A Bioinformatics Approach Reveals the Insecticidal Property of Morinda tinctoria Roxb. against the Cotton Bollworm Helicoverpa armigra

 

Praveena. A¹*, Sanjayan K.P²

¹Department of Biotechnology, Prathyusha Engineering College, Thiruvallur-602 025  India.

²Department of Advanced Zoology and Animal Biotechnology, Guru Nanak College, Chennai-600 042, India.

 

ABSTRACT:

Botanical insecticides have been acknowledged as attractive alternatives to synthetic chemical insecticides for pest management as they apparently pose little hazard to the environment or to human health. A number of plant substances have been considered for use as insect antifeedant and repellent. Studying the insecticidal property of plants against the insects is a difficult process. Hence we have done an insecticidal property analysis of phytochemicals derived from Chloroform, Ethyl acetate and Methanol extracts of root-bark and fruit of Morinda tinctoria against the cotton bollworm Helicoverpa armigera using bioinformatics approaches such as molecular structure property analysis, homology modeling and docking studies. Nine compounds from the root-bark and fruit extract of M.tinctoria were observed to strictly follow Tice rule and 8 compounds present in the extract and also known to have insecticidal property from literature were selected as ligands. The enzymes Acetylcholinesterase, Carboxylesterase and Protease of Helicoverpa armigera were decided as targets for the docking studies. The 3D structure of targets was modeled and the interaction between the enzymes and phytochemicals were studied using molecular docking studies in order to find effective insecticide.

 

 

INTRODUCTION:

The use of plant insecticides has a long-term tradition in India. Some of the botanicals like neem, pyrethrum, tobacco, karanj, mahua and sweet flag have already attained the status of potential pesticides of plant origin to be used in integrated pest management programmes for crop field insects¹. At present, several dozens of plant insecticide are being tested worldwide, based on various extracts, especially of the families Rutaceae, Lamiaceae, Meliaceae and Asteraceae.

 

Although plant pesticides have been studied in many laboratory tests^2,3, very few studies are available that present results from practical use, and there is a great lack of new technologies usage such as bioinformatics to increase the biological efficiency comparisons of several products on multiple pest species. The biological activity of substances is governed by their properties, which in turn are determined by their chemical structure. Morinda tinctoria is a medicinal plant predominantly grows as a weed tree in vacant agricultural land. Various biological activities such as antimicrobial activity of M. tinctoria have been explained by many researchers⁴. In the present study, phytochemicals derived from root-bark and fruit of Morinda tinctoria has been taken and studied against the enzymes such as Acetycholinesterase, Carboxylesterase and Protease of H.armigera, major polyphagous noctuid pest in Asia, causing heavy damage to agricultural, horticultural and ornamental crops. This work will help to identify the compounds of insecticidal potential.

 

MATERIALS AND METHODS:

Molecular Property Analysis

The molecular properties of the compounds identified from the GC-MS were analysed based on the Tice rules using Molinspiration server and NCBI PUBCHEM database.

 

Molecular Modeling

Template Selection

The 3D structure of the Acetylcholinesterase, Protease and Carboxylesterase (Targets) of H.armigera were modeled based on the template selected using BLASTp. In order to determine homologous sequences, the amino acid sequence of the targets were collected from the NCBI database in FASTA format (Accession number: Acetylcholinesterase - AAM90333.1, Protease - ABU98624.1 and Carboxylesterase- ADJ96632.1).  The collected target sequences were submitted to the NCBI BLASTp server (http://blast.ncbi.nlm.nih.gov/Blast.cgi) individually and searched against PDB database.

 

3D Structure Modeling

The 3D structure of the targets were modeled by homology modeling using MODELLER 9.9. The MODELLER program uses an automated approach to comparative protein structure modeling by satisfaction of spatial restraints⁵.

 

Model Evaluation

The MODELLER generated structure was further verified by PROCHECK. The PROCHECK program provides the information about the stereo chemical quality of a given protein structure. The modeled targets structure was visualized using RASMOL Viewer and the secondary structure of the modeled targets were analysed using “Structure” command.

 

Molecular Docking

The interaction studies between the targets and the ligands were done using molecular docking approach. AutoDock Vina, a new molecular docking and virtual screening program was used for the docking studies. AutoDock Vina significantly improves the average accuracy of the binding mode predictions compared to AutoDock 4. The binding mode of ligands to the targets was analysed using iGEMDOCK software, A Graphical Environment for Recognizing Pharmacological Interactions and Virtual Screening. The intermolecular complexes obtained from the molecular docking studies were visualized using RASMOL and PyMOL viwer. 

 

RESULTS

Molecular Property Analysis

All compounds identified by the GC-MS screening were assessed for their insecticidal potential using physico-chemical property calculations according to Tice rules. As per Tice rule compounds are more likely to have properties of an insecticide if 1) the molecular mass is within >150 and <500; 2) theoretical logarithm of the noctanol/water partition coefficient (log P), is less than or equal to 5.0; 3) Hydrogen bond donor is less than or equal to 2; 4) Hydrogen bond acceptor is within 1-8 and 5) the number of rotatable bond is less than or equal to 12. The results showed that all the identified compounds except Tetratetracontane present in the ethyl acetate and chloroform extract of the fruit have the molecular mass within the limit. The compounds that have logP value of <5 are 1-2(H)-Naphthalenone 3,4 dihydro- 6 methoxy, 2-[3-hydroxy-4-methyl cyclohexyl] acrylaldehyde semicarbazone, 1,2,3,4 tetrahydro isoquinolin, 2-acetyl-6,7 – di methoxy-1-phenmethylene, Butanedioic acid, monoamide, N-(6-methyl-2 benzothiazolyl]-, Benzoic acid, 2-methoxy-6-methyl-, 9,12,15-Octadecatrienoic acid, 2,3-dihydroxypropyl ester, (Z,Z,Z)-, Ethanone, 1- [2,4,5-triethylphenyl]-, Benzoic acid, 4-(amino carbonyl), Heptanoic acid, 7(5-acetylamino methylthien-2-yl), 5- Formylsalicylic acid, Urea, N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]-, and  N-[3-[N-Aziridyl] propyl]cyclohexylamine. The compounds that strictly follow the Tice rule are  1-2(H)-Naphthalenone 3,4 dihydro- 6 methoxy and 8a-methyl decalin-1,8-diol, diacetate of fruit chloroform extract, 1,2,3,4 tetrahydro isoquinolin, 2-acetyl-6,7 – di methoxy-1-phenmethylene and Butanedioic acid, monoamide, N-(6-methyl-2 benzothiazolyl]- of fruit ethyl acetate extract, Benzoic acid, 2-methoxy-6-methyl- of fruit methanol extract, Ethanone, 1- [2,4,5-triethylphenyl]-, Benzoic acid, 4-(aminocarbonyl) and Heptanoic acid, 7(5-acetylamino methylthien-2-yl) of root-bark chloroform extract, Cyclodecanamine, N-methyl, and N-[3-[N-Aziridyl] propyl] cyclohexylamine of root-bark ethyl acetate extract, Urea, N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]- of root ethyl acetate and methanol extract.

 

Molecular Modelling

Template Selection

The template selection for modeling the 3D structure of the targets (Protease, Acetylcholinesterase and Carboxylesterase of H. armigera) was done using the BlastP search. The blastP results showed a list of hits that matched with the PDB database. Among the hits, the best hit for modeling the 3D structure was selected based on the low E-value and the high sequence identity (>=30%). The top hits obtained for modelling targets are displayed in the table 1.

Table 1: Template selected for 3D Structure Modelling of Carboxylesterase, Acetylcholinesterase and Protease

Template Sequence	PDB ID	E-Value	Sequence identity between target and template
Significant matches found for Carboxylesterase structure modeling using BlastP
Chain A, Crystal Structure of Juvenile Hormone Esterase FromManduca sexta, With Otfp Covalently Attached	2FJ0	9e-62	33%
Significant matches found for Acetylcholinesterase structure modeling using BlastP
Chain A, Native Acetylcholinesterase From Drosophila melanogaster	1QO9	0.0	58%
Significant matches found for Protease structure modeling using BlastP.
Chain A, Fusarium oxysporum Trypsin At Atomic Resolution	1FN8	4e-36	37%

 

 

3D structure Modeling

The “MODEL-OUTPUTS” python script of MODELLER9.9 was used to model the targets structures. Five models were generated for each target. Among the five models, top model was selected based on the DOPE (Discrete Optimized Protein Energy) score and GA341 score. GA341 score assess the overall fold quality of the modeled structure. The DOPE score reveals that the models generated are stable. The GA341 score (1.00000) of top models shows that the targets have the native structure like the templates (Table 2). The structure with low DOPE score of -25778.41016, -70184.52344 and -61522.76562 were selected as best model of Protease, Acetylcholinesterase and Carboxylesterase respectively (Table 2). The modeled structure of the target was visualized using SwissPDBviewer. The modeled targets of H.armigera composed of Helix, Strands and Turns (Table 3).

 

Table 2: DOPE Score and GA341 Score of Top Five Models of Protease, Acetylcholinesterase and Carboxylesterase of H.armigera generated by MODELLER9.9

S.No	Protease		Acetylcholinesterase		Carboxylesterase
	DOPE score	GA341 score	DOPE score	GA341 score	DOPE score	GA341 score
1	-25002.31641	1.00000	-69427.39844	1.00000	-60315.41406	1.00000
2	-24722.83789	1.00000	-70184.52344	1.00000	-61522.76562	1.00000
3	-25778.41016	1.00000	-69813.49219	1.00000	-61312.88281	1.00000
4	-24400.01562	1.00000	-69340.35938	1.00000	-60912.87891	1.00000
5	-24743.58984	1.00000	-69597.10156	1.00000	-60555.48828	1.00000

 

Table 3: Secondary Structure Analysis of The Modeled Target Structure.

S. No	Modeled Target	Number of  Helices	Number of Strands	Number of  turns
1	Acetylcholinesterase	26	22	67
2	Carboxylesterase	21	20	62
3	Protease	5	23	34

 

 

Model Evaluation

The stereochemical quality of the modeled protein structure was evaluated using the PROCHECK program which produces a number of PostScript plots analysing its over all and residue-by-residue geometry. The quality of the modeled Protease, Acetylcholinesterase and Carboxylesterse structure are found to be satisfactory with the percentage of residues in most favored region 84.7%, 86.4% and 85.2% respectively (Table 4).

 

Table 4: PROCHECK Results of the Modeled Targets

Modeled target	Residues  in most  favored region	Residues in additional allowed region	Residues  in generously allowed region	Residues in  disallowed regions
Protease	84.7%	12%	1.9%	1.4%
Acetylcholinesterase	86.4%	11.8%	0.9%	0.9%
Carboxylesterase	85.2%	12.5%	1.9%	0.4%

 

 

Molecular Docking

The compounds identified from the GC-MS analysis were short listed based on the Tice rule as well as from information available in the literature. Nine compounds from the root-bark and fruit extract of M.tinctoria were observed to strictly follow Tice rule and 8 compounds present in the extract and also known to have insecticidal property from literature were selected (Table 5).

Table 5: Compounds Short-Listed From the GC-MS Results for Molecular Docking.

 

The molecular interaction between the Acetylcholinesterase, Carboxylesterase and Protease (receptor) of H.armigera and the selected ligands were studied using Autodock vina tool (Table 6). The docking results were analysed based on the calculated binding affinity energy score. The best docking confirmation was selected based on the lowest binding affinity energy score. The ligands, Butanedioic acid monoamide, N-(6-methyl-2 benzothiazolyl]- and Urea N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]- has the best affinity with Acetylcholinesterase of H.armigera with the lowest energy score of -0.7kcal/mol. The docking results showed that Octadecanoic acid methyl ester, Tetratetracontane, Heptacosane, Eicosanedioic acid have no interaction with Acetylcholinesterase of H.armigera.

 

Table 6 : Binding Affinity of Acetylcholinesterase , Carboxylesterase and Protease of H.armigera with Selected Ligands.

Ligands	Affinity energy score (kcal/mol) of ligands with the receptors
	Acetylcholinesterase	Carboxylesterase	Protease
1-2(H)-Naphthalenone 3,4 dihydro- 6 methoxy	-0.5	-1.1	0.0
8a-methyldecalin-1,8-diol, diacetate	-0.6	-1.1	0.0
Butanedioic acid, monoamide, N-(6-methyl-2 benzothiazolyl]-	-0.7	-1.2	0.0
Benzoic acid, 2-methoxy-6-methyl-	-0.5	-0.9	0.0
Ethanone, 1- [2,4,5-triethylphenyl]-	-0.6	-0.9	0.0
Heptanoic acid, 7(5-acetylaminomethylthien-2-yl)	-0.4	-0.8	0.0
Cyclodecanamine, N-methyl	-0.4	-1.1	0.0
Urea, N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]-	-0.7	-1.0	0.0
N-[3-[N-Aziridyl] propyl]cyclohexylamine	-0.4	-0.7	0.0
Hexadecanoic acid, Methyl ester	-0.3	-0.5	0.0
Dodecanoic acid, Ethyl ester	-0.5	-0.7	0.0
Heptadecanoic acid, methyl ester	-0.2	-0.6	0.0
Octadecanoic acid, methyl ester	0.0	-0.6	0.0
Tetratetracontane	0.0	0.0	0.0
Nonadecanoic acid, methyl ester	-0.4	-1.5	0.0
Heptacosane	0.0	0.0	0.0
Eicosanedioic acid	0.0	0.0	0.0

 

 

The best affinity score of -1.5 kcal/mol was observed in the interaction of Carboxylesterase with the ligand, Nonadecanoic acid methyl ester. No interaction was observed of Carboxylesterase with Tetratetracontane, Heptacosane and Eicosanedioic acid. Similarly the Protease of H.armigera did not show any interaction with the selected ligands. The ligands which have interaction with both Acetylcholinesterase and Carboxylesterase of H.armigera are 1-2(H)-Naphthalenone 3,4 dihydro- 6 methoxy, 8a-methyldecalin-1,8-diol diacetate, Butanedioic acid monoamide N-(6-methyl-2 benzothiazolyl]-, Benzoic acid 2-methoxy-6-methyl-, Ethanone 1- [2,4,5-triethylphenyl]-, Heptanoic acid 7(5-acetylaminomethylthien-2-yl), Cyclodecanamine N-methyl, Urea N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]-, N-[3-[N-Aziridyl] propyl]cyclohexylamine, Hexadecanoic acid methyl ester, Dodecanoic acid ethyl ester, Heptadecanoic acid methyl ester and Nonadecanoic acid methyl ester.

 

The binding site analysis was done using the iGEMDOCK software. The calculated low fitness energy score for each binding showed that the inter-molecular complex formed between the Acetylcholinesterase and Carboxylesterase of H.armigera with the selected ligands are stable. The intermolecular complexes were formed mainly due to Van der waals and H-bonding forces except in Acetylcholinesterase-Ethanone, 1- [2,4,5-triethylphenyl]-, and Carboxylesterase-Octadecanoic acid methyl ester complexes. The similarity between the ligand binding domain in the Acetylcholinesterase and Carboxylesterase was analysed by the over lapping amino acids found in the binding domain. The results showed that mainly aromatic amino acids were found in the ligand binding domain of Acetylcholinesterase namely “TYR361, TYR130, PHE408, TYR411”. In the case of Carboxylesterase, the ligand binding domains are “ALA, PRO and GLY”. 

 

DISCUSSION:

Lead generation is the first gateway to a promising pharmaceutical and insecticidal candidate. In the present investigation the compounds indentified by GC-MS were analysed further for finding the right compound to act as insecticide based on the Tice rules.  Lipinski’s rules and Tice’s limits for herbicides and insecticides were adapted to help guide the selection of promising molecules and avoid problematic structures. Increasing molecular mass or size has frequently been observed to be correlated with lower solubility and poorer penetration through membranes. The average molecular mass is 324 for marketed insecticides⁶. Large numbers of H-bond acceptors and donors often cause insolubility of the molecule in many solvents due to the formation of intermolecular H-bonds in the crystal lattice. Very flexible compounds are rarely potent pesticides because of their entropy disadvantage upon binding to the receptor. Entropy terms are highly related to the number of rotatable bonds in a molecule, and the upper limit of the selection rule is 12. In the present work, ten compounds from the root-bark and fruit extract of M.tinctoria have less than 12 rotatable bond. LogP is the well established parameter to describe the uptake and distribution of the compounds in the biological system. It is generally recognized that compounds with log P values in the range -0.5 to 3 are optimal for crossing membranes, and that compounds with log P values above this range tend to accumulate in lipid membranes, while very hydrophilic compounds cannot partition into the membrane⁷. As per the tice rule, the logP value for the insecticides is less than or equal to 5. Benting et.al.,⁸ have reported on the synthesis and screening of a library of oxime ethers designed as insecticidal agonists of the muscarinic acetylcholine receptor. The compounds 1-2(H)-Naphthalenone 3,4 dihydro- 6 methoxy, 8a-methyldecalin-1,8-diol, diacetate, Butanedioic acid monoamide N-(6-methyl-2 benzothiazolyl]-,  Benzoic acid 2-methoxy-6-methyl-, Ethanone 1- [2,4,5-triethylphenyl]-, Heptanoic acid 7(5-acetylaminomethy-lthien-2-yl), Cyclodecanamine N-methyl, Urea N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]- and N-[3-[N-Aziridyl] propyl]cyclohexylamine identified from the Chloroform, ethyl acetate, Methanol extracts of fruit and root-bark of M.tinctoria stickly follows the Tice rules. Thus these compounds might account for the observed insecticidal activity of fruit and root-bark of M.tinctoria extracts.

 

The process of finding novel leads for a new target is the most important and certainly one of the most crucial steps in a new insecticide development. In the present study, the molecular docking program was used to find out the novel compound from the root-bark and fruit extract of M.tinctoria with insecticidal property. The docking results showed that the ligands, Butanedioic acid monoamide, N-(6-methyl-2 benzothiazolyl]- and Urea N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]- has the best affinity with Acetylcholinesterase of H.armigera. Pravin et.al.,⁹ has reported that the insect cellular cytoskeletal beta-actin could be the target of Azadirachtin A using the in-silico docking analysis. It has been reported that a native or engineered cysteine residue near the active site of an enzyme can hook a small molecule that binds, even loosely, at the active site, as long as the cysteine residue is able to react with an eletrophilic group of the molecule¹⁰. The amino acid residues found in the ligand binding domain (active site) of the Acetylcholinesterase in H.armigera is located in between the CYS344 and CYS480. The overlapping amino acids found in the active site showed that the ligands interacted with AchE of H.armigera are almost occupying the location where the “TYR361, TYR130, PHE408, TYR411” are present. Yuan-Ping¹¹ has studies the Novel Acetylcholinesterase Target Site for Anopheles gambiae (Giles) using Homology modelling and docking studies. He has reported that the peripheral site of the refined AgAChE model, was located at ARG339 with PHE75, PHE78, TYR332, and TRP431. Molecular dynamics simulations of the greenbug AChE in complex with AMTS17 suggested that the 17-methylene-long inhibitor would tuck into the active site with its thiol sulfur atom located 3.6-A° away from the sulfur atom of CYS289 at the opening of the active site, while its ammonium group engages in an ionic interaction with GLU201 as well as cation-pi interactions with TRP87, TYR331, and TRP434 at the bottom of the active site¹².

Carboxylesterases (CarE) play important roles in insecticide resistance, allelochemical tolerance and developmental regulation¹³. Most of the CarEs are tissue specific and mainly expressed in the midgut, head, integument and silk gland¹⁴. The inhibition of CarE of H.armigera by the ligands identified from the root-bark and fruit extract of M.tinctoria were analysed based on the intermolecular complex formed by molecular docking. Ian et.al.,¹⁵ has suggested that the homology model and docking studies yield a good model of the insect GABA receptor binding site and the location of agonists within it. An important group of chemicals that promote CE inhibition are fluorinated ketones, which inhibit a variety of esterases such as acetylcho-linesterase¹⁶, juvenile hormone esterase (JHE)¹⁷ and human liver microsomal CEs¹⁸, as well as enzymes such as chymotrypsin and trypsin^{19, 20} and enzymes that metabolize chemical mediators including fatty acid amide hydrolase and diacyl glycerol²¹. Jiao et.al., ²² has suggested that the Ser197, His440 and Glu321  aggregated together and form the catalytic triad of Loxostege sticticalis L. CarE using the 3D structure analysis . The molecular docking analysis of the CarE with the selected ligands showed the amino acid involved in the active site. The results explored that the ligands, 1-2(H)-Naphthalenone 3,4 dihydro- 6 methoxy , 8a-methyldecalin-1,8-diol, diacetate , Butanedioic acid, monoamide, N-(6-methyl-2 benzothiazolyl]-, Cyclode-canamine N-methyl and Urea N,N-dimethyl-N’ [4-[1-methyl ethyl] phenyl]-,  that occupies the binding site consist of GLY,PRO and ALA residues.

 

In insects, proteases plays vital role in the digestion of protein and generally, the Serine proteases of insects are inhibited by the plant proteinase inhibitors (PIs). Proteinase inhibitors with high activity against serine proteinases was extracted from seeds of the tree legume, Acacia senegal (L.) Willd and was evaluated against Helicoverpa armigera larvae by in vitro and in vivo methods²³. There are numerous studies available related to the development of PIs against H.armigera. The inhibition of serine proteinase such as Trypsin and Chymotrypsin of Helicoverpa armigera by the PI of Vigna unguiculata, Capsicum annum and Phaseolus vulgaris was studied using molecular docking studies²⁴. In the present study, the phytochemicals identified from the extracts of root-bark and fruit of M.tinctoria has not shown any interaction with the protease of H.armigera.

 

CONCLUSION:

In conclusion, the extracts of root-bark and fruit from M.tinctoria showed potent insecticidal activity against H.armigera. The presence of phytochemicals such as Heptadecenoic acid, Heptacosane, Eicosanedioic acid, Dodecanoic acid Ethyl ester, Nonadecenoic acid in the extracts might be the reason for insecticidal activity of M.tinctoria. The molecular docking studies well supported the insecticidal activity of the phytochemicals against the H.armigera target enzymes such as Acetylcholinesterase and Carboxylesterase. Morinda tincoria shows promise for use as a source of novel insecticide.

 

REFERENCES:

1.       Prakash A, Rao, Botanical pesticides in agriculture. CRC Lewis Publs. Boca Raton, USA, pp.481, 1997.

2.       Chandler ES, Botanical aspects of pyrethrum. General considerations: the seat of the active princi­ples. Pyrethrum Post, 2; 1951: 1–8.

3.       Morgan ED, Azadirachtin, a scientific gold mine. Bioorganic and Medicinal Chemistry, 17; 2000: 4096-4105.

4.       Surendiran G, Antimicrobial and wound healing activities of Morinda tinctoria. M.Sc., thesis, University of Madras, 2004.

5.       Sali A and Blundell TL, Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol.1993; 234,779-815.

6.       Tice CM, Selecting the right compounds for screening: does Lipinski's Rule of 5 for pharmaceuticals apply to agrochemicals?. Pestic. Manag. Science 2001; 57:3-16.

7.       Pagliara A, Reist M, Geinoz S, Carrupt PA and Testa B, Evaluation and prediction of drug permeation. J. Pharm. Pharmacol.; 51:1339-1357.

8.       Benting J, Leonhardt M, Lindell SD, Tiebes, High Throughput Screening. J.Comb. Chem; 8: 649, 2005.

9.       Pravin Kumar R, Manoj MN, Kush A, Annadurai RS, In silico approach of azadirachtin binding with actins. Insect Biochem Mol Biol., 37(6): 1999: 635-40, 2007.

10.     Erlanson DA, Braisted AC, Raphael DR, et al. Site-directed ligand discovery. Proc. Natl. Acad. Sci., 97; 2000: 9367–9372.

11.     Yuan-Ping, Novel Acetylcholinesterase Target Site for Malaria Mosquito Control. PLoS ONE 1(1): e58, 2006.

12.     Yuan-Ping Pang, Sanjay K, Singha et al, Selective and Irreversible Inhibitors of Aphid Acetylcholinesterases: Steps Toward Human- Safe Insecticides. PLoS ONE, 4(2): e4349, 2009.

13.     Oakeshott JG, Claudianos C, Russell RJ, Robin GC. Carboxyl/ cholinesterases: a case study of the evolution of a successful multigene family. Bioessays, 21; 1999: 1031-1042.

14.     Yu, Q.Y., Lu, C., Li, W.L., Xiang, Z.H., Zhang, Z, Annotation and expression of carboxylesterases in the silkworm, Bombyx mori. BMC Genomics, 10; 2009: 553.

15.     Ian McGonigle, Sarah CR, Lummis.  Molecular Characterization of Agonists That Bind to an Insect GABA Receptor. Biochemistry, 49(13); 2010: 2897–2902.

16.     Gelb MH, Svaren JP, Abeles RH. Fluoroketone inhibitors of hydrolytic enzymes. Biochemistry, 24; 1985: 1813–1817.

17.     Abdel-Aal YAI, Hammock BD. 3-Octylthio-1,1,1-trifluoro-2- propanone, ahigh affinity and slow binding inhibitor of juvenile hormone esterase in Trichoplusia ni (Huebner). Insect Biochem.,15; 1985: 111–122.

18.     Wadkins RM, Hyatt JL, Edwards CC, Tsurkan L, et al., Analysis of mammalian carboxylesterase inhibition by trifluoromethylketone-containing compounds. Mol Pharmacol., 71; 2007:713–723.

19.     Parisi MF, Abeles RH. Inhibition of chymotrypsin by fluorinated alpha-keto acid derivatives. Biochemistry, 31; 1992: 9429–9435.

20.     Angliker H, Wilkstrom P, Rauber P, Stone S, Shaw E. Synthesis and properties of peptidyl derivatives of Arginylfluoromethanes. Biochem J., 256; 1988: 481–486.

21.     Wheelock CE, Nishi K, Ying A, et al., Influence of sulfur oxidation state and steric bulk upon trifluoromethyl ketone (TFK) binding kinetics to carboxylesterases and fatty acid amide hydrolase (FAAH). Bioorg Med Chem., 16; 2008: 2114–2130.

22.     Jiao Yin, Tao Zhong, Zhao-Jun Wei, Ke-Bin Li, Ya-Zhong Cao. and Wei Guo. Molecular characters and recombinant expression of the carboxylesterase gene of the meadow moth Loxostege sticticalis L. (Lepidoptera: Pyralidae). African Journal of Biotechnology, 10(10); 2011: 1794-1801.

23.     Ramesh Babu S, Subrahmanyam B. Bio-potency of serine proteinase inhibitors from Acacia senegal seeds on digestive proteinases, larval growth and development of Helicoverpa armigera (Hübner). Pesticide Biochemistry and Physiology, 98(3); 2010: 349-358.

24.     Praveena A and Sanjayan KP. In Silico Comparision of the Ligand Binding Domain of Ecdysone Receptor of Two Lepidopterous Insect Pests, Helicoverpa Armigera and Spodoptera Litura. International Journal of Genetic Engineering and Biotechnology, 1(1); 2010: 89—99.

 

 

Accepted on 09.06.2016        © RJPT All right reserved

Research J. Pharm. and Tech 2016; 9(11):1829-1834.