English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Statistical evaluation of simulated NMR data of flexible molecules

Sternberg, U., & Farès, C. (2022). Statistical evaluation of simulated NMR data of flexible molecules. Physical Chemistry Chemical Physics, 24(16), 9608-9618. doi:10.1039/D2CP00330A.

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Sternberg, Ulrich1, 2, Author
Farès, Christophe3, Author           
Affiliations:
1Research Partner of Karlsruhe Institute of Technology (KIT) , Karlsruhe, Germany, ou_persistent22              
2COSMOS-Software, Jena, Germany , ou_persistent22              
3Service Department Farès (NMR), Max-Planck-Institut für Kohlenforschung, Max Planck Society, ou_1445623              

Content

show
hide
Free keywords: -
 Abstract: A new probability score—named χ-probability—is introduced for evaluating the fit of mixed NMR datasets to calculate molecular model ensembles, in order to answer challenging structural questions such as the determination of stereochemical configurations. Similar to the DP4 parameter, the χ-probability is based on Bayes theorem and expresses the probability that an experimental NMR dataset fits to a given individual within a finite set of candidate structures or configurations. Here, the χ-probability is applied to single out the correct configuration in four example cases, with increasing complexity and conformational mobility. The NMR data (which include RDCs, NOE distances and 3J couplings) are calculated from MDOC (Molecular Dynamics with Orientational Constraints) trajectories and are investigated against experimentally measured data. It is demonstrated that this approach singles out the correct stereochemical configuration with probabilities more than 98%, even for highly mobile molecules. In more demanding cases, a decisive χ-probability test requires that the datasets include high-quality NOE distances in addition to RDC values.

Details

show
hide
Language(s): eng - English
 Dates: 2022-01-202022-03-222022-04-112022-04-28
 Publication Status: Issued
 Pages: 11
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1039/D2CP00330A
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Physical Chemistry Chemical Physics
  Abbreviation : Phys. Chem. Chem. Phys.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Cambridge, England : Royal Society of Chemistry
Pages: - Volume / Issue: 24 (16) Sequence Number: - Start / End Page: 9608 - 9618 Identifier: ISSN: 1463-9076
CoNE: https://pure.mpg.de/cone/journals/resource/954925272413_1