Automatic Learning of Hydrogen-Bond Fixes in the AMBER RNA Force Field
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F22%3A73615834" target="_blank" >RIV/61989592:15310/22:73615834 - isvavai.cz</a>
Alternative codes found
RIV/61989592:15640/22:73615834
Result on the web
<a href="https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.2c00200" target="_blank" >https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.2c00200</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1021/acs.jctc.2c00200" target="_blank" >10.1021/acs.jctc.2c00200</a>
Alternative languages
Result language
angličtina
Original language name
Automatic Learning of Hydrogen-Bond Fixes in the AMBER RNA Force Field
Original language description
The capability of current force fields to reproduce RNA structural dynamics is limited. Several methods have been developed to take advantage of experimental data in order to enforce agreement with experiments. Here, we extend an existing framework which allows arbitrarily chosen force-field correction terms to be fitted by quantification of the discrepancy between observables back-calculated from simulation and corresponding experiments. We apply a robust regularization protocol to avoid overfitting and additionally introduce and compare a number of different regularization strategies, namely, L1, L2, Kish size, relative Kish size, and relative entropy penalties. The training set includes a GACC tetramer as well as more challenging systems, namely, gcGAGAgc and gcUUCGgc RNA tetraloops. Specific intramolecular hydrogen bonds in the AMBER RNA force field are corrected with automatically determined parameters that we call gHBfix(opt). A validation involving a separate simulation of a system present in the training set (gcUUCGgc) and new systems not seen during training (CAAU and UUUU tetramers) displays improvements regarding the native population of the tetraloop as well as good agreement with NMR experiments for tetramers when using the new parameters. Then, we simulate folded RNAs (a kink-turn and L1 stalk rRNA) including hydrogen bond types not sufficiently present in the training set. This allows a final modification of the parameter set which is named gHBfix21 and is suggested to be applicable to a wider range of RNA systems.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10403 - Physical chemistry
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Chemical Theory and Computation
ISSN
1549-9618
e-ISSN
1549-9626
Volume of the periodical
18
Issue of the periodical within the volume
7
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
4490-4502
UT code for WoS article
000819421300001
EID of the result in the Scopus database
2-s2.0-85133743636