Certification of Molecular Dynamics Trajectories with NMR Chemical Shifts

By Da-Wei Li, R. Brüschweiler. 2010

86 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/b5291bc3b1f282710d5ad9a6623555caea804f3c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. A. Bax
2. Yang Shen

In Molecular Biology

1. A. Bax
2. Yang Shen
3. Nikolaos G. Sgourakis
4. Santrupti Nerli
5. Woonghee Lee
6. John L. Markley
7. Andrew C. McShan
8. Gaetano T. Montelione

In Spectroscopy

1. Yang Shen
2. A. Bax
3. Nikolaos G. Sgourakis
4. Santrupti Nerli

Citations in the corpus

• SPARTA+: a modest improvement in empirical NMR chemical shift prediction by means of an artificial neural network (2010, background): “Conceivably, further improvements in this regard could be obtained by recording very extended (*1 ls) molecular dynamics trajectories, and averaging predicted chemical shifts over such a trajectory (Li and Brüschweiler 2010).”
• Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks (2013, methodology): “…empirical methods therefore tend to predict chemical shifts at somewhat higher accuracy than quantum chemical approaches, although the latter clearly benefit from using an ensemble representation of the protein structure (Vila et al. 2009) (Li and Brüschweiler 2010; Li and Bruschweiler 2012).”