Ligand binding and homology modelling of insect odorant-binding proteins
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| Publicado en: | Physiological Entomology vol. 39, no. 3 (Sep 2014), p. 183 |
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| 022 | |a 0307-6962 | ||
| 022 | |a 1365-3032 | ||
| 024 | 7 | |a 10.1111/phen.12066 |2 doi | |
| 035 | |a 1555020642 | ||
| 045 | 2 | |b d20140901 |b d20140930 | |
| 084 | |a 38642 |2 nlm | ||
| 100 | 1 | |a Venthur, Herbert | |
| 245 | 1 | |a Ligand binding and homology modelling of insect odorant-binding proteins | |
| 260 | |b Wiley Subscription Services, Inc. |c Sep 2014 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This review describes the main characteristics of odorant-binding proteins (OBPs) for homology modelling and presents a summary of structure prediction studies on insect OBPs, along with the steps involved and some limitations and improvements. The technique involves a computing approach to model protein structures and is based on a comparison between a target (unknown structure) and one or more templates (experimentally determined structures). As targets for structure prediction, OBPs are considered to play a functional role for recognition, desorption, scavenging, protection and transportation of hydrophobic molecules (odourants) across an aqueous environment (lymph) to olfactory receptor neurones (ORNs) located in sensilla, the main olfactory units of insect antennae. Lepidopteran pheromone-binding proteins, a subgroup of OBPs, are characterized by remarkable structural features, in which high sequence identities (approximately 30%) among these OBPs and a large number of available templates can facilitate the prediction of precise homology models. Approximately 30 studies have been performed on insect OBPs using homology modelling as a tool to predict their structures. Although some of the studies have assessed ligand-binding affinity using structural information and biochemical measurements, few have performed docking and molecular dynamic (MD) simulations as a virtual method to predict best ligands. Docking and MD simulations are discussed in the context of discovery of novel semiochemicals (super-ligands) using homology modelling to conceive further strategies in insect management. [PUBLICATION ABSTRACT] | |
| 653 | |a Insects | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Mutis, Ana | |
| 700 | 1 | |a Zhou, Jing-Jiang | |
| 700 | 1 | |a Quiroz, Andrés | |
| 773 | 0 | |t Physiological Entomology |g vol. 39, no. 3 (Sep 2014), p. 183 | |
| 786 | 0 | |d ProQuest |t Agriculture Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1555020642/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |