dc.contributor.author | Niinivehmas, Sanna | |
dc.contributor.author | Manivannan, Elangovan | |
dc.contributor.author | Rauhamäki, Sanna | |
dc.contributor.author | Huuskonen, Juhani | |
dc.contributor.author | Pentikäinen, Olli | |
dc.date.accessioned | 2016-04-19T08:47:28Z | |
dc.date.available | 2016-04-19T08:47:28Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Niinivehmas, S., Manivannan, E., Rauhamäki, S., Huuskonen, J., & Pentikäinen, O. (2016). Identification of estrogen receptor α ligands with virtual screening techniques. <i>Journal of Molecular Graphics and Modelling</i>, <i>64</i>(March), 30-39. <a href="https://doi.org/10.1016/j.jmgm.2015.12.006" target="_blank">https://doi.org/10.1016/j.jmgm.2015.12.006</a> | |
dc.identifier.other | CONVID_25456390 | |
dc.identifier.other | TUTKAID_68683 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/49369 | |
dc.description.abstract | Utilization of computer-aided molecular discovery methods in virtual screening (VS) is a cost-effective approach to identify novel bioactive small molecules. Unfortunately, no universal VS strategy can guarantee high hit rates for all biological targets, but each target requires distinct, fine-tuned solutions. Here, we have studied in retrospective manner the effectiveness and usefulness of common pharmacophore hypothesis, molecular docking and negative image-based screening as potential VS tools for a widely applied drug discovery target, estrogen receptor α (ERα). The comparison of the methods helps to demonstrate the differences in their ability to identify active molecules. For example, structure-based methods identified an already known active ligand from the widely-used bechmarking decoy molecule set. Although prospective VS against one commercially available database with around 100,000 drug-like molecules did not retrieve many testworthy hits, one novel hit molecule with pIC50 value of 6.6, was identified. Furthermore, our small in-house compound collection of easy-to-synthesize molecules was virtually screened against ERα, yielding to five hit candidates, which were found to be active in vitro having pIC50 values from 5.5 to 6.5. | |
dc.language.iso | eng | |
dc.publisher | Elsevier Inc.; Molecular Graphics and Modelling Society | |
dc.relation.ispartofseries | Journal of Molecular Graphics and Modelling | |
dc.subject.other | estrogen receptor alpha | |
dc.subject.other | virtual screening | |
dc.subject.other | ligand discovery | |
dc.subject.other | pharmacophore modeling | |
dc.subject.other | 3D-QSAR | |
dc.subject.other | molecular docking | |
dc.subject.other | negative image | |
dc.title | Identification of estrogen receptor α ligands with virtual screening techniques | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-201604182229 | |
dc.contributor.laitos | Bio- ja ympäristötieteiden laitos | fi |
dc.contributor.laitos | Kemian laitos | fi |
dc.contributor.laitos | Department of Biological and Environmental Science | en |
dc.contributor.laitos | Department of Chemistry | en |
dc.contributor.oppiaine | Solu- ja molekyylibiologia | fi |
dc.contributor.oppiaine | Orgaaninen kemia | fi |
dc.contributor.oppiaine | Nanoscience Center | fi |
dc.contributor.oppiaine | Cell and Molecular Biology | en |
dc.contributor.oppiaine | Organic Chemistry | en |
dc.contributor.oppiaine | Nanoscience Center | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.date.updated | 2016-04-18T09:15:05Z | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 30-39 | |
dc.relation.issn | 1093-3263 | |
dc.relation.numberinseries | March | |
dc.relation.volume | 64 | |
dc.type.version | submittedVersion | |
dc.rights.copyright | © 2015 Elsevier Inc. This is a preprint version of an article whose final and definitive form has been published by Elsevier. | |
dc.rights.accesslevel | openAccess | fi |
dc.relation.doi | 10.1016/j.jmgm.2015.12.006 | |
dc.type.okm | A1 | |