-
nations at the ends of the main chain with JHBP of G. mellonella
(Fig. 1c).
Larvae of the fourth instar of G. mellonella were collected and
maintained for the treatment. Acetone solution (2 ml) containing
the analog was poured on the filter paper in each petri dish and
allowed to evaporate. Later, the counted number of larvae to be
treated was transferred to the Petri dishes and applying the dif-
ferent concentrations of the analogs to them. The mortality rate
was noted for each of the replication sets. Each treatment involved
three replicates with each replicate containing ten insects. The
same procedure has been applied for all the analogs (T1-T8).
Different concentrations ranging from 250 ppm to 2000 ppm
have been prepared to check the immediate action of all the syn-
thesized analogs with a lesser exposure period (2-10 hours). Syn-
thesized analogs (T3-T8) and in use IGRs (T1 &T2) did not show any
visible change in the insect behavior up to 750 ppm for ten hours
of exposure period but changes were seen at 1000 ppm from four
hours to ten hours exposure period. 2 ml volume of each has been
used for in vivo study.
Materials and Methods
2.1. General methods and material for the synthesis
Chemical reagents and solvents used were purchased from
Sigma Aldrich of 99% purity grade.
Analogs (T3-T8) have been synthesized in our laboratory using
a simple reaction scheme (Fig. 2). The progress of the reaction was
monitored by thin-layer chromatography (TLC).
The following solvent systems were employed – a. Benzene:
Methanol (8:2), b. Ether: Pet-Ether: Ethyl acetate (5:5:2).
Melting points were determined on a hot-stage apparatus and
are uncorrected. Each compound was synthesized and verified
by spectroscopic methods. FT-IR spectra were recorded on Perkin
Elmer 1600 spectrophotometer with the samples as compressed
2.2.3. Statistical analysis
For IGR action the data were subjected to analysis of variance.
The average larval mortality data were further subjected to pro-
bit analysis for calculating LC50 and LC90 values [28]. For pesticidal
action, the data were grouped according to the number of analogs
(T1 to T8), concentration (C in ppm), and exposure time (I in hours)
and subjected to analysis of variance. Further data were statisti-
cally analyzed to calculate the critical difference (CD) at P ≤0.05.
KBr pellets ranging from 4000 to 400 cm−1 1H and 13C NMR spec-
.
tra were recorded using a Brucker Avance 400 MHz spectropho-
tometer operating at room temperature in DMSO d6 as the solvent.
The electron spray ionization-mass spectroscopy (ESI-MS) analyses
were carried out in positive ion modes using a Water Q of Micro-
mass.
2.3. Principle of Molecular docking using AutoDock 4.2
AutoDock 4.2 an automated docking tool (The Scripps Research
Institute La Jolla, CA 92037-1000, U.S.A.) has been used for the
present study to predict the mode of binding of JH Analogues to a
receptor protein. The semiempirical force field evaluates binding in
two steps. In the first step, intramolecular energetics is estimated
for the transition from unbound states to the bound state whereas
the second step evaluates the intermolecular energetics of combin-
ing the ligand and protein in their bound conformation. The force
field includes six pair-wise evaluations (V) and estimates the con-
formational entropy lost upon binding (ꢀSconf):
2.2. Rearing of the insect model
An artificial diet has been developed for mass rearing of Galleria
mellonella in our laboratory (temperature 27 1°C, relative humid-
ity 65 5 % and 16:8 hr scoto-photo-phase regime) and prepared
by a well-defined method with some modifications [5].
In vivo efficacy of Analogs (T1-T8) as IGRs
A laboratory-reared colony of G. mellonella larvae was used for
IGR activity. Ten larvae of fourth instars were kept in a 500 ml
glass beaker. The diverse concentration of all analogs (T1-T8) rang-
ing from 10 ppm to 100 ppm, in acetone on w/v basis, has been
used for testing against lepidopteran insect species to show IGR
effects. The control mortalities were corrected by using Abbott’s
ꢀ
ꢀG = V
ꢀ
ꢁ
ꢀ
ꢁ
L−L
L−L
P−P
P−P
− V
+ V
− ꢀScon f
− V
bound
unbound
bound
unbound
ꢁ
P−L
P−L
+ V
− V
bound
unbound
(L refers to the “ligand” and P refers to the “protein” in a ligand-
protein docking calculation) (http://autodock.scripps.edu/)
3

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 2. Complete synthesis of juvenile hormone analogs (T3-T8)
Further analogs are screened based upon their scoring function.
In AutoDock the implemented scoring function is defined as an
empirical binding free energy function. Each of the pair-wise ener-
getic terms includes evaluations for dispersion/repulsion, hydrogen
bonding as per the following expression:
[ꢀG=change in free energy; ꢀGvdw: 12-6 Lennard-Jones po-
tential; ꢀGele
:
Coulombic with SolmaJer-dielectric; ꢀG
:
H-bond
12-10 Potential with Goodford Directionality; ꢀGtors: Number
of rotatable bonds; ꢀG Stouten Pairwise Atomic Solva-
:
solv
tion Parameters; ࢞Gtor is a measure of the unfavorable entropy
of ligand binding due to the restriction of conformational de-
grees of freedom, and Ntor is the number of sp3 bonds in
the ligand].
ꢃ
ꢄ
ꢃ
ꢄ
ꢂ
ꢂ
Aij
12
Bij
ri6j
Cij
12
Dij
10
ꢀG = ꢀG
−
+ ꢀGhbund E(φ)
−
vdw
r
r
r
ij
ij
ij
i, j
qiqj
i, j
ꢂ
ꢂ
(−ri2j/2σ2 )
+ ꢀGelec
+ ꢀGtorNtor + ꢀGsol (SiVj + SjVi)e
ε(rij )rij
i, j
i, j
4

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
nal energy of the ligand when it is bound to the protein.) [http:
//autodock.scripps.edu/]
Therefore,
ꢀGbind = aꢀGvdw + bꢀGele + cꢀGH−bond + dꢀGtors + eꢀGsolv
(Here ꢀG=change in free energy; ꢀGvdw
: 12-6 Lennard-
Jones potential; ꢀGele: Coulombic with Solmajer-dielectric; ꢀG
H-bond: 12-10 Potential with Goodford Directionality; ꢀGtors: Num-
ber of rotatable bonds; ꢀGsolv
vation Parameters; a, b, c,
:
Stouten Pairwise Atomic Sol-
and terms are scaling co-
d
e
efficient obtained using AutoDock force field and by default,
their values are: ꢀGbind =0.1662vdw + 0.1406 ele + 0.1209 H-
bond + 0.2983tors + 0.1322desolve)
Ki = exp((ꢀG × 1000)/ R × T
(
)
(Where ꢀGb is binding energy, R = 1.98719 cal and T = 298.15
(temp in Kelvin)
A combination of intermolecular + internal energy is measured
as ‘dock energy’, while intermolecular + torsional energy is mea-
sured as ‘binding energy’. The same protocol was applied for all
analogs (T3-T8) and standard IGR’s (pyriproxyfen and fenoxycarb).
All simulations have been performed on the Linux operating system
with system Properties (Intel(R) Pentium(R) D CPU 2.80GHz, 4.0 GB of
RAM).
Fig. 3. Docked structure of JH Analogs inside the binding cavity of JH binding pro-
tein (PDB 2RCK) (structures have been drawn by using Auto Dock 4.2 software)
2.3.1. Preparation of files
The structures of JH analogs have been built using pymol soft-
ware tool (www.pymol.com) and optimized using AMBER force
field. Gasteiger charge has been assigned to ligands and then non-
polar hydrogens were allowed to merge. The rigid roots were de-
fined automatically for each compound. Further Auto Tor module
has been applied to define the flexibility of the bonds in the lig-
ands. Final ligand structures were saved as ligand.pdbqt format. The
PDB file of the JHBP of G. mellonella (2RCK) has been downloaded
from the protein data bank (www.rcsb.org). Polar hydrogens were
added to the macromolecule (2RCK) using the ADDSOL utility of
AutoDock 4.2. The Kollman charges were added to each atom of
chain A and saved as protein.pdbqt format. A grid box was gener-
ated around the binding cavity of the JHBP by selecting key amino
acid residues THR 22, TYR 128 & 130 [46] (Fig. 3). It was gener-
ated for the calculation of docking interaction energy followed by
the generation of grid parameter file pro.gpf of protein using the
Auto Grid Tool of the software. Since the structure of the protein
kept rigid and known, interaction energies between the probe and
surrounding amino acids have been calculated at each point in the
grid and stored in the output file as pro.glg. The grids were cho-
sen to be sufficiently large to include not only the active site but
also a significant portion of the surrounding surface at receptor
protein with grid points 69 × 67 × 69, along with a grid spac-
ing of 0.531A0. Lamarckian Genetic Algorithm (LGA) protocol has
been used for protein fixed: ligand flexible model [63,38,53].
For the local search, the pseudo-solis and wets algorithm was
applied. Other docking parameters were set as default. Final dock-
ing orientations lying within 2 Ǻ of the root-mean-square devia-
tion (rmsd) tolerance of each other were represented as the most
favorable conformation with the low free energy of binding (ꢀGb).
The dock parameter file for ligand was saved as lig.dpf. All the
analogs were ranked according to their binding free energy (ꢀGb
in kcal/mol) and inhibition constant (Ki in μM) at 298.15K. Overall,
the free energy of binding (ꢀGb) was composed of a sum of free
energies measured for each analog pose and given as:
In silico ADMET screening
Absorption, distribution, metabolism, elimination, and toxicity
(ADMET) properties were analyzed using ADMET descriptors on
Discovery Studio 2.1. It has six mathematical models to quantita-
tively predict the properties like - ADMET absorption level (hu-
man intestinal absorption); ADMET aqueous solubility level; AD-
MET BBB (Blood Brain Barrier penetration level); ADMET CYP2D6
(Cytochrome P450 2D6 enzyme inhibition); ADMET hepatotoxicity;
ADMET PPB (plasma protein binding level) (Table 1).
These properties indicate threshold ADMET characteristics for
the chemical structure of synthesized JH analogs (T3-T8) and Syn-
thetic IGRs (T1-T2). All synthesized compounds were subjected to
ADMET study to predict the level of toxicity and side effects on
humans.
AlogP (ADMET AlogP98) and 2D polar surface area (ADMET
PSA_2D) calculations in ADMET can predict human intestinal ab-
sorption (HIA). The absorption level of the HIA model is defined
by 95% and 99% confidence ellipses by plotting ADMET AlogP98 vs
ADMET PSA_2D [15,17,22,66,23,19].
Quantum chemical studies: The quantum chemical calcula-
tions were carried out on Gaussian 98 software. Structures were
visualized in Gaussview 3.0 software tool. All the analogs (T1-T8)
were fully optimized using the B3LYP/6-31+G (d, p) level of ba-
sis set using the Density Functional Theory method. After opti-
mizations of analogs, energies of the highest occupied molecular
orbital (HOMO) and lowest unoccupied molecular orbital (LUMO)
were obtained from occupied and virtual eigenvalues mentioned in
the Gaussian output file. Further, the reactivity descriptors such as
energy gap, electrophilicity index, chemical hardness, and softness,
etc. have been calculated from HOMO –LUMO data [72,55,56]. The
present work examines the applicability of all chemical descriptors
in the prediction of biological activity of a class of synthesized JH
analogs (T3-T8) to be potential insect growth regulators (IGRs).
ꢀGb = IntermolecularEnergy + InternalEnergy
+ Torsionalenergy − Unboundsystem’senergy
Results and Discussion
3.1. Synthesis of N-(1-isopropyl-2-oxo-2-anilino-ethyl) benzene
sulfonamide and related compounds (T3-T8)
IntermolecularEnergy = aꢀGvdw + bꢀGele + cꢀGH−bond + eꢀGsol
(Since Auto Dock 4.2 measures the Final Total Internal Energy
same as Unbound System’s Energy and equal to the difference be-
tween the internal energy of the unbound model and the inter-
Synthesis of N-(1-isopropyl-2-oxo-2-anilino-ethyl) benzene sul-
fonamide and related compounds (T3-T8) has been achieved by the
5

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Table 1
at higher concentrations ranging from 750 to 2000 ppm at dif-
ferent exposure time from 2 to 10 h. The mortality rate was in-
significant at concentrations ranging from 250-750 ppm at a lesser
exposure time (2-10 hours) in comparison to previous IGR stud-
ies [63]. The larval mortality of G. mellonella increased with an in-
crease in the concentration of the different analogs-based formula-
tions. A significantly progressive increase in mortality was recorded
with the increase in the exposure period as well as concentration.
All treatments showed maximum efficacy against G. mellonella at
2000 ppm after 10 hours of exposure time.
ADMET descriptors and their rules/keys [57].
ADMET absorption level (human intestinal absorption)
Level
Description
0
1
2
3
Good absorption
Moderate absorption
Low absorption
Very low absorption
ADMET (blood brain barrier penetration level) BBB
Level
Description
0
Very High
1
High
All the synthetic analogs (T3-T8) showed significant effects on
larval mortality at 1000 ppm and 1500 ppm after 10 hours of ex-
posure (Fig. 5). The observations regarding the effect of different
concentrations (in ppm) of sulfonamide IGR’s at different exposure
periods (in hours) on percent larval mortality of G. mellonella have
been tabulated in Table 3.
2
Medium
3
Low
4
Undefined
5
Molecules with one or more unknown Alog P calculation
ADMET CYP2D6
Predicted Class
Value
0
1
Noninhibitor
Inhibitor
None of the treatments were significantly effective at 1000 ppm
concentration after exposure of 2 hours. Although there was a pro-
gressive increase in mortality with an increase in the exposure pe-
riod (Fig. 6a), the overall rate of mortality remained low at this
concentration. T1 and T2 showed maximum efficacy of 100.00 %
kills at 8 hours exposure period. T6 and T8 with the same concen-
tration exhibit 90.00 and 93.33 % mortality at the exposure period
of 8 hours, respectively. Mortality did not exceed 60.00 % in the
rest of the treatments for the same exposure period. Increasing the
exposure periods up to 10 hours, T6 and T8 attained the 100.00 %
larval mortality followed by T4 and T7 at the same concentration.
Mortality did not exceed 84.00 % in all other formulations. Trends
were similar at 1500 ppm concentration. T3 formulation was found
to be least effective with 16.67 % kill at 2 hours exposure time
while T8 formulation at the same exposure period exhibited 56.67
% mortality (Fig. 6b). While percent mortality in T8 enhanced from
56.67 to 100.00 % at 6 hours exposure period, T2 showed the en-
hancement from 53.33 % to 100.00 % at 6 hours followed by T1
from 46.67 % to 100.00 % mortality at similar exposure periods. T6
also showed an increase from 26.67 % to 100.00 % kill. Likewise, T7
exhibited the enhancement from 23.33 % to 100.00 % kill at a sim-
ilar exposure period (6 hours) at the same concentration. In the
case of T4 formulation 90.00 %, larvae were killed when exposed
to 1500 ppm for 6 hours. T3 and T5 were least effective register-
ing 73.33 and 83.33 % mortality and these values were insignificant
to each other (Table 3). The highest percent of larval mortality at
2000 ppm concentration up to 4 hours exposure was shown by T1
(100.00 %), T2 (100.00 %) followed by T7 and T8. Likewise, T4, T5,
and T6 also showed higher mortality of 93.33 % at the same expo-
sure period of 4 hours at the same concentrations. Formulation T3
showed the least 86.67 % mortality which is statistically insignifi-
cant to others (Fig. 6c). However, at 6 hours of exposure, the rest
of the formulations showed the 100.00 % larval mortality. Overall,
there occurred an increase in concentration and an increase in the
exposure period. Clear morphological changes have been observed
at the fourth larval instar of G. mellonella (Fig. 6(a-c)).
ADMET Hepatotoxicity
Predicted Class
Value
0
1
Nontoxic
Toxic
ADMET (plasma protein binding level) PPB
Level
Description
0
1
2
Binding is <90%
Binding is ≥ 90%
Binding is ≥ 95%
ADMET aqueous solubility level
Level
Description
0
1
2
3
4
5
6
Extremely Low
No, very low, but possible
Yes, low
Yes, good
Yes, optimal
No, too soluble
Molecule with one or more unknown AlogP98 types.
action of substituted aniline with acid chlorides in dry benzene.
N-(1-isopropyl-2-oxo-2-anilino-ethyl) benzene sulfonamide and re-
lated compounds (T3-T8) are new in literature and fully identified
based on their spectral data (IR, 1H NMR, 13C NMR, and ESI-MS
analysis). All the compounds have been obtained as pure solids.
(Supplementary Data)
3.2. Bioassay of synthesized analogs on G. mellonella
All the analogs have been screened for their IGRs and pestici-
dal action against fourth instar larvae of Galleria mellonella (Honey-
comb pest). The population of ten larvae each in three replication
sets has been studied for larval mortality at different concentra-
tions (in ppm) having variable exposure periods (in hours). Table 2
provides the results of IGR action of all the synthesized analogs
(T3-T8) along with in-use IGRs (T1 and T2) during the treatment of
fourth instar larvae of G. mellonella (wax moth) at different con-
centrations (10-100 ppm) at different exposure period (12 hrs.-72
hrs.). The highest mortality rate has been observed at 72 hours of
exposure time. LC50 value for all the synthesized analogs falls in
the range of 12.80 to 21.69 ppm in comparison to commercially
in use IGRs like Pyriproxyfen (T1) and Fenoxycarb (T2) having LC50
value 9.99 and 10.12 ppm respectively. Synthesized analogs like T3,
T4, T5, T7, and T8 showed the LC50 value (12.80-13.94 ppm) very
close to in use IGRs (Fig. 4). The overall pattern of LC50 for all the
analogs in comparison to in use IGRs against fourth larval instar
of G. mellonella was - T1>T2>T8>T7>T4>T5>T3>T6 and the pat-
tern for LC90 is T8>T7>T2>T5>T1>T4>T3>T6. Among the synthe-
sized series (T3-T8), analog T8 exhibited the highest mortality rate
having LC50 12.80 ppm at concentrations ranging from 10 to 100
ppm after 72 hours of exposure time (Table 2 and Fig. 4). Further,
the pesticidal action of all the analogs (T1-T8) has been studied
3.3. JHBP- JHAs Interactions
JHBP has been proposed to be the binding site of natural ju-
venile hormone. Detailed structural studies of JHBP of G.mellonella
with JH-III has been solved [46]. In rational bioactive molecular
design, an accurate estimate for the binding free energy is impor-
tant to justify the difference in binding affinity between different
JH analogs towards JH binding protein (JHBP). JHAs interactions
with JHBP depends upon specific and non-specific forces present
inside the binding pocket of the receptor protein. Electrostatic in-
teractions of structurally diverse data sets including series of JH
analogs vary mainly from each other by the number of C-atoms,
6

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Table 2
Probit analysis of sulfonamide analogs for IGR action (T1-T8) against G. mellonella
% Larval mortality
95% Confidence
Limits
95% Confidence
S.
LC50
LC90
Regression
Conc (ppm)
Limits
No.
Analogs
(ppm)
(ppm)
Equation
10
25
35
50
100
LCL
UCL
LCL
UCL
1.
2.
3.
4.
5.
6.
7.
8.
T1
T2
T3
T4
T5
T6
T7
T8
44
46
41
41
39
32
39
39
59
61
56
56
54
50
57
57
67
68
70
67
68
57
71
75
78
79
82
74
79
68
79
82
89
89
89
85
86
82
89
89
9.99
2.44
3.69
8.28
5.17
5.93
9.83
6.55
6.67
17.53
16.54
28.03
22.01
21.95
33.38
20.00
18.93
153.27
131.69
113.23
161.70
141.48
205.75
110.93
96.91
75.00
73.22
101.10
83.68
81.23
102.99
71.95
66.12
231.54
190.17
294.57
239.73
201.73
308.51
149.91
127.70
3.53+1.25X
3.52+1.30X
3.17+1.51X
3.38+1.30X
3.26+1.40X
3.12+1.36X
3.13+1.53X
3.08+1.60X
10.12
13.70
13.59
13.94
21.69
13.28
12.80
Table 3
Effect of different concentrations of IGRs (T1-T2) and synthesized analogs (T3-T8) at different exposure periods on per cent larval mortality of G. mellonella (in vivo)
Per cent larval mortality at concentration (ppm)
1000 ppm
1500 ppm
2000 ppm
Exposure period (hours)
Exposure period (hours)
Exposure period (hours)
Formulatios
2
4
6
8
10
2
4
6
8
10
2
4
6
8
10
T1
0.00
0.00∗
56.67
48.93∗
90.00
71.57∗
100.00
90.00∗
100.00
90.00∗
46.67
43.08∗
83.33
66.15∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
T2
T3
T4
T5
T6
T7
T8
0.00
0.00∗
43.33
41.16∗
70.00
57.00∗
100.00
90.00∗
100.00
90.00∗
53.33
46.92∗
90.00
75.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
0.00
0.00∗
10.00
18.44∗
26.67
31.00∗
40.00
39.15∗
60.00
50.85∗
16.67
23.86∗
36.67
37.14∗
73.33
59.01∗
100.00
90.00∗
100.00
90.00∗
70.00
61.92∗
86.67
72.79∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
0.00
0.00∗
16.67
23.86∗
33.33
35.22∗
60.00
50.85∗
83.33
66.15∗
26.67
31.00∗
50.00
45.00∗
90.00
71.57∗
100.00
90.00∗
100.00
90.00∗
60.00
50.85∗
93.33
81.15∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
0.00
0.00∗
16.67
23.86∗
46.67
43.08∗
56.67
48.85∗
70.00
57.00∗
26.67
31.00∗
53.33
46.92∗
83.33
66.15∗
100.00
90.00∗
100.00
90.00∗
63.33
52.78∗
93.33
77.71∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
0.00
0.00∗
33.33
35.01∗
66.67
54.78∗
90.00
75.00∗
100.00
90.00∗
26.67
31.00∗
63.33
52.78∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
86.67
76.93∗
93.33
81.15∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
0.00
0.00∗
16.67
23.86∗
33.33
35.22∗
60.00
50.85∗
83.33
66.15∗
23.33
28.78∗
53.33
46.92∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
90.00
75.00∗
100.0
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
0.00
0.00∗
33.33
34.93∗
63.33
53.15∗
93.33
81.15∗
100.00
90.00∗
56.67
48.93∗
93.33
77.71∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
96.67
83.86∗
100.0
90.00∗
100.00
90.00∗
100.00
90.00∗
100.00
90.00∗
CD0.05 Analogs (T1-T2, T3-T8) x Concentration (ppm) x Exposure period (in hours 4.82
T1: Pyriproxyfen (Standard); T2: Fenoxycarb (Standard)
T3: N–(1-isopropyl-2-anilino-2-oxo-ethyl) benzene sulphonamide; T4: N–(1-isopropyl-2-anilino-2-oxo-ethyl) toluene- sulphonamide
T5: N-(1-isopropyl -2- p-chloroanilino-2-oxo -ethyl) benzene-sulphonamides; T6: N-(1-isopropyl-2- p-chloroanilino-2-oxo–ethyl) toluene-sulphonamides
T7∗:N-(1-isopropyl-2-p-nitroanilino-2-oxo-ethyl)benzene-sulphonamides;T8:N-(1-isopropyl-2-p-nitroanilino-2-oxoethyl)toluene-sulphonamides
angular transformed values.
the number of heteroatoms/functionality groups on the aromatic
moiety, etc. [67].
tively. Lower binding energy profile is due to the presence of two
different functional groups at the terminals of the main chain. This
structural deviation leads to strain at the main chain and prevents
the folding of the analog inside the binding pocket of JHBP. There
was a large deviation in the value of the total internal energy of
synthesized sulfonamide analogs (T3-T8) over commercial IGRs i.e
Pyriproxyfen (T1) and Fenoxycarb (T2) (Fig. 7(a-b)).
Docking identifies the correct position of the molecule inside
the binding pocket of the receptor and also predicts affinity level
between the molecule and the receptor [24,41,9,7,62,63]. AutoDock
program has been applied to investigate the binding energy pro-
file (B.E. (ꢀGb) Kcal/mol), inhibition constant (Ki in μM) of sulfon-
amide series (T3-T8) and in use IGRs (T1-T2) with JHBP of G. mel-
lonella (2RCK) (Fig. 3). The energy profile was sequenced according
to the binding energy and inhibitory constant (Ki) (Table 4).
All synthesized analogs illustrate a low binding energy profile
than Fenoxycarb but higher than Pyriproxyfen upon interaction
with JHBP. Among synthesized analogs, analog T8 having lower
binding energy followed by T7, T3, T4, T5, and T6 analogs, respec-
The fluctuating energy profile of synthesized analogs is due to
the variation of substituted groups at the rings i.e., A & B (Table 4).
Torsional energy is associated with the degree of freedom of the
molecule and more is the degree of freedom larger will be the pos-
sibility of change in the conformation inside the pocket. The polar-
NO2 group in analogs T7-T8 exhibited a lowering in binding energy
profile. As olfactory sensations of the insects require some degree
7

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Table 4
Free energy of binding (ꢀGb, Kcal/mol), Inhibitory constant (Ki in μM) and Hydrogen bond interactions along with distances (A°) of IGRs (in use T1-T2 and synthesized T3-T8)
with JHBP of G. mellonella
InhibitionConst Binding Energy Docking
Energy Torsional energy Ki(μM∗, nM∗∗
)
Binding
Distances
(A)
Number in
Cluster
S. No. IDs Ligands
(Kcal/mol) (Kcal/mol) (Kcal/mol)
interactions
ͦ
1.
T1
5.32∗
-7.18
-8.25
0.60
O2……. OH
THR 22
2.781
2.587
99
O5……...OH
THR 22
2.
T2
136.43∗
-5.27
-0.69
1.19
O6........HN
LYS 218
1.779
42
3.
T3
3.35∗
-7.74
-10.3
1.79
O5………NH 2.019
28
LYS 218
2.119
NH6……OH
THR 22
4.
T4
7.03∗
-7.03
-10.04
1.79
O-S-
1.879
27
O…….NH LYS 2.001
218
NH6………OH
THR 22
5.
6.
7.
T5
T6
T7
7.98∗
21.02∗
1.23∗
-6.96
-6.38
-8.06
-10.04
1.79
1.79
2.09
O5….HN LYS 2.002
2
218
2.096
NH6…..OH
THR 22
-9.47
OSO…….HN 1.669
3
LYS 218
2.131
NH3………OH
THR 22
-11.25
OSO….HN
LYS 218
1.976
1.706
17
ONO……HN
LYS 85
8.
T8
941.82∗∗ -8.22
-11.61
2.09
NH6……..OH 1.931
24
TYR 130
ONO——-HN
LYS 85
1.701
8

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 4. Concentration-mortality response of different analogs to fourth-instar larvae of G. mellonella by topical application method.
of lipid solubility, therefore, hydrophobicity/lipophilicity of the re-
pellents is likely to be an important factor for potent repellent ac-
tivity [35,60,39,42,18,78]. Inhibitory constant (Ki) likewise as B.E.
profile for all the synthetic analogs, and in use IGRs (T1-T2). Syn-
thesized analogs T8, T7, and T3 possess lower value for inhibitory
constant (Ki) in comparison to the rest of the analogs (Table 4). The
values of inhibition constant of these synthetic analogs are compa-
rable to Pyriproxyfen (T1).
ing energy behavior over synthesized analogs with JHBP of G. mel-
lonella (Fig. 8).
Analogs T7 and T8 having -NO2 group at the para position to
ring B, forming H-bond with pocket residues THR 22, LYS 85, 218
and TYR 130 (Table 4) adopts an extended conformation inside the
binding cavity with a decrease in binding energy in comparison to
T5 and T6 analogs with p-substituted Cl group. Closer the packing
of the analogs stronger will be the JHAs – JHBP complex and effec-
tive will be the interactions with decreased binding energy. There-
fore, it is concluded that functionalities present at position 2nd, 5th,
and 6th interact effectively via H-bonding with amino acid residues
inside the binding pocket. (Fig. 8).
Synthetic IGR, Pyriproxyfen (T1) having a functional group at
2nd and 5th position showed H-bonding with THR 22. The pyridine
ring being hydrophobic moiety showed additional H-bond interac-
tions with PRO 146 amino acid residue of the pocket (Fig. 8).
In Fenoxycarb (T2), the group at the 6th position formed H-
bonding with LYS 218. It also showed additional interactions with
THR22, TYR 130 which could be the reason for their good bind-
Synthesized analogs showed additional H-bond interactions
with amino acid residues- CYS 10, ALA 21, 220, PRO146, SER129,
HIS 207, ARG 210, 214 at the binding pocket which confirms
9

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 5. Effect of different concentration (in ppm) at different exposure period (in Hours) on percent larval mortality of G. mellonella
10

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 6. (a) Physiological changes on G. mellonella larvae after applying 1000 ppm concentrations of N-(1-isopropyl -2- p-nitroanilino-2-oxo ethyl)-p-toluene sulfonamide (T8)
at exposure period of 6 hrs. in comparison to Pyriproxyfen (T1) and Fenoxycarb (T2);
(b): Physiological changes on G. mellonella larvae after applying 1500 ppm concentrations of N-(1-isopropyl -2- p-nitroanilino-2-oxo ethyl)-p-toluene sulfonamide (T8) at
exposure period of 4 hrs. in comparison to Pyriproxyfen (T1) and Fenoxycarb (T2);
(c): Physiological changes on G. mellonella larvae after applying 2000 ppm concentrations of N-(1-isopropyl -2- p-nitroanilino-2-oxo ethyl)-p-toluene sulfonamide (T8) at
exposure period of 2 hrs. in comparison to Pyriproxyfen (T1) and Fenoxycarb (T2);
11

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 6. Continued
Table 5
Additional interactions (bold – common, normal- additional) of the IGRs (in use T1-T2
and synthesized T3-T8) with amino acid residues at the binding pocket of JHBP of G.
mellonella
Additional Interactions of the ligands with
S.No.
IDs
T1
amino acid residues inside the binding pocket
THR 22, LYS 85,218, PRO∗∗ 146∗∗, THR 148
1.
2.
3.
T2
T3
THR 22, TYR 130, LYS 218
ALA 21, THR22, HIS∗ 207, ARG∗∗ 210-214, SER
∗129, TYR 130, PRO∗∗146, GLU 147, THR 148, LYS
218
4.
5.
T4
ILE 18, ALA, THR 22, SER∗ 129, TYR 130,
PRO∗∗146, GLU 147, THR 148, HIS∗207, ARG∗∗210,
LYS 218, ALA21, 220
T5
T6
T7
T8
CYS10, THR22, ASN 94, TYR 130, TYR142, LYS
218, ALA220
CYS10, ALA 21, THR22, TYR 130, LYS 92, 218,
ALA 220,
6.
7.
ALA 21, THR 22, LYS 39,85, 133,218 TYR 130,
GLU 147, HIS∗ 207, ARG∗∗ 210,214, ALA220
THR 22, LYS 39,85,133,218, TYR 130, GLU 147,
ALA21,220, HIS∗ 207, ARG∗∗ 210, 214
8.
∗
∗∗ Mixed codon
Strong codon,
the hydrophobic, acidic, and basic nature of the binding pocket
(Table 5). The amino acid moieties having additional interactions
are referred to as the strong codon for effective binding. They had
shown a strong tendency to form H-Bond with JH analogs [73].
These simulation results corroborate with the spectroscopic studies
of the binding of JH-II with JHBP of G. mellonella [47].
3.4. ADMET Prediction
It is of utmost importance to design and develop effective in-
secticide and pesticide, however, these chemicals should not be
toxic to the environment and living organisms. As the direct ani-
mal test is time-consuming, therefore, in silico model based on the
structure-activity relationship (SAR) obtained from past knowledge
could be very useful in predicting the toxic effect of synthesized
JH analogs. It is important to predict toxicity before the develop-
ment/ launch of the chemical/drug for any application. Therefore,
to predict the side effects of new candidate compounds, ADMET
simulation proved to be one of the most effective methods.
The addition of the aromatic ring at one terminal increased the
hydrophobic character of the analog hence enhanced π – cation
interactions which stabilize the analogs inside the pocket (Fig. 8).
Docking studies have shown that more/increased would be the hy-
drophobic character in JH analogs; more will be the activity in
terms of binding energy profile [7,62,63].
12

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 7. (a) Binding energy profile of IGRs (T1-T8); (b): Energy variations (intermolecular, internal and torsional energy) of all the analogues with juvenile hormone binding
protein of G. mellonella .
ADMET predictions were carried out to evaluate the drug-
likeness of sulfonamide analogs and the properties were reported
in table 6 along with biplot Fig. 9.
ADMET_PPB (Plasma Protein Binding) shows the extent of binding
of analogs (T1-T8) with the carrier protein is greater than 2 corre-
sponds to binding greater than 95%. The aqueous solubility of the
analogs is low to optimal indicates is bioavailability. The value of
the absorption level for all (T1-T8) analogs corresponds to value
2 indicates low intestine absorption. ADMET_CYP2D6 values pre-
dict the non-inhibitor nature of analogs in the human system. The
value of CYP_2D6 is less than even zero. All the analogs having
zero and negative CYP_2D6 values indicate their non- toxic na-
ture. ADMET Hepatotoxic data indicates the non-toxic nature of all
the analogs (T1-T8) to the liver. The Log P is used to estimate the
lipophilicity, thus the information of H-bonding characteristics as
The pharmacokinetic profile of analogs was predicted using
six precalculated ADMET models provided by Discovery Studio.
Fig. 9 biplot shows two analogs 95 % and 99% confidence ellipse
corresponding to HIA and BBB models. PSA has an inverse relation-
ship with human intestinal absorption and thus cell wall perme-
ability. ADMET_BBB (Blood-Brain Barrier) predicts the blood-brain
penetration power of analogs after oral administration. The val-
ues of BBB level for (T1-T2) coming out to be 0 and 1 indicates
a high BB penetration level whereas in the case of synthesized JH
analogs (T3-T8) values come to be 2 i.e. medium penetration level.
13

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 8. H-bond interactions of in use IGRs Pyriproxyfen and Fenoxycarb (T1 & T2), synthesized analogs (T3 – T8) with juvenile hormone binding protein of G. mellonella. (Juve-
nile hormone analogs are shown in blue. Hydrogen bond interactions between amino acid residue and analogs are shown in green-colored arrows and π-cation interactions
are shown in yellow colors)
obtained by calculating the Polar Surface Area could be taken into
consideration along with Log P calculation (Table 6).
Further, all these synthetic JH analogs were subjected to toxi-
city predictions by computer-assisted technology (TOPKAT) mouse
male and female as per National Toxicology Predictions (NTP). Data
analysis indicates the non-carcinogenic and non- skin irritant na-
ture of synthesized analogs (T3-T8) in comparison to synthetic IGRs
(T1&T2) (Table 7).
To predict the cell permeability of JH analogs (T1-T8) a model
with descriptors like- ADMET AlogP98 and ADMET PSA_2D with a
bi-plot comprising 95% and 99% confidence ellipse was considered.
These ellipses indicate the region where all the compounds get ab-
sorbed. All analogs exhibit a safer range in ADMET as shown in bi-
plot (Fig. 9). The poor pharmacokinetic profile and toxicity compli-
cations are generally responsible for the dropout of the lead can-
didate/analog during the clinical trial.
3.5. Frontier Molecular Orbital Analysis
The frontier orbital energy gap helps to characterize the chemi-
cal reactivity and kinetic stability of the molecule. A molecule with
14

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Table 6
ADMET prediction of in use IGRs (T1-T2) and synthesized JHAs (T3-T8):
Analogs
AlogP
PSA_2D
PPB
Hepatotoxicity
CYP2D6 binding
Aqueous solubility
BBB penetration
Intestinal absorption
T1
T2
T3
T4
T5
T6
T7
T8
4.6
3.2
2.7
3.1
3.3
3.8
2.5
3.0
20.19
47.97
77.52
77.52
77.52
77.52
120.34
120.34
True(highly bounded)
True(highly bounded)
True(highly bounded)
True(highly bounded)
True(highly bounded)
True(highly bounded)
True(highly bounded)
True(highly bounded)
False(non-toxic)
False(non-toxic)
False(non-toxic)
False(non-toxic)
False(non-toxic)
False(non-toxic)
False(non-toxic)
False(non-toxic)
False(non-inhibitor)
False(non-inhibitor)
False(non-inhibitor)
False(non-inhibitor)
False(non-inhibitor)
False(non-inhibitor)
False(non-inhibitor)
False(non-inhibitor)
2(low)
3(good)
3(good)
2(low)
2(low)
2(low)
2(low)
2(low)
0(very good)
1(good)
0(good)
0(good)
0(good)
0(good)
0(good)
0(good)
0(good)
0(good)
2(medium)
2(medium)
2(medium)
2(medium)
2(medium)
2(medium)
Abbreviations: AlogP, the logarithm of the partition coefficient between n-octanol and water; PSA, polar surface area, CYP450 cytochrome P450, PPB plasma protein binding,
BBB blood-brain barrier
Fig. 9. Prediction of analogs absorption for various PA considered for IGR activity. Discovery Studio 2.1 (Accelrys, San Diego, CA) ADMET Descriptors, 2D polar surface area
(PSA_2D) in A˚2 for each analog is plotted against their corresponding calculated atom-type partition coefficient (ALog98). The area encompassed by the ellipse is a prediction
of good absorption with no violation of ADMET properties. The plot of Polar Surface Area (PSA) vs. LogP for a standard and test set showing the 95% and 99% confidence
limit ellipse corresponding to the Blood-Brain Barrier and Intestinal Absorption models.
Table 7
Toxicity prediction of synthetic IGRs (T1&T2) and JH analogs (T3-T8):
Analogs
Topkat mouse female ∗NTP prediction
Topkat mouse male ∗NTP prediction
Mouse female #fda
Mouse male FDA
Topkat skin irritancy
T1
T2
T3
T4
T5
T6
T7
T8
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
NC
None
None
None
None
None
None
None
None
∗NTP – National Toxicology Predictions, #fda- food and drug administration, NC- Non-Carcinogen
a small frontier orbital gap is more polarizable and is generally as-
sociated with a high chemical reactivity, low kinetic stability, and
is also termed as a soft molecule [72,26,55,56]. The HOMO and
LUMO energies are used as chemical reactivity ratios and are usu-
ally associated with other indexes such as electron affinity and ion-
ization potential. The energy of HOMO is directly related to the
ionization potential and LUMO energy is directly related to the
electron affinity. The energy difference between HOMO and LUMO
orbitals is called as energy gap which serves as an important sta-
bility factor for the proposed analogs.
15

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Fig. 10. Graphical view of DFT originated wavefunctions (molecular orbitals) in the form of HOMO-LUMO orbitals from occupied and virtual molecular orbitals of titled
analogs (T1-T8) visualized by Gaussview 3.0. Red and green color distribution represents positive and negative phase in molecular orbital wave function, respectively.
The HOMO-LUMO energy gap for the analogs T8 and T7 is
1.6 eV which confirms that the proposed analogs have a stable
structure. The lower the energy gap, the more easily electrons
are excited from the ground state to the excited state (Fig. 10,
Table 8).
3.6. Global Reactivity Descriptors
Global reactivity descriptors act as a bridge between the stabil-
ity of the structures and global chemical reactivity. Based on fron-
tier molecular orbital (FMO) energies the global reactivity descrip-
16

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
Table 8
The HOMO and LUMO energies and the energy gap between HOMO and LUMO
(࢞Eg) in eV units at DFT/6-31+G (d, p) level in the gas phase
S.No
Analogs
HOMO (in eV)
LUMO (in eV)
Energy Gap (࢞Eg in eV)
1.
2.
3.
4.
5.
6.
7.
8.
T1
T2
T3
T4
T5
T6
T7
T8
-6.751
-5.934
-6.016
-5.989
-6.179
-6.125
-6.587
-6.533
-1.089
-3.838
-4.682
-4.600
-4.764
-4.682
-4.900
-4.900
-5.662
-2.096
-1.334
-1.388
-1.415
-1.443
-1.688
-1.633
tors such as electronegativity (χ), chemical potential (μ), global
hardness(η), global softness (S), and global electrophilicity index
(ω) have been calculated for aniline based sulfonamide analogs
(T3-T8) along with in-use IGRs (T1-T2) (Table 9). The concept of
these parameters is related to each other:
Chemical potential (μ)= 1 (ELUMO + EHOMO
)
2
Electronegativity (χ)= - μ= - 1 (ELUMO + EHOMO
)
2
Global Hardness (η)= 1 (ELUMO − EHOMO
)
2
Softness (S) = 1/η
Electrophilicity (ω) = μ2/2η
The electrophilicity index helps in describing the biological ac-
tivity of the proposed analogs (T3-T8). Considering the chemical
hardness, a large HOMO-LUMO gap means- a hard molecule (more
stable & less reactive), and small HOMO-LUMO means -a soft
molecule. One can also relate the stability of the analog with the
least energy gap which is related to high reactivity. The analogs
T7 and T8 have the lowest energy gap (Egap= 1.60 eV) and this
lower energy gap makes the analog soft. The analog T4 has the
highest HOMO energy (EHOMO= -5.989eV) known to the best elec-
tron donor. The analog T8 has the lowest LUMO energy (ELUMO=-
4.900 eV) which signifies that it can be the best electron acceptor.
The two properties like I (potential Ionization) and A (affinity) can
be used to calculate the absolute electronegativity and the absolute
hardness. These two parameters are related to the one-electron or-
bital energies of the HOMO and LUMO respectively. Analog T4 has
the lowest value of the potential ionization (I = 5.989 eV), so that
will be the better electron donor. Analog T8 has the largest value
of the affinity (A = 4.900 eV), so it is the better electron accep-
tor. The chemical reactivity varies with the structure of molecules.
Electronegativity and chemical hardness help to predict the for-
mation of the chemical bonds and the physical, chemical prop-
erties of the analogs. Chemical hardness is related to the stabil-
ity and reactivity of a chemical system, it measures the resistance
to change in the electron distribution or charge transfer. Chemical
hardness (softness) value of analog T3 (η = 0.6670 eV, S = 1.499
eV) is lesser (greater) among all the analogs (T1-T8). Thus, analog
T3 is found to be more reactive than all the analogs T1-T8. Analog
T7 & T8 possess higher electronegativity value (χ = 5.7 eV) than
rest, hence; it is the best electron acceptor. The electrophilicity in-
dex (ω) measures the propensity or capacity of a species to ac-
cept electrons. The value of ω for T3 (ω = 21.448eV) indicates that
it is the stronger nucleophile whereas analog T7 is the strongest
electrophiles among all analogs. Analog T7 & T8 have the smaller
frontier orbital gap so, are more polarizable and associated with a
high chemical reactivity, low kinetic stability, and termed as a soft
analog. Ionization energy is a fundamental descriptor of the chem-
ical reactivity of atoms and molecules. High ionization energy in-
dicates high stability and chemical inertness, and small ionization
energy indicates high reactivity of the atoms and molecules. Ab-
solute hardness and softness are important properties to measure
molecular stability and reactivity. It is apparent that the chemical
hardness fundamentally signifies the resistance towards the defor-
17

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
mation or polarization of the electron cloud of the atoms, ions, or
molecules under small perturbation of chemical reaction.
pocket of the JH receptor protein as well as the hydrophobic nature
of JHA’s played a vital role in the binding process. The study also
revealed that the most active compounds must possess an active
atom (O/N) in the molecules. The presence of an Electron with-
drawing moiety is essential for high activity [61].
Conclusions
Quantum chemical descriptors calculated by the density func-
tional theory (DFT) method were used for establishing the
structure-activity relationship between descriptors and bioactivity.
Electrophilicity index, polarity, chemical softness, or hardness are
most likely responsible for their effectiveness as good IGRs. Fur-
ther, all the analogs were also tested for their toxicity prediction
using the ADMET tool executed in the discovery studio software.
Outcomes from ADMET analysis were compared with the standard
JH analogs (IGRs T1 & T2) which already proved to be non-toxic in
the literature, confirms the eco-friendly and biodegradable nature
of compounds. Interestingly, the results of bioassay on G. mellonella
are supported by computational results, both by docking and DFT
study. A comparison between bioassay and virtual screening has
been drawn in figure 11.
The proposed work is a part of a synthesis, in vivo efficacy,
docking, ADMET, and Frontier Molecular Orbital analysis of effec-
tive and environmentally safe JH analogs to be Insect Growth Reg-
ulators (IGRs). We have synthesized series of analogs containing
activating groups like sulfur, L-amino acids, (un) substituted ani-
line derivatives. Sulfur being the essential nutrients to the plants
also plays an important role in chlorophyll during photosynthe-
sis and showed important role in agrochemicals. Sulfur-containing
compounds are biodegradable finds a unique place in the Phar-
maceutical and pesticidal industry [21]. Sulfonamide functionality,
aniline bearing – chloro/ nitro group at the para position are the
key factors for the enhanced bioactivity of the analogs in compar-
ison to in use IGRs (T1 &T2) [35,39,42,18,78]. In Vivo Evaluation of
T3-T8 along with commercial IGRs T1&T2, on G. mellonella has been
carried out with diverse concentrations (in ppm) with the varied
exposure time (in hours). The general picture of sulfonamide for-
mulations used in this study could be rated as T8 > T7 > T6 > T3
> T5 > T4 i.e. in decreasing order of their effectiveness against G.
mellonella.
The theoretical trend for binding energy followed the pattern:
T8>T7>T3>T1>T4>T5>T6>T2. The binding energy values for all
the analogs occurred within the range of 2kcal/mol. The docking
study clearly showed the similar behavior of synthesized analogs
in comparison to in use IGRs (T1 & T2) against JHBP of G. mel-
lonella. These results were further augmented by in vivo findings.
Analogs T7 & T8 at 2000 ppm at 4 h of exposure period showed
a similar activity like that of T1 and T2 by yielding 100 % mor-
tality. Further decreasing concentration to 1500 ppm at 6 hrs. ex-
posure period; 100 % mortality has been achieved by T6, T7 &T8
analogs. Thus, analog T8 having leading behavior over T1&T2 as per
in vivo study. Interestingly, bioassay results are being supported by
the theoretical outcome (Fig. 11).
Virtual screening of all the analogs (T1-T8) has been performed
using JHBP (2RCK) of G. mellonella on AutoDock 4.2 software.
Molecular docking suggests that juvenile hormone analogs with
minimum binding energy will fit better inside the binding pocket
of the receptor protein [46]. Six synthetic analogs reported in this
paper differ from one another based on substituent groups at-
tached at aromatic ring A and B. Synthesized JHAs (T3-T8) bears
lower binding energy profile as compared to Fenoxycarb (IGRs),
but higher than Pyriproxyfen (IGRs). Among synthesized series (T3-
T8); analog T8 bears the lowest energy profile followed by T7 and
T3 analogs. Methylated analogs (T8) having nitro functionality at
the para-position of aromatic B ring results in the lowest binding
energy in comparison to the chloro analogs. Some inter or intra-
atomic interactions are induced by –NO2 group substitution at
para- position of ring B which further believes to affect the binding
mode. Overall, the study confirms that all synthesized analogs (T3-
T8) showed binding energy in the range of ࢞G°≥2kcal/mol hence
proposed to be effective IGRs in comparison to in use (T1 &T2)
IGRs. This study has shown the hydrophobic nature of the binding
The incorporation of different functionalities at the main skele-
ton dictates the binding pattern of JH to a receptor protein (JHBP).
The number of JH analogs have been synthesized and evaluated on
these lines. We have incorporated different design features that are
very common in other bio-applications like- sulfonamide, amide
in the main chain, and incorporation of hydrophobic moieties at
the three sides of the molecules (Fig. 1c). Comparing this series
(T3-T8) with previously reported heterocyclic and aza based sul-
fonamide Juvabione series, [7,62,63], the addition of sulfonamide
functionality at the main chain skeleton, the aromatic substitution
at A & B ring, increase in hydrophobicity at the main chain, initi-
Fig. 11. Comparison of in silico study and in vivo screening (at 1500 ppm for 4 hrs.)
18

P. Sharma and P. Awasthi
Journal of Molecular Structure 1231 (2021) 129945
ates /stabilizes the ligand-receptor protein complex. The hydropho-
bic region of different synthesized analogs tends to come together
to have an effective contribution to binding free energy (Fig. 1c).
The present analysis also proposes the flexible behavior of the syn-
thesized analogs in the Pharmaceutical industry in addition to the
agrochemical industry. The combined bioassay and in silico study
of JHAs has revealed important structural features necessary for
specific interactions that these Juvenoids exhibit with JHBP of the
receptor protein. The present study indicates that these JH analogs
(mimics of JH) could serve as the basis for future design to find
new derivatives with multiple activities to counteract lepidopteran
insect species. We are in progress on the detailed investigation on
lead compounds (T7, T8) and their environmental impact, which
will be published in due course of time.
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Declaration of Competing Interest
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The authors declare that there is no conflict of interests regard-
ing the publication of this paper.
Acknowledgment
The authors thank the Sophisticated Analytical Instrument Fa-
cility, Punjab University, Chandigarh, for recording FT-IR, NMR (1H
and 13C), and mass spectra. We are also thankful to the Direc-
tor, Institute of Biotechnology, and Environmental Science- Neri
(Hamirpur) H.P for extending all help in performing biological
studies.. One of the authors Priyanka Sharma acknowledges MHRD,
Government of India for a Ph.D. fellowship.
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Supplementary materials
Supplementary material associated with this article can be
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