Advanced Screening to Identify Novel Pesticides

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Advanced Technologies for Managing Insect Pests

Abstract

Insect molting is regulated by 20-hydroxyecdsysone (20E), and the disruption of the molting process leads to death. To date, non-steroidal ecdysone agonists, diacylhydrazine (DAH)-type compounds, have been used as insecticides. We will review classical quantitative structure activity relationship (QSAR) studies for the in vivo and in vitro activity of DAHs and ecdysteroids. In the QSAR study for ecdysteroids, we applied three-dimensional QSAR, where hydrogen bond number was used as a parameter. The ligand-receptor complex was constructed by the homology modeling technique and the number of hydrogen bonds was counted. In recent drug design, computational approaches such as virtual (in silico) screening (VS) and high throughput screening (HTS) are often used. The VS procedure is classified as ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS); both are often used for the design of pharmaceuticals. We applied LBVS to find novel ecdysone agonists, in which ponasterone A (PoA), the most potent ecdysteroid, was used as a template molecule. Other computational techniques such as homology modeling and bioinformatics are also briefly reviewed.

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Abbreviations

DAH:

diacylhydrazine

DBH:

dibenzoylhydrazine

PoA:

ponasterone A

QSAR:

quantitative structure-activity relationship

HTS:

high throughput screening

CoMFA:

comparative molecular field analysis

E:

ecdysone

References

  • Agrafiotis DK, Bandyopadhyay D, Wegner JK, Vlijmen H (2007) Recent advances in chemoinformatics. J Chem Inf Model 47:1279–1293

    PubMed  CAS  Google Scholar 

  • Akamatsu M (2002) Current state and perspectives of 3D-QSAR. Curr Top Med Chem 2:1381–1394

    PubMed  CAS  Google Scholar 

  • Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    PubMed  CAS  Google Scholar 

  • Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    PubMed  CAS  Google Scholar 

  • Andersson A, Jordan D, Schneider G, Lindqvist Y (1996) Crystal structure of the ternary complex of 1,3,8-trihydroxynaphthalene reductase from Magnaporthe grisea with NADPH and an active-site inhibitor. Structure 4:1161–1170

    PubMed  CAS  Google Scholar 

  • Aoki-Kinoshita KF (2006) Overview of KEGG applications to omics-related research. J Pestic Sci 31:296–299

    CAS  Google Scholar 

  • Arai H, Watanabe B, Nakagawa Y, Miyagawa H (2008) Synthesis of ponasterone A derivatives with various steroid skeleton moieties and evaluation of their binding to the ecdysone receptor of Kc cells. Steroids 73:1452–1464

    PubMed  CAS  Google Scholar 

  • Ayers M, Symmans WF, Stec J, Damokosh AI, Clark E, Hess K, Lecocke M, Metivier J, Booser D, Ibrahim N et al (2004) Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. J Clin Oncol 22:2284–2293

    PubMed  CAS  Google Scholar 

  • Billas IM, Iwema T, Garnier JM, Mitschler A, Rochel N, Moras D (2003) Structural adaptability in the ligand-binding pocket of the ecdysone hormone receptor. Nature 426:91–96

    PubMed  CAS  Google Scholar 

  • Bomgardner MM (2011) Germinating pesticide. Chemical and Engineering News:13–17

    Google Scholar 

  • Bondi A (1964) van der Waals volumes and radii. J Phys Chem 68:441–451

    CAS  Google Scholar 

  • Brunskole M, Stefane B, Zorko K, Anderluh M, Stojan J, Lanisnik Rizner T, Gobec S (2008) Towards the first inhibitors of trihydroxynaphthalene reductase from Curvularia lunata: synthesis of artificial substrate, homology modelling and initial screening. Bioorg Med Chem 16:5881–5889

    PubMed  CAS  Google Scholar 

  • Brunskole Svegelj M, Turk S, Brus B, Lanisnik Rizner T, Stojan J, Gobec S (2011) Novel inhibitors of trihydroxynaphthalene reductase with antifungal activity identified by ligand-based and structure-based virtual screening. J Chem Inf Model 51:1716–1724

    PubMed  Google Scholar 

  • Bujnicki JM (2006) Protein-structure prediction by recombination of fragments. Chembiochem 7:19–27

    PubMed  CAS  Google Scholar 

  • Burke MD, Schreiber SL (2004) A planning strategy for diversity-oriented synthesis. Angew Chem Int Ed Engl 43:46–58

    PubMed  Google Scholar 

  • Carlson GR, Dhadialla TS, Hunter R, Jansson RK, Jany CS, Lidert Z, Slawecki RA (2001) The chemical and biological properties of methoxyfenozide, a new insecticidal ecdysteroid agonist. Pest Manag Sci 57:115–119

    PubMed  CAS  Google Scholar 

  • Carmichael JA, Lawrence MC, Graham LD, Pilling PA, Epa VC, Noyce L, Lovrecz G, Winkler DA, Pawlak-Skrzecz A, Eaton RE et al (2005) The X-ray structure of a hemipteran ecdysone receptor ligand-binding domain: comparison with a lepidopteran ecdysone receptor ligand-binding domain and implications for insecticide design. J Biol Chem 280:22258–22269

    PubMed  CAS  Google Scholar 

  • Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R, Mohsin S, Osborne CK, Chamness GC, Allred DC et al (2003) Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet 362:362–369

    PubMed  CAS  Google Scholar 

  • Charton M (1981) Electrical effect substituent constants for correlation analysis. Prog Phys Org Chem 13:119–251

    CAS  Google Scholar 

  • Chen JH, Turner PC, Rees HH (2002) Molecular cloning and induction of nuclear receptors from insect cell lines. Insect Biochem Mol Biol 32:657–667

    PubMed  CAS  Google Scholar 

  • Cherezov V, Rosenbaum DM, Hanson MA, Rasmussen SG, Thian FS, Kobilka TS, Choi HJ, Kuhn P, Weis WI, Kobilka BK et al (2007) High-resolution crystal structure of an engineered human beta2-adrenergic G protein-coupled receptor. Science 318:1258–1265

    PubMed  CAS  Google Scholar 

  • Cramer III RD, Patterson DE, Bunce JD (1988) Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J Am Chem Soc 110:5959–5967

    Google Scholar 

  • Duong-Thi MD, Meiby E, Bergstrom M, Fex T, Isaksson R, Ohlson S (2011) Weak affinity chromatography as a new approach for fragment screening in drug discovery. Anal Biochem 414:138–146

    PubMed  CAS  Google Scholar 

  • Eddy SR (1996) Hidden Markov models. Curr Opin Struct Biol 6:361–365

    PubMed  CAS  Google Scholar 

  • Elofsson A, Wallner B, Fang HS (2003) Automatic consensus-based fold recognition using Pcons, ProQ, and pmodeller. Proteins-Struct Funct Genet 53:534–541

    PubMed  Google Scholar 

  • Engel T (2006a) Basic overview of chemoinformatics. J Chem Inf Model 46:2267–2277

    PubMed  CAS  Google Scholar 

  • Engel T (2006b) Johann Gasteiger–Germany’s pioneer in chemoinformatics. J Chem Inf Model 46:2191–2192

    PubMed  CAS  Google Scholar 

  • Free SM Jr, Wilson JW (1964) A mathematical contribution to structure-activity studies. J Med Chem 7:395–399

    PubMed  CAS  Google Scholar 

  • Fujita T (1990) The extrathermodynamic approach to drug design. In: Ramsden CA (ed) Compre-hensive medicinal chemistry. Pergamon, Oxford, pp 497–560

    Google Scholar 

  • Fujita T (2011) In memoriam Professor Corwin Hansch: birth pangs of QSAR before 1961. J Comput Aided Mol Des 25:509–517

    PubMed  CAS  Google Scholar 

  • Fujita T, Hansch C, Iwasa J (1964) New substituent constant Π derived from partition coefficients. J Am Chem Soc 86:5175–5180

    CAS  Google Scholar 

  • Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA et al (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286:531–537

    PubMed  CAS  Google Scholar 

  • Hajduk PJ, Greer J (2007) A decade of fragment-based drug design: strategic advances and lessons learned. Nat Rev Drug Discov 6:211–219

    PubMed  CAS  Google Scholar 

  • Hansch C, Fujita T (1964) r-s-Π analysis. Method for correlation of biological activity and chemical structure. J Am Chem Soc 86:1616–1626

    CAS  Google Scholar 

  • Hansch C, Maloney PP, Fujita T (1962) Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 194:178–180

    CAS  Google Scholar 

  • Hansch C, Streich M, Geiger F, Muir RM, Maloney PP, Fujita T (1963) Correlation of biological activity of plant growth regulators and chloromycetin derivatives with Hammett constants and partition coefficients. J Am Chem Soc 85:2817–2824

    CAS  Google Scholar 

  • Hansch C, Leo AJ, Hoekman D (1995) Exploring QSAR-hydrophobic, electronic, and steric constants. American Chemical Society, Washington, DC

    Google Scholar 

  • Harada T, Nakagawa Y, Akamatsu M, Miyagawa H (2009) Evaluation of hydrogen bonds of ecdysteroids in the ligand-receptor interactions using a protein modeling system. Bioorg Med Chem 17:5868–5873

    PubMed  CAS  Google Scholar 

  • Harada T, Nakagawa Y, Ogura T, Yamada Y, Ohe T, Miyagawa H (2011) Virtual screening for ligands of the insect molting hormone receptor. J Chem Inf Model 51:296–305

    PubMed  CAS  Google Scholar 

  • Hormann RE, Smagge G, Nakagawa Y (2008) Multidimensional quantitative structure-activity relationships of diacylhydrazine toxicity in Spodoptera exigua, Chilo suppressalis, and Leptinotarsa decemlineata. QSAR Comb Sci 27:1098–1112

    CAS  Google Scholar 

  • Horvath D (1997) A virtual screening approach applied to the search for trypanothione reductase inhibitors. J Med Chem 40:2412–2423

    PubMed  CAS  Google Scholar 

  • Hsu AC-T (1991) 1,2-Diacyl-1-alkylhydrazines, a new class of insect growth regulators. In: Baker DR, Fenyes JG, Moberg WK (eds) Synthesis and chemistry of agrochemicals II. American Chemical Society, Washington, DC, pp 478–490

    Google Scholar 

  • Hsu AC-T, Fujimoto TT, Dhadialla TS (1997) Structure-activity study and conformational analysis of RH-5992, the first commercialized nonsteroidal ecdysone agonist. In: Hedin PA, Hollingworth RM, Masler EP, Miyamoto J, Thompson DG (eds) Phytochemicals for pest control. American Chemical Society, Washington, DC, pp 206–219

    Google Scholar 

  • Iwadate M, Kanou K, Terashi G, Umeyama H, Takeda-Shitaka M (2010) Method for predicting homology modeling accuracy from amino acid sequence alignment: the power function. Chem Pharm Bull(Tokyo) 58:1–10

    CAS  Google Scholar 

  • Iwema T, Billas IM, Beck Y, Bonneton F, Nierengarten H, Chaumot A, Richards G, Laudet V, Moras D (2007) Structural and functional characterization of a novel type of ligand-independent RXR-USP receptor. EMBO J 26:3770–3782

    PubMed  CAS  Google Scholar 

  • Jain AN, Nicholls A (2008) Recommendations for evaluation of computational methods. J Comput Aided Mol Des 22:133–139

    PubMed  CAS  Google Scholar 

  • Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M (2006) From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 34:D354–D357

    PubMed  CAS  Google Scholar 

  • Kanou K, Hirata T, Iwadate M, Terashi G, Umeyama H, Takeda-Shitaka M (2010a) HUMAN FAMSD-BASE: high quality protein structure model database for the human genome using the FAMSD homology modeling method. Chem Pharm Bull(Tokyo) 58:66–75

    CAS  Google Scholar 

  • Kanou K, Hirata T, Terashi G, Umeyama H, Takeda-Shitaka M (2010b) New protein structure model evaluation methods that include a side-chain consensus score for the protein modeling. Chem Pharm Bull(Tokyo) 58:180–190

    CAS  Google Scholar 

  • Kasuya A, Sawada Y, Tsukamoto Y, Tanaka K, Toya T, Yanagi M (2003) Binding mode of ecdysone agonists to the receptor: comparative modeling and docking studies. J Mol Model 9:58–65

    PubMed  CAS  Google Scholar 

  • Keseru GM, Makara GM (2009) The influence of lead discovery strategies on the properties of drug candidates. Nat Rev Drug Discov 8:203–212

    PubMed  Google Scholar 

  • Kubinyi H (1977) Quantitative structure-activity-relationships. 7. Bilinear model, a new model for nonlinear dependence of biological-activity on hydrophobic character. J Med Chem 20:625–629

    PubMed  CAS  Google Scholar 

  • Laskowski RA, Macarthur MW, Moss DS, Thornton JM (1993) Procheck – a program to check the stereochemical quality of protein structures. J Appl Crystallogr 26:283–291

    CAS  Google Scholar 

  • Leo AJ (1993) Calculating log Poct from structures. Chem Rev 93:1281–1306

    CAS  Google Scholar 

  • Luthy R, Bowie JU, Eisenberg D (1992) Assessment of protein models with three-dimensional profiles. Nature 356:83–85

    PubMed  CAS  Google Scholar 

  • Marchler-Bauer A, Panchenko AR, Shoemaker BA, Thiessen PA, Geer LY, Bryant SH (2002) CDD: a database of conserved domain alignments with links to domain three-dimensional structure. Nucleic Acids Res 30:281–283

    PubMed  CAS  Google Scholar 

  • Martin YC (1992) 3D database searching in drug design. J Med Chem 35:2145–2154

    PubMed  CAS  Google Scholar 

  • Mcgaughey GB, Sheridan RP, Bayly CI, Culberson JC, Kreatsoulas C, Lindsley S, Maiorov V, Truchon JF, Cornell WD (2007) Comparison of topological, shape, and docking methods in virtual screening. J Chem Inf Model 47:1504–1519

    PubMed  CAS  Google Scholar 

  • Minakuchi C, Nakagawa Y, Miyagawa H (2003) Validity analysis of a receptor binding assay for ecdysone agonists using cultured intact insect cells. J Pestic Sci 28:55–57

    CAS  Google Scholar 

  • Miyashita M, Oda M, Ono Y, Komoda E, Miyagawa H (2011) Discovery of a small peptide from combinatorial libraries that can activate the plant immune system by a jasmonic acid signaling pathway. Chembiochem 12:1323–1329

    PubMed  CAS  Google Scholar 

  • Mo SL, Liu WF, Chen Y, Luo HB, Sun LB, Chen XW, Zhou ZW, Sneed KB, Li CG, Du YM et al (2012) Ligand- and protein-based modeling studies of the inhibitors of human cytochrome P450 2D6 and a virtual screening for potential inhibitors from the Chinese herbal medicine, Scutellaria baicalensis (Huangqin, Baikal Skullcap). Comb Chem High Throughput Screen 15:36–80

    Google Scholar 

  • Mukherjee P, Shah F, Desai P, Avery M (2011) Inhibitors of SARS-3CLpro: virtual screening, biological evaluation, and molecular dynamics simulation studies. J Chem Inf Model 51:1376–1392

    PubMed  CAS  Google Scholar 

  • Nakagawa Y (2005) Nonsteroidal ecdysone agonists. Vitam Horm 73:131–173

    PubMed  CAS  Google Scholar 

  • Nakagawa Y, Henrich VC (2009) Arthropod nuclear receptors and their role in molting. FEBS J 276:6128–6157

    PubMed  CAS  Google Scholar 

  • Nakagawa Y, Shimizu B, Oikawa N, Akamatsu M, Nishimura K, Kurihara N, Ueno T, Fujita T (1995a) Three-dimensional quantitative structure-activity analysis of steroidal and dibenzoylhydrazine-type ecdysone agonists. In: Hansch C, Fujita T (eds) Classical and three-dimensional QSAR in agrochemistry. American Chemical Society, Washington, DC, pp 288–301

    Google Scholar 

  • Nakagawa Y, Soya Y, Nakai K, Oikawa N, Nishimura K, Ueno T, Fujita T, Kurihara N (1995b) Quantitative structure-activity studies of insect growth regulators. XI. Stimulation and inhibition of N-acetylglucosamine incorporation in a cultured integument system by substituted N-tert-butyl-N, N′-dibenzoylhydrazines. Pestic Sci 43:339–345

    CAS  Google Scholar 

  • Nakagawa Y, Hattori K, Shimizu B, Akamatsu M, Miyagawa H, Ueno T (1998) Quantitative structure-activity studies of insect growth regulators XIV. Three dimensional quantitative structure-activity relationship of ecdysone agonists including dibenzoylhydrazine analogs. Pestic Sci 53:267–277

    CAS  Google Scholar 

  • Nakagawa Y, Smagghe G, Kugimiya S, Hattori K, Ueno T, Tirry L, Fujita T (1999) Quantitative structure-activity studies of insect growth regulators: XVI. Substituent effects of dibenzoylhydrazines on the insecticidal activity to Colorado potato beetle Leptinotarsa decemlineata. Pestic Sci 55:909–918

    CAS  Google Scholar 

  • Nakagawa Y, Minakuchi C, Ueno T (2000) Inhibition of [3H]ponasterone A binding by ecdysone agonists in the intact Sf-9 cell line. Steroids 65:537–542

    PubMed  CAS  Google Scholar 

  • Nakagawa Y, Smagghe G, Van Paemel M, Tirry L, Fujita T (2001) Quantitative structure-activity studies of insect growth regulators: XVIII. Effects of substituents on the aromatic moiety of dibenzoylhydrazines on larvicidal activity against the Colorado potato beetle Leptinotarsa decemlineata. Pest Manag Sci 57:858–865

    PubMed  CAS  Google Scholar 

  • Nakagawa Y, Minakuchi C, Takahashi K, Ueno T (2002a) Inhibition of [3H]ponasterone A binding by ecdysone agonists in the intact Kc cell line. Insect Biochem Mol Biol 32:175–180

    PubMed  CAS  Google Scholar 

  • Nakagawa Y, Smagghe G, Tirry L, Fujita T (2002b) Quantitative structure-activity studies of insect growth regulators: XIX. Effects of substituents on the aromatic moiety of dibenzoylhydrazines on larvicidal activity against the beet armyworm Spodoptera exigua. Pest Manag Sci 58:131–138

    PubMed  CAS  Google Scholar 

  • Ogata K, Umeyama H (2000) An automatic homology modeling method consisting of database searches and simulated annealing. J Mol Graph Model 18:258–272

    PubMed  CAS  Google Scholar 

  • Ogura T, Nakagawa Y, Minakuchi C, Miyagawa H (2005) QSAR for binding affinity of substituted dibenzoylhydrazines to intact Sf-9 cells. J Pestic Sci 30:1–6

    CAS  Google Scholar 

  • Ohlson S (2008) Designing transient binding drugs: a new concept for drug discovery. Drug Discov Today 13:433–439

    PubMed  CAS  Google Scholar 

  • Oikawa N, Nakagawa Y, Soya Y, Nishimura K, Kurihara N, Ueno T, Fujita T (1993) Enhancement of N-acetylglucosamine incorporation into the cultured integument of Chilo suppressalis by molting hormone and dibenzoylhydrazine insecticides. Pestic Biochem Physiol 47:165–170

    CAS  Google Scholar 

  • Oikawa N, Nakagawa Y, Nishimura K, Ueno T, Fujita T (1994a) Quantitative structure-activity analysis of larvicidal 1-(substituted benzoyl)-2-benzoyl-1-tert-butylhydrazines against Chilo suppressalis. Pestic Sci 41:139–148

    CAS  Google Scholar 

  • Oikawa N, Nakagawa Y, Nishimura K, Ueno T, Fujita T (1994b) Quantitative structure-activity studies of insect growth regulators X. Substituent effects on larvicidal activity of 1-tert-butyl-1-(2-chlorobenzoyl)-2-(substituted benzoyl)hydrazines against Chilo suppressalis and design synthesis of potent derivatives. Pestic Biochem Physiol 48:135–144

    CAS  Google Scholar 

  • Okada T, Le Trong I, Fox BA, Behnke CA, Stenkamp RE, Palczewski K (2000) X-Ray diffraction analysis of three-dimensional crystals of bovine rhodopsin obtained from mixed micelles. J Struct Biol 130:73–80

    PubMed  CAS  Google Scholar 

  • Okuno Y (2008) In silico drug discovery based on the integration of bioinformatics and chemoinformatics. Yakugaku Zasshi 128:1645–1651

    PubMed  CAS  Google Scholar 

  • Osolodkin DI, Palyulin VA, Zefirov NS (2011) Structure-based virtual screening of glycogen synthase kinase 3beta inhibitors: analysis of scoring functions applied to large true actives and decoy sets. Chem Biol Drug Des 78:378–390

    PubMed  CAS  Google Scholar 

  • Pearson WR, Lipman DJ (1988) Improved tools for biological sequence comparison. Proc Natl Acad Sci USA 85:2444–2448

    PubMed  CAS  Google Scholar 

  • Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Mol Biol 7:95–99

    PubMed  CAS  Google Scholar 

  • Rasmussen SG, Choi HJ, Rosenbaum DM, Kobilka TS, Thian FS, Edwards PC, Burghammer M, Ratnala VR, Sanishvili R, Fischetti RF et al (2007) Crystal structure of the human beta2 adrenergic G-protein-coupled receptor. Nature 450:383–387

    PubMed  CAS  Google Scholar 

  • Rosenwald A, Wright G, Chan WC, Connors JM, Campo E, Fisher RI, Gascoyne RD, Muller-Hermelink K, Smeland EB, Staudt LM (2002) The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl J Med 346:1937–1947

    PubMed  Google Scholar 

  • Sage C, Wang R, Jones G (2011) G-protein coupled receptors virtual screening using genetic algorithm focused chemical space. J Chem Inf Model 51:1754–1761

    PubMed  CAS  Google Scholar 

  • Sawada Y, Yanai T, Nakagawa H, Tsukamoto Y, Tamagawa Y, Yokoi S, Yanagi M, Toya T, Sugizaki H, Kato Y et al (2003) Synthesis and insecticidal activity of benzoheterocyclic analogues of N′-benzoyl-N-(tert-butyl)benzohydrazide: Part 3. Modification of N-tert-butylhydrazine moiety. Pest Manag Sci 59:49–57

    PubMed  CAS  Google Scholar 

  • Schaffer AA, Wolf YI, Ponting CP, Koonin EV, Aravind L, Altschul SF (1999) IMPALA: matching a protein sequence against a collection of PSI-BLAST-constructed position-specific score matrices. Bioinformatics 15:1000–1011

    PubMed  CAS  Google Scholar 

  • Schreiber SL (2000) Target-oriented and diversity-oriented organic synthesis in drug discovery. Science 287:1964–1969

    PubMed  CAS  Google Scholar 

  • Shah F, Mukherjee P, Gut J, Legac J, Rosenthal PJ, Tekwani BL, Avery MA (2011) Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library. J Chem Inf Model 51:852–864

    PubMed  CAS  Google Scholar 

  • Shimamura T, Shiroishi M, Weyand S, Tsujimoto H, Winter G, Katritch V, Abagyan R, Cherezov V, Liu W, Han GW et al (2011) Structure of the human histamine H1 receptor complex with doxepin. Nature 475:65–70

    PubMed  CAS  Google Scholar 

  • Shimizu B, Nakagawa Y, Hattori K, Nishimura K, Kurihara N, Ueno T (1997) Molting hormonal and larvicidal activities of aliphatic acyl analogs of dibenzoylhydrazine insecticides. Steroids 62:638–642

    PubMed  CAS  Google Scholar 

  • Simons KT, Kooperberg C, Huang E, Baker D (1997) Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J Mol Biol 268:209–225

    PubMed  CAS  Google Scholar 

  • Simons KT, Ruczinski I, Kooperberg C, Fox BA, Bystroff C, Baker D (1999) Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins. Proteins 34:82–95

    PubMed  CAS  Google Scholar 

  • Smagghe G, Nakagawa Y, Carton B, Mourad AK, Fujita T, Tirry L (1999) Comparative ecdysteroid action of ring-substituted dibenzoylhydrazines in Spodoptera exigua. Arch Insect Biochem Physiol 41:42–53

    CAS  Google Scholar 

  • Smellie AS, Crippen GM, Richards WG (1991) Fast drug-receptor map** by site-directed distances – a novel method of predicting new pharmacological leads. J Chem Inf Comput Sci 31:386–392

    PubMed  CAS  Google Scholar 

  • Tanaka K, Tsukamoto Y, Sawada Y, Kasuya A, Hotta H, Ichinose R, Watanabe T, Toya T, Yokoi S, Kawagishi A et al (2001) Chromafenozide: a novel lepidopteran insect control agent. Annu Rep Sankyo Res Lab 53:1–49

    CAS  Google Scholar 

  • Terashi G, Takeda-Shitaka M, Takaya D, Komatsu K, Umeyama H (2005) Searching for protein-protein interaction sites and docking by the methods of molecular dynamics, grid scoring, and the pairwise interaction potential of amino acid residues. Proteins-Struct Funct Bioinform 60:289–295

    CAS  Google Scholar 

  • Thomas GL, Spandl RJ, Glansdorp FG, Welch M, Bender A, Cockfield J, Lindsay JA, Bryant C, Brown DF, Loiseleur O et al (2008) Anti-MRSA agent discovery using diversity-oriented synthesis. Angew Chem Int Ed Engl 47:2808–2812

    PubMed  CAS  Google Scholar 

  • Tohidi-Esfahani D, Lawrence MC, Graham LD, Hannan GN, Simpson AM, Hill RJ, Tohidi-Esfahani D, Lawrence MC, Graham LD, Hannan GN, Simpson AM, Hill RJ (2011) Isoforms of the heteropteran Nezara viridula ecdysone receptor: protein characterisation, RH5992 insecticide binding and homology modelling. Pest Manag Sci 67:1457–1467

    PubMed  CAS  Google Scholar 

  • Tomii K, Akiyama Y (2004) FORTE: a profile-profile comparison tool for protein fold recognition. Bioinformatics 20:594–595

    PubMed  CAS  Google Scholar 

  • Tsuji G, Takeda T, Furusawa I, Horino O, Kubo Y (1997) Carpropamid, an anti-rice blast fungicide, inhibits scytalone dehydratase activity and appressorial penetration in Colletotrichum lagenarium. Pestic Biochem Physiol 57:211–219

    CAS  Google Scholar 

  • Vedani A, Dobler M (2002) Multidimensional QSAR: moving from three- to five-dimensional concepts. Quant Struct-Act Relatsh 21:382–390

    CAS  Google Scholar 

  • Verloop A (1983) The STERIMOL approach: further development of the method and new applications. In: Miyamoto J, Kearney PC (eds) Pesticide chemistry, human welfare and environment. Pergamon Press, Oxford, pp 339–344

    Google Scholar 

  • Vilar S, Ferino G, Phatak SS, Berk B, Cavasotto CN, Costanzi S (2011) Docking-based virtual screening for ligands of G protein-coupled receptors: not only crystal structures but also in silico models. J Mol Graph Model 29:614–623

    PubMed  CAS  Google Scholar 

  • Wallner B, Fang H, Elofsson A (2003) Automatic consensus-based fold recognition using Pcons, ProQ, and Pmodeller. Proteins 53(Suppl 6):534–541

    PubMed  CAS  Google Scholar 

  • Walters WP, Stahl MT, Murcko MA (1998) Virtual screening – an overview. Drug Discov Today 3:160–178

    CAS  Google Scholar 

  • Wang F, Li J, Sinn AL, Knabe WE, Khanna M, Jo I, Silver JM, Oh K, Li L, Sandusky GE et al (2011) Virtual screening targeting the urokinase receptor, biochemical and cell-based studies, synthesis, pharmacokinetic characterization, and effect on breast tumor metastasis. J Med Chem 54:7193–7205

    PubMed  CAS  Google Scholar 

  • Watanabe B, Nakagawa Y, Ogura T, Miyagawa H (2004) Stereoselective synthesis of (22R)- and (22S)-castasterone/ponasterone A hybrid compounds and evaluation of their molting hormone activity. Steroids 69:483–493

    PubMed  CAS  Google Scholar 

  • Wheelock CE, Miyagawa H (2006) The omicization of agrochemical research. J Pestic Sci 31:240–244

    Google Scholar 

  • Wheelock CE, Nakagawa Y, Harada T, Oikawa N, Akamatsu M, Smagghe G, Stefanou D, Iatrou K, Swevers L (2006) High-throughput screening of ecdysone agonists using a reporter gene assay followed by 3-D QSAR analysis of the molting hormonal activity. Bioorg Med Chem 14:1143–1159

    PubMed  CAS  Google Scholar 

  • Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:W407–W410

    PubMed  Google Scholar 

  • Wilk W, Zimmermann TJ, Kaiser M, Waldmann H (2010) Principles, implementation, and application of biology-oriented synthesis (BIOS). Biol Chem 391:491–497

    PubMed  CAS  Google Scholar 

  • Wing KD (1988) RH 5849, a nonsteroidal ecdysone agonist: effects on a Drosophila cell line. Science 241:467–469

    PubMed  CAS  Google Scholar 

  • Yabuuchi H, Niijima S, Takematsu H, Ida T, Hirokawa T, Hara T, Ogawa T, Minowa Y, Tsujimoto G, Okuno Y (2011) Analysis of multiple compound-protein interactions reveals novel bioactive molecules. Mol Syst Biol 7:472

    PubMed  CAS  Google Scholar 

  • Yokota T, Arima M, Takahashi N (1982) Castasterone, a new phytosterol with plant-hormone potency, from chestnut insect gall. Tetrahedron Lett 23:1275–1278

    CAS  Google Scholar 

  • Zhou H, Zhou Y (2005) Fold recognition by combining sequence profiles derived from evolution and from depth-dependent structural alignment of fragments. Proteins 58:321–328

    PubMed  CAS  Google Scholar 

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Acknowledgements

We thank Prof. Tsunemi Yamashita for his time to edit the English. We also give sincere thanks to Dr. Paul Hawkins for providing invaluable suggestions for this review.

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Correspondence to Yoshiaki Nakagawa .

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Nakagawa, Y., Harada, T. (2013). Advanced Screening to Identify Novel Pesticides. In: Ishaaya, I., Palli, S., Horowitz, A. (eds) Advanced Technologies for Managing Insect Pests. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4497-4_7

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