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Items: 1 to 20 of 100

1.

An enumerative stepwise ansatz enables atomic-accuracy RNA loop modeling.

Sripakdeevong P, Kladwang W, Das R.

Proc Natl Acad Sci U S A. 2011 Dec 20;108(51):20573-8. doi: 10.1073/pnas.1106516108. Epub 2011 Dec 5.

2.

Atomic-accuracy prediction of protein loop structures through an RNA-inspired Ansatz.

Das R.

PLoS One. 2013 Oct 21;8(10):e74830. doi: 10.1371/journal.pone.0074830. eCollection 2013.

3.

Modeling Small Noncanonical RNA Motifs with the Rosetta FARFAR Server.

Yesselman JD, Das R.

Methods Mol Biol. 2016;1490:187-98. doi: 10.1007/978-1-4939-6433-8_12.

PMID:
27665600
4.

Blind prediction of noncanonical RNA structure at atomic accuracy.

Watkins AM, Geniesse C, Kladwang W, Zakrevsky P, Jaeger L, Das R.

Sci Adv. 2018 May 25;4(5):eaar5316. doi: 10.1126/sciadv.aar5316. eCollection 2018 May.

5.

Modeling complex RNA tertiary folds with Rosetta.

Cheng CY, Chou FC, Das R.

Methods Enzymol. 2015;553:35-64. doi: 10.1016/bs.mie.2014.10.051. Epub 2015 Feb 12.

PMID:
25726460
6.

Macromolecular modeling with rosetta.

Das R, Baker D.

Annu Rev Biochem. 2008;77:363-82. doi: 10.1146/annurev.biochem.77.062906.171838. Review.

PMID:
18410248
7.

A probabilistic model of RNA conformational space.

Frellsen J, Moltke I, Thiim M, Mardia KV, Ferkinghoff-Borg J, Hamelryck T.

PLoS Comput Biol. 2009 Jun;5(6):e1000406. doi: 10.1371/journal.pcbi.1000406. Epub 2009 Jun 19.

8.

Four small puzzles that Rosetta doesn't solve.

Das R.

PLoS One. 2011;6(5):e20044. doi: 10.1371/journal.pone.0020044. Epub 2011 May 20.

9.

Automated de novo prediction of native-like RNA tertiary structures.

Das R, Baker D.

Proc Natl Acad Sci U S A. 2007 Sep 11;104(37):14664-9. Epub 2007 Aug 28.

10.

Improved prediction of RNA tertiary structure with insights into native state dynamics.

Bida JP, Maher LJ 3rd.

RNA. 2012 Mar;18(3):385-93. doi: 10.1261/rna.027201.111. Epub 2012 Jan 25.

11.

Correcting pervasive errors in RNA crystallography through enumerative structure prediction.

Chou FC, Sripakdeevong P, Dibrov SM, Hermann T, Das R.

Nat Methods. 2013 Jan;10(1):74-6. doi: 10.1038/nmeth.2262. Epub 2012 Dec 2.

12.

MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology.

Feig M, Karanicolas J, Brooks CL 3rd.

J Mol Graph Model. 2004 May;22(5):377-95.

PMID:
15099834
13.

Atomic accuracy in predicting and designing noncanonical RNA structure.

Das R, Karanicolas J, Baker D.

Nat Methods. 2010 Apr;7(4):291-4. doi: 10.1038/nmeth.1433. Epub 2010 Feb 28.

14.

Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas.

Petrov AI, Zirbel CL, Leontis NB.

RNA. 2013 Oct;19(10):1327-40. doi: 10.1261/rna.039438.113. Epub 2013 Aug 22.

16.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

Boniecki MJ, Lach G, Dawson WK, Tomala K, Lukasz P, Soltysinski T, Rother KM, Bujnicki JM.

Nucleic Acids Res. 2016 Apr 20;44(7):e63. doi: 10.1093/nar/gkv1479. Epub 2015 Dec 19.

17.

Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics.

Trabuco LG, Villa E, Mitra K, Frank J, Schulten K.

Structure. 2008 May;16(5):673-83. doi: 10.1016/j.str.2008.03.005.

18.

Towards 3D structure prediction of large RNA molecules: an integer programming framework to insert local 3D motifs in RNA secondary structure.

Reinharz V, Major F, Waldispühl J.

Bioinformatics. 2012 Jun 15;28(12):i207-14. doi: 10.1093/bioinformatics/bts226.

19.
20.

All-atom Monte Carlo simulation of GCAA RNA folding.

Nivón LG, Shakhnovich EI.

J Mol Biol. 2004 Nov 12;344(1):29-45.

PMID:
15504400

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