dc.contributor.author | Groenhof, Gerrit | |
dc.contributor.author | Modi, Vaibhav | |
dc.contributor.author | Morozov, Dmitry | |
dc.date.accessioned | 2020-04-30T08:02:43Z | |
dc.date.available | 2020-04-30T08:02:43Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Groenhof, G., Modi, V., & Morozov, D. (2020). Observe while it happens : catching photoactive proteins in the act with non-adiabatic molecular dynamics simulations. <i>Current Opinion in Structural Biology</i>, <i>61</i>, 106-112. <a href="https://doi.org/10.1016/j.sbi.2019.12.013" target="_blank">https://doi.org/10.1016/j.sbi.2019.12.013</a> | |
dc.identifier.other | CONVID_34071802 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/68788 | |
dc.description.abstract | Organisms use photo-receptors to react to light. The first step is usually the absorption of a photon by a prosthetic group embedded inside the photo-receptor, often a conjugated chromophore. The electronic changes in the chromophore induced by photo-absorption can trigger a cascade of structural or chemical transformations that culminate into a response to light. Understanding how these proteins have evolved to mediate their activation process has remained challenging because the required time and spacial resolutions are notoriously difficult to achieve experimentally. Therefore, mechanistic insights into photoreceptor activation have been predominantly obtained with computer simulations. Here we briefly outline the challenges associated with such computations and review the progress made in this field. | en |
dc.format.mimetype | application/pdf | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | Elsevier Ltd. | |
dc.relation.ispartofseries | Current Opinion in Structural Biology | |
dc.rights | CC BY-NC-ND 4.0 | |
dc.subject.other | photoactive proteins | |
dc.subject.other | molecular biology | |
dc.title | Observe while it happens : catching photoactive proteins in the act with non-adiabatic molecular dynamics simulations | |
dc.type | research article | |
dc.identifier.urn | URN:NBN:fi:jyu-202004302995 | |
dc.contributor.laitos | Kemian laitos | fi |
dc.contributor.laitos | Department of Chemistry | en |
dc.contributor.oppiaine | Fysikaalinen kemia | fi |
dc.contributor.oppiaine | Physical Chemistry | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 106-112 | |
dc.relation.issn | 0959-440X | |
dc.relation.volume | 61 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © 2020 The Authors. Published by Elsevier Ltd. | |
dc.rights.accesslevel | openAccess | fi |
dc.type.publication | article | |
dc.subject.yso | proteiinit | |
dc.subject.yso | molekyylibiologia | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p4332 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p7549 | |
dc.rights.url | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.relation.doi | 10.1016/j.sbi.2019.12.013 | |
jyx.fundinginformation | This work has been done as part of the BioExcel CoE (www.bioexcel.eu), a project funded by the European Union contracts H2020-INFRAEDI-02-2018-823830, H2020-EINFRA-2015-1-675728. | |
dc.type.okm | A1 | |