Schmidt, Michael ; Schroeder, Indra ; Bauer, Daniel ; Thiel, Gerhard ; Hamacher, Kay (2024)
Inferring functional units in ion channel pores via relative entropy.
In: European Biophysics Journal, 2021, 50 (1)
doi: 10.26083/tuprints-00023470
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Inferring functional units in ion channel pores via relative entropy |
Language: | English |
Date: | 3 September 2024 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2021 |
Place of primary publication: | Berlin ; Heidelberg ; New York |
Publisher: | Springer International Publishing |
Journal or Publication Title: | European Biophysics Journal |
Volume of the journal: | 50 |
Issue Number: | 1 |
DOI: | 10.26083/tuprints-00023470 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
Abstract: | Coarse-grained protein models approximate the first-principle physical potentials. Among those modeling approaches, the relative entropy framework yields promising and physically sound results, in which a mapping from the target protein structure and dynamics to a model is defined and subsequently adjusted by an entropy minimization of the model parameters. Minimization of the relative entropy is equivalent to maximization of the likelihood of reproduction of (configurational ensemble) observations by the model. In this study, we extend the relative entropy minimization procedure beyond parameter fitting by a second optimization level, which identifies the optimal mapping to a (dimension-reduced) topology. We consider anisotropic network models of a diverse set of ion channels and assess our findings by comparison to experimental results. |
Uncontrolled Keywords: | Potassium channel (pores), Mechanical coupling relative entropy, Anisotropic network model |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-234702 |
Classification DDC: | 500 Science and mathematics > 530 Physics 500 Science and mathematics > 570 Life sciences, biology |
Divisions: | 10 Department of Biology > Biology of Algae and Protozoa 10 Department of Biology > Computational Biology and Simulation |
Date Deposited: | 03 Sep 2024 13:51 |
Last Modified: | 02 Oct 2024 14:01 |
SWORD Depositor: | Deep Green |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23470 |
PPN: | 521851521 |
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