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Готові списки джерел за темами / SILICO SCREENING

Добірка наукової літератури з теми "SILICO SCREENING"

Автор: Grafiati

Опубліковано: 26 жовтня 2023

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Статті в журналах з теми "SILICO SCREENING"

1

Recanatini, Maurizio, Giovanni Bottegoni, and Andrea Cavalli. "In silico antitarget screening." Drug Discovery Today: Technologies 1, no. 3 (December 2004): 209–15. http://dx.doi.org/10.1016/j.ddtec.2004.10.004.

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2

Rudisser, Simon, and Wolfgang Jahnke. "NMR and In silico Screening." Combinatorial Chemistry & High Throughput Screening 5, no. 8 (December 1, 2002): 591–603. http://dx.doi.org/10.2174/1386207023329987.

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3

Gallinger, Tom L., Samuel Y. Aboagye, Wiebke Obermann, Michael Weiss, Arnold Grünweller, Carlo Unverzagt, David L. Williams, Martin Schlitzer, and Simone Haeberlein. "First In Silico Screening of Insect Molecules for Identification of Novel Anti-Parasitic Compounds." Pharmaceuticals 15, no. 2 (January 19, 2022): 119. http://dx.doi.org/10.3390/ph15020119.

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Schistosomiasis is a neglected tropical disease caused by blood flukes of the genus Schistosoma. In silico screenings of compounds for the identification of novel anti-parasitic drug candidates have received considerable attention in recent years, including the screening of natural compounds. For the first time, we investigated molecules from insects, a rather neglected source in drug discovery, in an in silico screening approach to find novel antischistosomal compounds. Based on the Dictionary of Natural Products (DNP), we created a library of 1327 insect compounds suitable for molecular docking. A structure-based virtual screening against the crystal structure of a known druggable target in Schistosoma mansoni, the thioredoxin glutathione reductase (SmTGR), was performed. The top ten compounds predominantly originated from beetles and were predicted to interact particularly with amino acids in the doorstop pocket of SmTGR. For one compound from a jewel beetle, buprestin H, we tested and confirmed antischistosomal activity against adult and juvenile parasites in vitro. At concentrations with anti-parasitic activity, we could also exclude any unspecific cytotoxic activity against human HepG2 cells. This study highlights the potential of insect molecules for the identification of novel antischistosomal compounds. Our library of insect-derived molecules could serve not only as basis for future in silico screenings against additional target proteins of schistosomes, but also of other parasites.

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4

Seifert, Markus H. J., Kristina Wolf, and Daniel Vitt. "Virtual high-throughput in silico screening." BIOSILICO 1, no. 4 (September 2003): 143–49. http://dx.doi.org/10.1016/s1478-5382(03)02359-x.

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5

Reddy, Bandi Deepa, and Ch M. Kumari Chitturi. "Screening and Identification of Microbial Derivatives for Inhibiting Legumain: An In silico Approach." Journal of Pure and Applied Microbiology 12, no. 3 (September 30, 2018): 1623–30. http://dx.doi.org/10.22207/jpam.12.3.69.

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6

Ma, Dik-Lung, Victor Pui-Yan Ma, Daniel Shiu-Hin Chan, Ka-Ho Leung, Hai-Jing Zhong, and Chung-Hang Leung. "In silico screening of quadruplex-binding ligands." Methods 57, no. 1 (May 2012): 106–14. http://dx.doi.org/10.1016/j.ymeth.2012.02.001.

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7

Lin, Li-Chiang, Adam H. Berger, Richard L. Martin, Jihan Kim, Joseph A. Swisher, Kuldeep Jariwala, Chris H. Rycroft, et al. "In silico screening of carbon-capture materials." Nature Materials 11, no. 7 (May 27, 2012): 633–41. http://dx.doi.org/10.1038/nmat3336.

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8

Arvidson, Kirk B., Luis G. Valerio, Marilyn Diaz, and Ronald F. Chanderbhan. "In Silico Toxicological Screening of Natural Products." Toxicology Mechanisms and Methods 18, no. 2-3 (January 2008): 229–42. http://dx.doi.org/10.1080/15376510701856991.

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9

Vidal, David, and Jordi Mestres. "In Silico Receptorome Screening of Antipsychotic Drugs." Molecular Informatics 29, no. 6-7 (July 9, 2010): 543–51. http://dx.doi.org/10.1002/minf.201000055.

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10

Zaini, Vikra Ardiansyah, Purwantiningsih Sugita, Luthfan Irfana та Suminar Setiati Achmadi. "In Silico Screening Anticancer of Six Triterpenoids toward miR-494 and TNF-α Targets". Jurnal Kimia Sains dan Aplikasi 23, № 4 (7 квітня 2020): 117–23. http://dx.doi.org/10.14710/jksa.23.4.117-123.

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Анотація:

Hepatocellular carcinoma (HCC) accounts for up to 90% of all primary liver cancers worldwide. Cinobufagin is recognized to inhibit miR-494 as the HCC target. Increased expression of TNF-α results in an inadequate response to liver anticancer drugs. The models in this study were cinobufagin, cycloartenol, and ethyl acetate fractions of Ganoderma lucidum, 2–5. Seven docking targets in this study were Akt, ERK1, ERK2, PI3K, TNF-α, TNFR1, and TNFR2. Cycloartenol and compound 4 comply with Veber’s rules, Lipinski’s rule of 5, and demonstrate moderate toxicity. The action implies a potential docking target since it produces bond affinities with the compound 2–5 that agree with the IC50 in the literature, which is based on in vitro experiments. Akt as a receptor target is AZD5363. Cycloartenol shows a low ability to inhibit Akt. Conversely, compound 4 inhibits the Akt better than that of cycloartenol, although it is not as good as cinobufagin and AZD5363. Therefore, compound 4, a triterpenoid with a basic framework of lanostane has the potential to be an anticancer candidate for the liver.

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Більше джерел

Дисертації з теми "SILICO SCREENING"

1

Dunkel, Mathias [Verfasser]. "3D Konformationsdatenbanken für das in silico Screening / Mathias Dunkel." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2008. http://d-nb.info/1023262142/34.

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2

Barakat, Nora Hisham. "Combining in vivo and in silico screening for protein stability." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3258327.

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Анотація:

Thesis (Ph. D.)--University of California, San Diego and San Diego State University, 2007.
Title from first page of PDF file (viewed May 29, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 137-152).

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3

Füllbeck, Melanie. "In silico und in vitro Screening von Proteinliganden zur Apoptoseinduktion." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät I, 2007. http://dx.doi.org/10.18452/15702.

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Анотація:

Die moderne Tumormedizin hat das Ziel die deregulierte Wachstumskontrolle und die Überlebensstrategien maligner Tumoren zu überwinden. Mittels computerbasierter Methoden sollten hierzu in dieser Arbeit neue apoptoseinduzierende Substanzen gefunden und deren Wirksamkeit in späteren in vitro Experimenten überprüft werden. In drei Modellprojekten konnten neue Substanzen identifiziert werden, die Apoptose in Tumorzellen induzieren. Im ersten Projekt wurden Inhibitoren der an das COP9 Signalosom (CSN-) assoziierten Kinasen CK2 und PKD mittels der Leitstrukturen Curcumin und Emodin gefunden. Im zweiten Projekt wurde der Naturstoff Betulinsäure (betulinic acid, BA) bezüglich seines Wirkmechanismus untersucht. Die Ergebnisse haben gezeigt, dass die BA-induzierte Apoptose weitestgehend unabhängig von den pro- und anti-apoptotischen Proteinen der Bcl-2-Familie, aber in Abhängigkeit von aktiven Caspasen, ausgelöst wird. Durch ein in silico Screening und die Verwendung eines neuen Eigenschaftsfilters konnten neuen BA-Analoga identifiziert werden. Zur Bewertung der Ergebnisse des in silico Screenings wurden Daten des National Cancer Institutes (NCI) verwendet. Im dritten Projekt wurden mittels in silico Screening, Docking-Experimenten und in vitro Screenings zwei neue Bcl-2-Inhibitoren identifiziert, die derzeit in funktionellen Experimenten getestet werden. Durch den Einbau eines niedermolekularen, photoschaltbaren Moleküls an die Aminosäuren-Seitenketten des alpha-helikalen Peptides aus der BH3-Domäne von Bid konnte eine gezielte Aktivierung und damit auch eine gezielte Apoptoseinduktion in Tumorzellen ausgelöst werden. Die Methode des in silico Screenings hat gezeigt, dass die Zeit und Kosten für die Suche nach Wirkstoffen reduziert werden können. Die gefundenen Treffer können als neue Leitstrukturen für weitere in silico Screenings ihre Verwendung finden oder mit Hilfe von Optimierungsprozessen in weitere Stufen der Entwicklung eintreten.
Nowadays, cancer research is focused on the overcoming of survival strategies of malign tumors. In the present work, computer-based methods lead to the identification of novel apoptosis inducing molecules, whose potency should be validated in in vitro experiments. Novel compounds, which induce apoptosis in cancer cells, could be identified on the basis of three projects. Inhibitors for the COP9 signalosome (CSN) associated kinases CK2 and PKD could be discovered using curcumin and emodin as lead compounds. Investigations concerning the mechanism-of-action of betulinic acid (BA) should give information about the function of the Bcl-2 protein family in the BA induced cell death. The experiments, which are focused on the mitochondrial signalling pathway, revealed that BA induces apoptosis in an almost independent manner with regards to the pro- and anti-apoptotic Bcl-2 proteins, but dependent on the presence of activated caspases. Via an in silico screening and the utilisation of a new property filter, novel BA analogues could be identified. For the first time, the data of the National Cancer Institute (NCI) is employed to evaluate results from the in silico screening. In the third project two novel Bcl-2 inhibitors have been identified via in silico screenings, docking experiments and in vitro screenings, which are performed at the moment. The insertion of a photo-switchable compound to the amino acid side chain of an alpha-helical peptide from the pro-apoptotic protein Bid triggered the effect of a modulator, which results in a controllable activation and initiation of apoptosis in tumor cells. In silico screenings as a reliable method corroborated that a systematical evaluation of the virtual hits could decrease the time and costs of experimental testings. The identified hits could serve as novel lead compounds for further in silico screenings or enter the next steps in the development of novel drugs using optimisation methods.

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4

MONTE, M. LO. "IN SILICO SCREENING OF TASTE RECEPTORS: AN INTEGRATE MODELING APPROACH." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/252746.

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Taste is one of the five senses and accounts for the sensory impression of food or other substances on the tongue. It represents an innate mechanism of defence by which humans and animals detect safety or threat in food. Notably, taste is a whole-body experience since taste receptors, besides being located in the taste buds, are also found in non-sensory tissues, like the gut or the airways, playing still not completely known roles, for example, in glucose metabolism as well as in energy homeostasis. This clearly lays the groundwork for scientific investigations aimed to develop chemical tools through which modulate these physiopathological mechanisms. Although both GPCR and Ion Channels mediate these processes, this Thesis focuses on the latter class, so far less explored than the former one, involving four members of the Transient Potential Receptors family, namely TRPM8, TRPM5, TRPV1 and TRPV4. Although if each study presented its own objectives, peculiarities and relative computational approaches, a common path can be traced for all of them. First, the three-dimensional structure was generated by homology modelling techniques, by exploiting a well validated fragmental approach, then the obtained homology model was tested by docking calculations, which while including preliminary correlative studies, were always aimed at developing reliable strategies for virtual screening campaigns. The here reported results provide further remarkable confirmations for the reliability of the already modelled (and exploited) TRPM8 model, while the here generated TRPM5 and TRPV4 models afford results (despite obtained in a validating preliminary phase) in line with those of TRPM8 further emphasizing the reliability of the fragmental approach. Not to mention that the described targeted strategy to model TRPV1 suggests that previously generated homology models can be then exploited to assist the modeling of highly homologous proteins still obtaining encouraging results but with a significant saving of the required computational efforts. Finally, the here proposed TRPM8 results offer a convincing proof of the potential improvements that may be obtained combining ligand-based and structure-based approaches in a virtual screening analysis.

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5

Harding, Simon D. "Database analysis of protein-peptide interactions and in silico screening for peptidomimetics." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/10935.

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A potential path to the development of small-molecule inhibitors is to identify small-molecules that mimic the interactions of short peptides with proteins. The present study uses Perl scripts and a MySQL database to build a unique dataset of 258 protein-peptide interactions (ProPep) from structures contained in the Protein Data Bank. The physiochemical and structural nature of protein-peptide interfaces were analysed in part using a novel amino acid pictogram analysis alongside accessible surface area, residue pairing and amino acid composition analysis. The results indicate that, for the peptide, proline residues and tyrosine residues play specific roles in protein-peptide interfaces. Furthermore it was observed that the peptide residues are significantly more buried than the residues of the cognate protein surface. The virtual screening program LIDAEUS was used to mine chemical databases to identify novel peptidomimetic compounds that have evincible binding to protein targets of therapeutic interest. Target-based and fragment-based virtual screening identified a series of potential compounds targeting the interaction between p21 and PCNA. Whilst the docking results were promising, results from testing in biological assays were inconclusive. A target-based virtual screening approach to identify small-molecule mimics of the interaction between the GnRH peptide and GnRH receptor yielded two promising compounds that demonstrated weak binding in biological assays. A third study to identify small-molecules binding to the SH3 domain of PSD-95 produced some promising hit compounds that as yet have not been tested in binding assays.

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6

Lauro, Gianluigi. "New techniques of molecular modelling and structural chemistry for the development of bioactive compounds." Doctoral thesis, Universita degli studi di Salerno, 2013. http://hdl.handle.net/10556/986.

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2011 - 2012
Computational chemistry represents today a valid and fast tool for the research of new compounds with potential biological activity. The analysis of ligand-macromolecule interactions and the evaluation of possible “binding modes” have a crucial role for the design and the development of new and more powerful drugs. In silico Virtual Screening campaigns of large libraries compounds (fragments or drug-like) on a specific target allow the selection of promising compounds, leading the identification of new scaffolds. The accurate analysis and the comparison of different bioactive compounds clarify the molecular basis of their interaction and the construction of pharmacoforic models. In parallel, another crucial aspect of pharmacological research is the identification of targets of interaction of bioactive molecules, and this is particularly true for compounds from natural sources. In fact, a wide range of drug tests on a large number of biological targets can represent a useful approach for the study of natural products, but often one of the main problems is their limited availability. Starting from these assumptions, a new computational method named Inverse Virtual Screening is described in details in this thesis. The different works based on this approach were performed considering panels of targets involved in the cancer events, determining the identification of the specific antitumor activity of the natural compounds investigated. Inverse Virtual Screening studies were performed by means of molecular docking experiments on different natural compounds, organized in small libraries or as single compounds. Firstly, a mathematical method for the exclusion of false positive and false negative results was proposed applying a normalization of the predicted binding energies (expressed in kcal/mol) obtained from the docking calculations. Then this approach was applied on a library of 10 compounds extracted from natural sources, obtaining a good validation through in vitro biological tests. Afterwards, another study was performed on the cyclopeptide namalide. Its biological inhibitory activity and selectivity on Carboxipeptidase A target was in accordance with Inverse Virtual Screening results. Virtual Screening topic was also inspected analyzing the efficacy of Molecular Dynamics-based methods for the accurate calculations of the binding affinities. This work was conducted on a library of 1588 compounds (44 ligands + 1544 decoys) extracted from the DUD database on trypsin target, using the Linear Interaction Energy (LIE) method by means of extensive Molecular Dynamics simulations. Four different LIE results obtained combining different scaling factors were compared with docking results, evaluating and comparing ROC and enrichment curves for each of the considered methods. Poor results were obtained with LIE, and further analysis with MM-GBSA and MM-PBSA approaches are under investigation. Moreover, in silico screenings were performed for the detailed study of natural compounds whose activities are known a priori. With this procedure, several binding modes were reported for a library of compounds on PXR target, whose activity or inactivity were rationalized comparing their binding poses with that of Solomonsterol A, used as a reference compound on this receptor. The presence/absence of biological activity of another library of compounds extracted from the marine sponge Plakinastrella Mamillaris on PPAR-γ and for the diterpene oridonin on HSP70 1A are described at a molecular level with molecular docking and Molecular Dynamics simulations. The putative binding modes for the reported molecules was described offering a complete rationalization of docking results, evaluating how ligand target specific interactions (e.g. hydrophobic, hydrophilic, electrostatic contacts) can influence their biological activity. [edited by author]
La chimica computazionale rappresenata un valido e rapido strumento per l’identificazione di nuovi potenziali composti bioattivi. L’analisi delle interazioni ligando-target macromolecolare e la valutazione di un possibile “binding mode” sono cruciali per il design e lo sviluppo di nuovi potenziali farmaci. Il Virtual Screening di grandi librerie di composti (fragments o drug-like) condotto in silico su uno specifico recettore può permettere la selezione di composti dalla promettente attività, e parallelamente l’identificazione di nuovi scaffolds molecolari. L’analisi accurata dei modelli di interazione ligando-recettore e il confronto di tali modelli con quelli di composti dalla già nota attività permette la costruzione di un modello farmacoforico, punto di partenza per successivi studi di potenziamento dell’attività farmacologica. Parallelamente, un altro aspetto fondamentale della ricerca farmacologica è rappresentato dall’identificazione dei targets di interazione per composti dalla nota bioattività, e questo risulta particolarmente interessante per i composti di origine naturale. Infatti, per tale classe di molecole sarebbe molto utile effettuare tests biologici su un elevato numero di recettori, ma ciò risulta spesso proibitivo a causa della scarsa quantità di composto disponibile. Partendo da tali presupposti, nella presente tesi è descritto approfonditamente un nuovo metodo computazionale definito Inverse Virtual Screening. I vari lavori basati su questo nuovo tipo di approccio sono stati effettuati considerando pannelli composti da diversi targets coinvolti nello sviluppo del cancro, portando all’identificazione della specifica attività antitumorale dei vari composti naturali investigati. Gli studi basati sull’Inverse Virtual Screening sono stati effettuati attraverso calcoli di Molecular Docking utilizzando diversi composti naturali, raggruppati in piccole librerie o studiati singolarmente. In primo luogo, è stato proposto un metodo matematico con l’obiettivo di escludere i falsi positivi e i falsi negativi applicando una normalizzazione delle affinità di legame predette (espresse in kcal/mol). Successivamente, tale approccio è stato applicato su una libreria di 10 composti di origine naturale, validando l’applicabilità di tale metodo attraverso tests biologici in vitro. Successivamente, un ulteriore studio è stato incentrato su un ciclopeptide definito namalide, la cui attività biologica su Carbossipeptidasi A era in totale accordo con i dati provenienti dallo studio di Inverse Virtual Screening condotto. Il Virtual Screening è stato inoltre studiato anche analizzando l’efficacia dei metodi per il calcolo accurato delle affinità di legame basati su simulazioni di Dinamica Molecolare. Tale studio è stato condotto su una libreria di 1588 composti (44 ligandi + 1544 decoys, estratti dal DUD database) sul target tripsina, utilizzando il metodo LIE (Linear Interaction Energy) attraverso un elevato numero di simulazioni di Dinamica Molecolare. Sono stati ottenuti quattro differenti scale di affinità predetta (attraverso quattro combinazioni di differenti scaling factors) e sono stati confrontati con i risultati derivanti dai calcoli di Molecular Docking, valutando e confrontando curve ROC e di enrichment. Attraverso il metodo LIE sono stati ottenuti risultati non incoraggianti, e quindi ulteriori analisi attraverso metodi MM-GBSA e MM-PBSA sono in corso di studio. Inoltre, screenings in silico sono stati effettuati anche per lo studio dettagliato di altri composti naturali la cui attività era nota a priori. Attraverso questa procedura, sono stati proposti diversi modelli di binding di una libreria di composti sul target PXR, e per tali composti è stata razionalizzata l’attività/inattività confrontando il loro binding mode con quello del Solomonsterol A, utilizzato come composto di riferimento su tale target. La presenza/assenza di attività biologica è stata è stata descritto a livello molecolare per un’altra classe di composti estratti dalla spugna Plakinastrella Mamillaris sul target PPAR-γ e sul diterpene oridonina sul target HSP70 1A attraverso esperimenti combinati di Molecular Docking e Molecular Dynamics. Sono stati proposti e descritti approfonditamente modelli di binding di tali composti, valutando come specifiche interazioni ligando-target macromolecolare (di natura idrofobica, elettrostatica o caratterizzata dalla presenza di specifici legami ad idrogeno) possano influenzare l’attività biologica. [a cura dell'autore]
XI n.s.

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7

Rowlatt, Jack D. "Characterisation of putative glycan and drug binding proteins predicted using in silico screening methods." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/397633.

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This thesis describes the characterisation of six targets for a novel antimicrobial drug 3,4-methylenedioxy-beta-nitropropene (BDM-I) shown to inhibit bacterial, protozoal and fungal infections and the characterisation putative carbohydrate binding proteins (CBP) BT_411 and BT_3781. Furthermore, described here is the experimental validation of bioinformatic programs SPOT-Ligand, of which identified six putative drug targets for BDM-I, and SPOT-Struc, that predicted BT_411 and BT_3781 as CBPs. Specifically I expressed and purified the six BDM-I targets predicted by SPOT-Ligand and expressed the two SPOT-Struc predicted putative CBPs BT_411 and BT_3781. The drug targets were then used to identify a potential mechanism of action for BDM-I while the putative CBPs were likewise characterised to identify their carbohydrate binding affinity. Lastly the characterisation results were then utilised to evaluate the predictive capabilities of SPOT-Ligand and SPOT-Struc and in turn help clarify the role of bioinformatics in experimental research. The six BDM-I targets (Gene name: EF0414, ubiE, ftsZ5, Lebu_1328, acpD, and ubiH) were expressed in E. coli BL21 (DE3) cells with expressed recombinant soluble protein purified to homogeneity using HIS-select nickel affinity and size exclusion chromatography (SEC). Likewise, two putative CBPs BT_411 and BT_3781 as well as an additional novel mushroom lectin PSL-2 (used as a positive lectin control), were expressed in E. coli BL21 (DE3) cells and purified to homogeneity using affinity chromatography and SEC. All proteins were confirmed pure by SDS-PAGE and of those proteins containing a HIS-tag (all except PSL-2), western blot immunodetection. All purified proteins were then measured using circular dichroism (CD) spectroscopy as a quality control step to determine if they had denatured before proceeding with further characterisation. The six potential ii drug targets were analysed for BDM-I affinity using surface plasmon resonance (SPR) with those showing affinity for BDM-I further characterised by computational docking analysis. Similarly, putative CBPs BT_411 and BT_3781 in conjunction with PSL-2 were analysed for carbohydrate affinity with a wide variety of glycans using SPR followed by computational docking analysis of the CBPs with some of the SPR defined glycan matches. Results showed that BDM-I has high affinity for drug target AcpD from Salmonella enterica, serovar Typhimurium, a bacterial azoreductase protein responsible for the breakdown of azo dyes in S. typhimurium (S. typhimurium causes gastroenteritis in humans). SPR analysis of the binding of BDM-I to AcpD revealed an equilibrium dissociation constant (KD) of 0.58 μM with an association constant (ka) of 9.4 x 104 M-1s-1 and dissociation constant (kd) of 9.7 x 10-4 s-1, suggesting that BDM-I binds rapidly and easily to acpD followed by a slow dissociation. Docking analysis of BDM-I in AcpD showed hydrogen bonds between a BDM-I nitro group and residues Ala115 and Asn98, with a binding energy of – 6.7 kcal/mol. AcpD structural alignment with an azoreductase that also shows nitroreductase activity, PaAzoR from Pseudomonas aeruginosa, showed a high enough structural similarity with AcpD to computationally infer that function is likely shared between the two proteins. As such, it was computationally determined that AcpD may act on BDM-I as a nitroreductase via the binding of BDM-I’s nitro group in order to reduce it to chemical intermediates (similar to paAzoR nitroreductase activity). This reveals a possible mechanism of action for BDM-I; namely that bacterial nitroreductases may bind and reduce the nitro group on BDM-I resulting in the production of bacterially toxic intermediates. SPR analysis of BT_411 revealed carbohydrate affinity for β1,4 linked N-acetylglucosamines (GlcNAc) and 2,3 linked sialic acids (Neu5Ac) with KD’s between iii 0.10 μM and 0.23 μM. Computational analysis of BT_411 further indicated preferential affinity towards GlcNAc (-4.6 kcal/mol) over Neu5Ac and indicated that BT_411 is likely a carbohydrate binding module (CBM) showing possible functional attributes of a βGNase (hydrolase) that catalyses the reduction of GlcNAc glycosidic bonds. SPR analysis of BT_3781 indicated carbohydrate affinity for fucose (Fuc) and galactose (Gal) containing glycans; specifically blood group H, B and A showing high affinity with KD’s between 0.17 μM and 0.34 μM. Computational analysis of BT_3781 supported SPR analysis indicating affinity with Fuc, in particular blood group H disaccharide (Fucα1-2Gal) with a binding energy of -6.8 kcal/mol. Indicating that BT_3781 is also a CBM with functional similarities to that of a glycosidic hydrolase; namely a fucosidase that catalyses the reduction of Fucα1-2 linkages. SPR analysis of the positive control PSL-2 confirmed crystallography data of the protein that showed preferential binding to Gal and Fuc residues. Specifically, SPR indicated PSL-2 has high affinity towards blood group B (Galα1-3(Fucα1-2)Galβ1-4Glc), implying that PSL-2 may be a blood group lectin. Moreover, successful characterisation of PSL-2 validates the experimental procedures used in the characterisation of BT_411 and BT_3781. The characterisation results of BDM-I drug targets and CBPs BT_411 and BT_3781 validate the supportive role of bioinformatic programs SPOT-Ligand and SPOT-Struc in experimental research. Mainly in the structural predication of drug targets and identification of novel CBPs.
Thesis (Masters)
Doctor of Philosophy (PhD)
School of Medical Science
Griffith Health
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8

Salentin, Sebastian. "In Silico Identification of Novel Cancer Drugs with 3D Interaction Profiling." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-226435.

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Cancer is a leading cause of death worldwide. Development of new cancer drugs is increasingly costly and time-consuming. By exploiting massive amounts of biological data, computational repositioning proposes new uses for old drugs to reduce these development hurdles. A promising approach is the systematic analysis of structural data for identification of shared binding pockets and modes of action. In this thesis, I developed the Protein-Ligand Interaction Profiler (PLIP), which characterizes and indexes protein-ligand interactions to enable comparative analyses and searching in all available structures. Following, I applied PLIP to identify new treatment options in cancer: the heat shock protein Hsp27 confers resistance to drugs in cancer cells and is therefore an attractive target with a postulated drug binding site. Starting from Hsp27, I used PLIP to define an interaction profile to screen all structures from the Protein Data Bank (PDB). The top prediction was experimentally validated in vitro. It inhibits Hsp27 and significantly reduces resistance of multiple myeloma cells against the chemotherapeutic agent bortezomib. Besides computational repositioning, PLIP is used in docking, binding mode analysis, quantification of interactions and many other applications as evidenced by over 12,000 users so far. PLIP is provided to the community online and as open source.

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9

Youngs, Louise Claire. "Evaluation of in silico and in vitro screening methods for characterising endocrine disrupting chemical hazards." Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/9717.

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Anthropogenic activities have drastically altered chemical exposure, with traces of synthetic chemicals detected ubiquitously in the environment. Many of these chemicals are thought to perturb endocrine function, leading to declines in reproductive health and fertility, and increases in the incidence of cancer, metabolic disorders and diabetes. There are over 90 million unique chemicals registered under the Chemical Abstracts Service (CAS), of which only 308,000 were subject to inventory and/or regulation, in September 2013. However, as a specific aim of the EU REACH regulations, the UK is obliged to reduce the chemical safety initiatives reliance on in vivo apical endpoints, promoting the development and validation of alternative mechanistic methods. The human health cost of endocrine disrupting chemical (EDC) exposure in the EU, has been estimated at €31 billion per annum. In light of the EU incentives, this study aims to evaluate current in silico and in vitro tools for EDC screening and hazard characterisation; testing the hypothesis that in silico virtual screening accurately predicts in vitro mechanistic assays. Nuclear receptor binding interactions are the current focus of in silico and in vitro tools to predict EDC mechanisms. To the author’s knowledge, no single study has quantitatively assessed the relationship between in silico nuclear receptor binding and in vitro mechanistic assays, in a comprehensive manner. Tripos ® SYBYL software was used to develop 3D-molecular models of nuclear receptor binding domains. The ligand binding pockets of estrogen (ERα and ERβ), androgen (AR), progesterone (PR) and peroxisome proliferator activated (PPARγ) receptors were successfully modelled from X-ray crystal structures. A database of putative-EDC ligands (n= 378), were computationally ‘docked’ to the pseudo-molecular targets, as a virtual screen for nuclear receptor activity. Relative to in vitro assays, the in silico screen demonstrated a sensitivity of 94.5%. The SYBYL Surflex-Dock method surpassed the OECD Toolbox ER-Profiler, DfW and binary classification models, in correctly identifying endocrine active substances (EAS). Aiming to evaluate the current in vitro tools for endocrine MoA, standardised ERα transactivation (HeLa9903), stably transfected AR transactivation (HeLa4-11) assays in addition to novel transiently transfected reporter gene assays, predicted the mechanism and potency of test substances prioritised from the in silico results (n = 10 potential-EDCs and 10 hormone controls). In conclusion, in silico SYBYL molecular modelling and Surflex-Dock virtual screening sensitively predicted the binding of ERα/β, AR, PR and PPARγ potential EDCs, and was identified as a potentially useful regulatory tool, to support EAS hazard identification.

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10

Elkaïm, Judith. "Drug design in silico : criblage virtuel de protéines à visée thérapeutique." Thesis, Bordeaux 1, 2011. http://www.theses.fr/2011BOR14444/document.

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Les processus qui mènent à la découverte de nouveaux médicaments sont longs et fastidieux, et les taux de succès sont relativement faibles. L’identification de candidats par le biais de tests expérimentaux s’avère coûteuse, et nécessite de connaître en profondeur les mécanismes d'action de la protéine visée afin de mettre en place des essais efficaces. Le criblage virtuel peut considérablement accélérer ces processus en permettant une évaluation rapide de chimiothèques de plusieurs milliers de molécules afin de déterminer lesquelles sont les plus susceptibles de se lier à une cible. Ces dernières années ont ainsi été témoins de quelques success stories dans ce domaine.Le premier objectif de ce travail était de comparer différents outils et stratégies couramment utilisés dans le criblage virtuel “structure-based”, puis de les appliquer à des cibles protéiques à visée thérapeutique, en particulier dans le cadre du cancer.La protéine kinase GSK3 et un test set de ligands connus ont servi de modèle pour différentes études méthodologiques ayant pour but d’évaluer les programmes de docking et de scoring à notre disposition. En particulier, l’utilisation de plusieurs structures relaxées du récepteur ou l’insertion de torsions sur certains résidus du site actif pendant le docking ont permis d’évaluer l’influence de la flexibilité de la protéine. L’utilité et la pertinence d’outils permettant de générer automatiquement les structures 3D des ligands et de méthodes de consensus scoring ont également été étudiées.Un criblage virtuel de la Pontine, une ATPase impliquée dans la croissance tumorale pour laquelle aucun inhibiteur n’était connu, a permis la sélection de candidats issus de banques de données commerciales. Ces molécules ont été testées dans un essai enzymatique par le biais d’une collaboration, et quatre d’entre elles se sont révélées capable d’inhiber l’activité ATPase de la Pontine. Le criblage de bases de ligands synthétisés et imaginés dans l’équipe a également fourni un inhibiteur original. Au contraire, l’étude de la sPLA2-X humaine, une phospholipase dont l’activité catalytique est dépendante d’un atome de Ca2+ localisé au sein du site actif, a montré les limites de nos outils de docking qui n’ont pas été capables de gérer cet ion métallique et mis en évidence la nécessité de mettre en place d’autres outils
The process of drug discovery is long and tedious. Besides, it is relatively inefficient in terms of hit rate. The identification of candidates through experimental testing is expensive and requires extensive data on the mechanisms of the target protein in order to develop efficient assays. Virtual screening can considerably accelerate the process by quickly evaluating large databases of compounds and determining the most likely to bind to a target. Some success stories have emerged in the field over the last few years.The objectives of this work were first, to compare common tools and strategies for structure-based virtual screening, and second, to apply those tools to actual target proteins implied notably in carcinogenesis.In order to evaluate the docking and scoring programs available, the protein kinase GSK3 and a test set of known ligands were used as a model to perform methodological studies. In particular the influence of the flexibility of the protein was explored via relaxed structures of the receptor or the insertion of torsions on the side chains of residues located in the binding site. Studies concerning the automatic generation of 3D structures for the ligands and the use of consensus scoring also provided insights on the usability of these tools while performing a virtual screening.Virtual screening of the human protein Pontin, an ATPase implied in tumor cell growth for which no inhibitors were known, allowed the prioritization of compounds from commercial databases. These compounds were tested in an enzymatic assay via a collaboration, and led to the identification of four molecules capable of inhibiting the ATPase activity of Pontin. Additional screens of in-house oriented databases also provided at least one innovative inhibitor for this protein. On the contrary, a study of the human PLA2-X, a phospholipase that requires a Ca2+ atom to bind to its active site in order to catalyze the hydrolysis of its substrate, revealed the limits of our docking tools that could not handle the metal ion and the need for new tools

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Книги з теми "SILICO SCREENING"

1

Uchida, Shizuka. Annotating new genes: From in silico screening to experimental validation. Oxford: Woodhead Publishing Limited, 2012.

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2

1st, Naga Raju Chinthakunta, Suresh Kumar Chitta 2nd, Anuradha C. M. 3rd, and Rajani Vallepu IV. In Silico Screening of Natural Compounds As Potential Inhibitors of GPR120 to Prevent Cancer. INSC International Publisher (IIP), 2021.

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3

Atta-ur-Rahman and M. Iqbal Choudhary, eds. Frontiers in Cardiovascular Drug Discovery: Volume 4. BENTHAM SCIENCE PUBLISHERS, 2019. http://dx.doi.org/10.2174/97816810839951180401.

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Frontiers in Cardiovascular Drug Discovery is an eBook series devoted to publishing the latest advances in cardiovascular drug design and discovery. Each volume brings reviews on the biochemistry, in-silico drug design, combinatorial chemistry, high-throughput screening, drug targets, recent important patents, and structure-activity relationships of molecules used in cardiovascular therapy. The eBook series should prove to be of great interest to all medicinal chemists and pharmaceutical scientists involved in preclinical and clinical research in cardiology. The fourth volume of the series covers the following topics: -Aspirin administration -Adenosine receptor targeting for cardiovascular therapy -Drug treatment of patients with coronary stenting -Immunosuppressive drugs in heart transplantation -PCSK9 inhibition for lowering LDL-C levels.

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4

Lin, C. W., N. F. Chiu, and C. C. Chang. Modulation design of plasmonics for diagnostic and drug screening. Edited by A. V. Narlikar and Y. Y. Fu. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533060.013.18.

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This article discusses the modulation design of plasmonics for diagnosis and drug screening applications. It begins with an overview of the advances made in terms of theoretical insights, focusing on the origins of surface plasmon wave and manipulation, admittance loci design method, and surface plasmon grating coupled emission. It then considers how prism coupler, Ge-doped silica waveguide, nanograting and active plasmonics can trigger the excitation of surface plasmon resonance (SPR). It also examines the metallic effect of long-range surface plasmon resonance and conducting metal oxide as adhesive layer before describing three SPR waveguide biosensors that were developed for the realization of a hand-held SPR system. In particular, it presents a lateral-flow microfluidic channel based on a nitrocellulose membrane and integrated with a SPR waveguide biosensor to achieve dynamic detection. Finally, the article evaluates the biomolecular layer effect, with emphasis on kinetics analysis of antibody binding.

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5

Narlikar, A. V., and Y. Y. Fu, eds. Oxford Handbook of Nanoscience and Technology. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199533060.001.0001.

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This volume highlights engineering and related developments in the field of nanoscience and technology, with a focus on frontal application areas like silicon nanotechnologies, spintronics, quantum dots, carbon nanotubes, and protein-based devices as well as various biomolecular, clinical and medical applications. Topics include: the role of computational sciences in Si nanotechnologies and devices; few-electron quantum-dot spintronics; spintronics with metallic nanowires; Si/SiGe heterostructures in nanoelectronics; nanoionics and its device applications; and molecular electronics based on self-assembled monolayers. The volume also explores the self-assembly strategy of nanomanufacturing of hybrid devices; templated carbon nanotubes and the use of their cavities for nanomaterial synthesis; nanocatalysis; bifunctional nanomaterials for the imaging and treatment of cancer; protein-based nanodevices; bioconjugated quantum dots for tumor molecular imaging and profiling; modulation design of plasmonics for diagnostic and drug screening; theory of hydrogen storage in nanoscale materials; nanolithography using molecular films and processing; and laser applications in nanotechnology. The volume concludes with an analysis of the various risks that arise when using nanomaterials.

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Частини книг з теми "SILICO SCREENING"

1

Luque, F. J., and X. Barril. "In Silico Screening." In Protein Surface Recognition, 211–35. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470972137.ch8.

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Egbuna, Chukwuebuka, Santwana Palai, Israel Ehizuelen Ebhohimen, Andrew G. Mtewa, Jonathan C. Ifemeje, Genevieve D. Tupas, and Toskë L. Kryeziu. "Screening of Natural Antidiabetic Agents." In Phytochemistry: An in-silico and in-vitro Update, 203–35. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6920-9_11.

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3

K. C., Dhanya, Aditya Menon, and Laxmi Shanker Rai. "In-vitro Models in Anticancer Screening." In Phytochemistry: An in-silico and in-vitro Update, 251–65. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6920-9_13.

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4

Li, Shawn S. C., and Lei Li. "SH2 Ligand Prediction–Guidance for In-Silico Screening." In Methods in Molecular Biology, 77–81. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6762-9_5.

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5

Fischer, B., H. Merlitz, and W. Wenzel. "Increasing Diversity in In-silico Screening with Target Flexibility." In Lecture Notes in Computer Science, 186–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11560500_17.

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6

Merlitz, Holger, and Wolfgang Wenzel. "High Throughput in-silico Screening against Flexible Protein Receptors." In Computational Science and Its Applications – ICCSA 2004, 465–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24767-8_48.

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7

Thrithamarassery Gangadharan, Nandu, Ananda Baskaran Venkatachalam, and Shiburaj Sugathan. "High-Throughput and In Silico Screening in Drug Discovery." In Bioresources and Bioprocess in Biotechnology, 247–73. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3573-9_11.

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8

Myrianthopoulos, Vassilios, George Lambrinidis, and Emmanuel Mikros. "In Silico Screening of Compound Libraries Using a Consensus of Orthogonal Methodologies." In Methods in Molecular Biology, 261–77. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8630-9_15.

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9

Akhoon, Bashir A., Krishna P. Singh, Madhumita Karmakar, Suchi Smita, Rakesh Pandey, and Shailendra K. Gupta. "Virtual screening and prediction of the molecular mechanism of bioactive compoundsin silico." In Biotechnology of Bioactive Compounds, 371–94. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118733103.ch15.

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10

Srivastava, Supriya, and Puniti Mathur. "In Silico Modeling and Screening Studies of PfRAMA Protein: Implications in Malaria." In Recent Studies on Computational Intelligence, 91–101. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8469-5_8.

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Тези доповідей конференцій з теми "SILICO SCREENING"

1

Arrigo, Patrizio, Norbert Maggi, and Carmelina Ruggiero. "In silico screening of Rac1 ligand specificity." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4650110.

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2

Osman, Ahmed M., and Hanaa M. Alam EL-Din. "In-Silico Screening of Potential Anti-Glycoprotein of Nipah Virus." In 2021 Tenth International Conference on Intelligent Computing and Information Systems (ICICIS). IEEE, 2021. http://dx.doi.org/10.1109/icicis52592.2021.9694143.

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3

Pal, Rajesh, Gauri Misra, and Puniti Mathur. "In silico screening of small molecule modulators of Zika virus proteins." In 2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence (Confluence). IEEE, 2017. http://dx.doi.org/10.1109/confluence.2017.7943179.

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4

Fukunishi, Yoshifumi. "In Silico Drug Screening Based on a Protein-Compound Affinity Matrix." In 2008 International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies (BIOTECHNO). IEEE, 2008. http://dx.doi.org/10.1109/biotechno.2008.10.

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5

Soonwook Hwang, Sehoon Lee, Sangdo Lee, Jincheol Kim, Hanh Thi Thanh Nguyen, Doman Kim, Vincent Breton, and Jean Salzemann. "A grid-enabled problem solving environment for in-silico screening in drug discovery." In 2010 5th International Conference on Computer Sciences and Convergence Information Technology (ICCIT 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccit.2010.5711070.

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6

Frolenko, V. S., V. I. Uvarova, A. A. Nikitina, E. V. Khvatov, M. Dodina, E. Bayurova, L. I. Kozlovskaya, and D. I. Osolodkin. "SCREENING OF TICK-BORNE ENCEPHALITIS VIRUS METHYLTRANSFERASE INHIBITORS IN VITRO AND IN SILICO." In MedChem-Russia 2021. 5-я Российская конференция по медицинской химии с международным участием «МедХим-Россия 2021». Издательство Волгоградского государственного медицинского университета, 2021. http://dx.doi.org/10.19163/medchemrussia2021-2021-323.

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7

Lida Zhu, Fengji Liang, Juan Liu, Simon Rayner, Yinghui Li, Shanguang Chen, and Jianghui Xiong. "Dynamic remodeling of context-specific miRNAs regulation networks facilitate in silico cancer drug screening." In 2011 IEEE International Conference on Systems Biology (ISB). IEEE, 2011. http://dx.doi.org/10.1109/isb.2011.6033168.

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8

de Jonge, Marc R., H. Maarten Vinkers, Joop H. van Lenthe, Frits Daeyaert, Ian J. Bush, Huub J. J. van Dam, Paul Sherwood, et al. "Ab Initio potential grid based docking: From High Performance Computing to In Silico Screening." In COMPLIFE 2007: The Third International Symposium on Computational Life Science. AIP, 2007. http://dx.doi.org/10.1063/1.2793399.

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9

Asaduzzaman, Md, Jahangir Alom, Mohammad Taufiq Alam, and Md Anwarul Karim. "In-silico Screening of Arjun Plant (Terminalia arjuna) Compounds Against Cardiovascular Disease Targeting GRK2 Protein." In 2021 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2). IEEE, 2021. http://dx.doi.org/10.1109/ic4me253898.2021.9768431.

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10

Omix Yu-Chian Chen. "Pharmacoinformatics approach to the discovery of novel selective COX-2 inhibitors by in silico virtual screening." In 2008 IEEE International Joint Conference on Neural Networks (IJCNN 2008 - Hong Kong). IEEE, 2008. http://dx.doi.org/10.1109/ijcnn.2008.4633958.

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Звіти організацій з теми "SILICO SCREENING"

1

Rafaeli, Ada, Russell Jurenka, and Chris Sander. Molecular characterisation of PBAN-receptors: a basis for the development and screening of antagonists against Pheromone biosynthesis in moth pest species. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7695862.bard.

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The original objectives of the approved proposal included: (a) The determination of species- and tissue-specificity of the PBAN-R; (b) the elucidation of the role of juvenile hormone in gene regulation of the PBAN-R; (c) the identificationof the ligand binding domains in the PBAN-R and (d) the development of efficient screening assays in order to screen potential antagonists that will block the PBAN-R. Background to the topic: Moths constitute one of the major groups of pest insects in agriculture and their reproductive behavior is dependent on chemical communication. Sex-pheromone blends are utilised by a variety of moth species to attract conspecific mates. In most of the moth species sex-pheromone biosynthesis is under circadian control by the neurohormone, PBAN (pheromone-biosynthesis-activating neuropeptide). In order to devise ideal strategies for mating disruption/prevention, we proposed to study the interactions between PBAN and its membrane-bound receptor in order to devise potential antagonists. Major conclusions: Within the framework of the planned objectives we have confirmed the similarities between the two Helicoverpa species: armigera and zea. Receptor sequences of the two Helicoverpa spp. are 98% identical with most changes taking place in the C-terminal. Our findings indicate that PBAN or PBAN-like receptors are also present in the neural tissues and may represent a neurotransmitter-like function for PBAN-like peptides. Surprisingly the gene encoding the PBAN-receptor was also present in the male homologous tissue, but it is absent at the protein level. The presence of the receptor (at the gene- and protein-levels), and the subsequent pheromonotropic activity are age-dependent and up-regulated by Juvenile Hormone in pharate females but down-regulated by Juvenile Hormone in adult females. Lower levels of pheromonotropic activity were observed when challenged with pyrokinin-like peptides than with HezPBAN as ligand. A model of the 3D structure of the receptor was created using the X-ray structure of rhodopsin as a template after sequence alignment of the HezPBAN-R with several other GPCRs and computer simulated docking with the model predicted putative binding sites. Using in silico mutagenesis the predicted docking model was validated with experimental data obtained from expressed chimera receptors in Sf9 cells created by exchanging between the three extracellular loops of the HezPBAN-R and the Drosophila Pyrokinin-R (CG9918). The chimera receptors also indicated that the 3ʳᵈ extracellular loop is important for recognition of PBAN or Diapause hormone ligands. Implications: The project has successfully completed all the objectives and we are now in a position to be able to design and screen potential antagonists for pheromone production. The successful docking simulation-experiments encourage the use of in silico experiments for initial (high-throughput) screening of potential antagonists. However, the differential responses between the expressed receptor (Sf9 cells) and the endogenous receptor (pheromone glands) emphasize the importance of assaying lead compounds using several alternative bioassays (at the cellular, tissue and organism levels). The surprising discovery of the presence of the gene encoding the PBAN-R in the male homologous tissue, but its absence at the protein level, launches opportunities for studying molecular regulation pathways and the evolution of these GPCRs. Overall this research will advance research towards the goal of finding antagonists for this important class of receptors that might encompass a variety of essential insect functions.

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2

Rafaeli, Ada, and Russell Jurenka. Molecular Characterization of PBAN G-protein Coupled Receptors in Moth Pest Species: Design of Antagonists. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7593390.bard.

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The proposed research was directed at determining the activation/binding domains and gene regulation of the PBAN-R’s thereby providing information for the design and screening of potential PBAN-R-blockers and to indicate possible ways of preventing the process from proceeding to its completion. Our specific aims included: (1) The identification of the PBAN-R binding domain by a combination of: (a) in silico modeling studies for identifying specific amino-acid side chains that are likely to be involved in binding PBAN with the receptor and; (b) bioassays to verify the modeling studies using mutant receptors, cell lines and pheromone glands (at tissue and organism levels) against selected, designed compounds to confirm if compounds are agonists or antagonists. (2) The elucidation ofthemolecular regulationmechanisms of PBAN-R by:(a) age-dependence of gene expression; (b) the effect of hormones and; (c) PBAN-R characterization in male hair-pencil complexes. Background to the topic Insects have several closely related G protein-coupled receptors (GPCRs) belonging to the pyrokinin/PBAN family, one with the ligand pheromone biosynthesis activating neuropeptide or pyrokinin-2 and another with diapause hormone or pyrokinin-1 as a ligand. We were unable to identify the diapause hormone receptor from Helicoverpa zea despite considerable effort. A third, related receptor is activated by a product of the capa gene, periviscerokinins. The pyrokinin/PBAN family of GPCRs and their ligands has been identified in various insects, such as Drosophila, several moth species, mosquitoes, Triboliumcastaneum, Apis mellifera, Nasoniavitripennis, and Acyrthosiphon pisum. Physiological functions of pyrokinin peptides include muscle contraction, whereas PBAN regulates pheromone production in moths plus other functions indicating the pleiotropic nature of these ligands. Based on the alignment of annotated genomic sequences, the primary and secondary structures of the pyrokinin/PBAN family of receptors have similarity with the corresponding structures of the capa or periviscerokinin receptors of insects and the neuromedin U receptors found in vertebrates. Major conclusions, solutions, achievements Evolutionary trace analysisof receptor extracellular domains exhibited several class-specific amino acid residues, which could indicate putative domains for activation of these receptors by ligand recognition and binding. Through site-directed point mutations, the 3rd extracellular domain of PBAN-R was shown to be critical for ligand selection. We identified three receptors that belong to the PBAN family of GPCRs and a partial sequence for the periviscerokinin receptor from the European corn borer, Ostrinianubilalis. Functional expression studies confirmed that only the C-variant of the PBAN-R is active. We identified a non-peptide agonist that will activate the PBAN-receptor from H. zea. We determined that there is transcriptional control of the PBAN-R in two moth species during the development of the pupa to adult, and we demonstrated that this transcriptional regulation is independent of juvenile hormone biosynthesis. This transcriptional control also occurs in male hair-pencil gland complexes of both moth species indicating a regulatory role for PBAN in males. Ultimate confirmation for PBAN's function in the male tissue was revealed through knockdown of the PBAN-R using RNAi-mediated gene-silencing. Implications, both scientific and agricultural The identification of a non-peptide agonist can be exploited in the future for the design of additional compounds that will activate the receptor and to elucidate the binding properties of this receptor. The increase in expression levels of the PBAN-R transcript was delineated to occur at a critical period of 5 hours post-eclosion and its regulation can now be studied. The mysterious role of PBAN in the males was elucidated by using a combination of physiological, biochemical and molecular genetics techniques.

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