Methods Used to Determine RNA Conformational Classes

Bohdan Schneider Institute of Organic Chemistry and Biochemistry Academy of Sciences of the Czech Republic,

Prague, Czech Republic bohdan@uochb.cas.cz

David Micallef John Westbrook Helen M. Berman

Department of Chemistry and Biological Chemistry, Rutgers University, Piscataway, NJ, USA

in collaboration with

Laura Murray and Jane RichardsonDuke University, Durham NC, USA

Supported by the NSF grant DBI 0110076 to the NDB and grant LC512 from Ministry of Education of the Czech Republic

Unit of Analysis

Nucleotide-like Largest variability at the

phosphodiester link A unit for analysis

dinucleotide “suite” (ribose-to-ribose) (Pi – Pi+1 – Pi+2 )

Challenge dimensionality

• nucleotide has 7 torsions noise of experimental data

Datasets

Original analysis done on crystal structure of 50S rRNAs: Ban et al., Science, 905 (2000), PDB

code 1JJ2• analyzed ~2700 dinucleotides

Repeated using filtered data supplied by the Richardson group

• ~4000 “suites” from ~100 crystal structures

1D, 2D, 3D Distributions

Simple analysis in 1D and 2D indicates possible clustering, directs further analysis

A few torsions bear most variability

Histograms – hints for clustering

Scattergrams

Highest variability at phosphodiester link i–i+1

Other important distributions:

ii ii

Analysis of 3D torsion distributions

Combine key 2D distributions, as i–i+1 or

ii, with other torsions: i, i+1, i+1, i, i, i+1,

i

In the current analysis: used ~4,000 filtered “suites” calculated 17 3D maps

• in all 17, fitted peaks, assigned fragments to peaks

Analysis of 3D distributions by Fourier averaging

Point distribution Fourier average

map i-i+1-i

A-RNA

Clustering

Peaks in 3D maps fitted Nearby data points labeled in all

analyzed maps Fragments clustered by alphabetical

sorting 6 primary maps for clustering 5 to monitor quality of proposed clusters 6 more or less ignored in the analysis

Torsional Space Real Space

To check if clusters represent typical conformations: Cartesian coordinates were determined for

all clusters using standard valence geometry

Members of a cluster were overlapped over the average resulting rmsd values were analyzed,

outliers excluded

Result is a conformational family

Results

Ribosome: 32 clusters of dinucleotides Filtered data: 38 clusters of “suites” For the atoms common to both

fragments, “Ribosome” and “Filtered” clusters overlap well

• more clusters were discovered with the filtered data

Both FT analyses monitored during clustering

Protocol

Selection of fragments for analysis• 23S and 5S rRNA from 1JJ2• filtered “suite” fragments from ~100 crystals

Put torsion angles into data matrix Fourier-average 3D distributions of torsions Localize and name peaks in all maps Name data points by nearby peaks Cluster fragments by their names Check clusters by overlap in real 3D Well overlapping fragments within a cluster

form conformational family

A-RNA low rise

open, stretchedA-like, intercalation Z-like

U-/S-shape