guest ::
| Home > Publications database > Statistical mechanical models for cation selectivity in biological channels > print |
| Home > Publications database > Statistical mechanical models for cation selectivity in biological channels > print |
| 001 | 255840 | ||
| 005 | 20210129220543.0 | ||
| 037 | _ | _ | |a FZJ-2015-05951 |
| 100 | 1 | _ | |a Finnerty, Justin |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a CECAM Workshop: Computational approaches to chemical senses |c Jülich |d 2015-09-09 - 2015-09-11 |w Germany |
| 245 | _ | _ | |a Statistical mechanical models for cation selectivity in biological channels |
| 260 | _ | _ | |c 2015 |
| 336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1446101995_9941 |2 PUB:(DE-HGF) |x Invited |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a Other |2 DataCite |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 520 | _ | _ | |a Cation selective channels constitute the gate for ion currents through the cell membrane. These proteins select between the physiologically important Na+, K+ and Ca2+ cations. Here we present a statistical mechanical model based on atomistic structural information and without tuned parameters that reproduces the selectivity of bacterial Na+ and Ca2+ selective ion channels, the only such channels for which we have X-ray structures. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores. |
| 536 | _ | _ | |a 511 - Computational Science and Mathematical Methods (POF3-511) |0 G:(DE-HGF)POF3-511 |c POF3-511 |f POF III |x 0 |
| 536 | _ | _ | |a 574 - Theory, modelling and simulation (POF3-574) |0 G:(DE-HGF)POF3-574 |c POF3-574 |f POF III |x 1 |
| 536 | _ | _ | |a SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) |0 G:(DE-Juel1)HGF-SMHB-2013-2017 |c HGF-SMHB-2013-2017 |f SMHB |x 2 |
| 700 | 1 | _ | |a Peyser, Alexander |0 P:(DE-Juel1)161525 |b 1 |
| 700 | 1 | _ | |a Carloni, Paolo |0 P:(DE-Juel1)145614 |b 2 |
| 909 | C | O | |o oai:juser.fz-juelich.de:255840 |p VDB |
| 910 | 1 | _ | |a German Research School for Simulation Sciences |0 I:(DE-588b)1026307295 |k GRS Aachen |b 0 |6 P:(DE-HGF)0 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)161525 |
| 910 | 1 | _ | |a Forschungszentrum Jülich GmbH |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)145614 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-511 |2 G:(DE-HGF)POF3-500 |v Computational Science and Mathematical Methods |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-574 |2 G:(DE-HGF)POF3-500 |v Theory, modelling and simulation |x 1 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
| 914 | 1 | _ | |y 2015 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 920 | 1 | _ | |0 I:(DE-82)080012_20140620 |k JARA-HPC |l JARA - HPC |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-5-20120330 |k IAS-5 |l Computational Biomedicine |x 2 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-9-20140121 |k INM-9 |l Computational Biomedicine |x 3 |
| 980 | _ | _ | |a conf |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a I:(DE-82)080012_20140620 |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-5-20120330 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-9-20140121 |
| 980 | _ | _ | |a UNRESTRICTED |
| 981 | _ | _ | |a I:(DE-Juel1)IAS-5-20120330 |
| 981 | _ | _ | |a I:(DE-Juel1)INM-9-20140121 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|