Detail
Article
Online article
FT
Medvik - BMC
  • Something wrong with this record ?

Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study

A. Bochicchio, M. Krepl, F. Yang, G. Varani, J. Sponer, P. Carloni,

. 2018 ; 14 (12) : e1006642. [pub] 20181206

Language English Country United States

Document type Journal Article, Research Support, Non-U.S. Gov't

Persistent link   https://www.medvik.cz/link/bmc19012072

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations. Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.

References provided by Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc19012072
003      
CZ-PrNML
005      
20190416113637.0
007      
ta
008      
190405s2018 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1371/journal.pcbi.1006642 $2 doi
035    __
$a (PubMed)30521520
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Bochicchio, Anna $u Computational Biomedicine, Institute for Advanced Simulation IAS-5 and Institute of Neuroscience and Medicine INM-9, Forschungszentrum Jülich, Jülich, Germany.
245    10
$a Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study / $c A. Bochicchio, M. Krepl, F. Yang, G. Varani, J. Sponer, P. Carloni,
520    9_
$a The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations. Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.
650    _2
$a sekvence aminokyselin $7 D000595
650    _2
$a vazebná místa $x genetika $7 D001665
650    _2
$a výpočetní biologie $7 D019295
650    _2
$a lidé $7 D006801
650    _2
$a mikro RNA $x chemie $x genetika $x metabolismus $7 D035683
650    _2
$a molekulární modely $7 D008958
650    _2
$a simulace molekulární dynamiky $7 D056004
650    _2
$a nukleární magnetická rezonance biomolekulární $7 D019906
650    _2
$a konformace nukleové kyseliny $7 D009690
650    _2
$a vazba proteinů $7 D011485
650    _2
$a proteinové inženýrství $7 D015202
650    _2
$a RNA $x chemie $x metabolismus $7 D012313
650    12
$a motiv rozpoznávající RNA $x genetika $7 D000071377
650    _2
$a stabilita RNA $7 D020871
650    _2
$a proteiny vázající RNA $x chemie $x genetika $x metabolismus $7 D016601
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Krepl, Miroslav $u Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic.
700    1_
$a Yang, Fan $u Department of Chemistry, University of Washington, Seattle, Washington, United States of America.
700    1_
$a Varani, Gabriele $u Department of Chemistry, University of Washington, Seattle, Washington, United States of America.
700    1_
$a Sponer, Jiri $u Institute of Biophysics of the Czech Academy of Sciences, Brno, Czech Republic. Regional Centre of Advanced Technologies and Materials, Department of Physical Chemistry, Faculty of Science, Palacky University Olomouc, Olomouc, Czech Republic.
700    1_
$a Carloni, Paolo $u Computational Biomedicine, Institute for Advanced Simulation IAS-5 and Institute of Neuroscience and Medicine INM-9, Forschungszentrum Jülich, Jülich, Germany. JARA-HPC, Jülich Supercomputing Centre, Forschungszentrum Jülich GmbH, Jülich, Germany.
773    0_
$w MED00008919 $t PLoS computational biology $x 1553-7358 $g Roč. 14, č. 12 (2018), s. e1006642
856    41
$u https://pubmed.ncbi.nlm.nih.gov/30521520 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y a $z 0
990    __
$a 20190405 $b ABA008
991    __
$a 20190416113702 $b ABA008
999    __
$a ok $b bmc $g 1391382 $s 1050377
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2018 $b 14 $c 12 $d e1006642 $e 20181206 $i 1553-7358 $m PLoS computational biology $n PLoS Comput Biol $x MED00008919
LZP    __
$a Pubmed-20190405

Find record

Citation metrics

Archiving options