Multistart simulated annealing refinement of the crystal structure of the 70S ribosome

Abstract

A macromolecular X-ray crystal structure is usually represented as a single static model with a single set of temperature factors representing a simple approximation of motion and disorder of the structure. Multiconformer representations of small proteins have been shown to better describe anisotropic motion and disorder and improve the quality of their electron density maps. Here, we apply multistart simulated annealing crystallographic refinement to a 70S ribosome-RF1 translation termination complex that was recently solved at 3.2 Å resolution. The analysis improves the interpretability of the electron density map of this 2.5-MDa ribonucleoprotein complex and provides insights into its structural dynamics. We also used multistart refinement and conventional Fourier difference maps to address a recent study in which cross-crystal averaging between two crystal forms of the 70S ribosome was used to evaluate reported differences between two ribosome crystal structures solved at 2.8 and 3.7 Å resolution. Our analysis suggests that results obtained from cross-crystal averaging are inherently biased toward the higherresolution dataset.multistart refinement ͉ protein synthesis ͉ ribosome dynamics ͉ rRNA C rystallographic techniques and methods of structure determination have progressed rapidly in recent years, accompanied by an explosion in the amount of structural information about biological molecules and macromolecular assemblies. X-ray crystal structures have traditionally been represented by a single set of atomic coordinates accompanied by a set of temperature factors (B factors) to characterize atomic thermal motion. At most experimentally attainable resolutions, a spherical approximation for thermal motion is used, accounting only for the isotropic component of atomic displacement. It has been shown that the use of a static model with isotropic thermal parameters underestimates the total disorder and conformational variability of macromolecules (1-5). The limitation of the single-model approach is exemplified by several cases where high-resolution data are available. Nearly half the amino acid side chains and even some backbone atoms were found to have alternative conformations in the 0.54 Å structure of crambin and in the 1.0 Å structure of calmodulin (1, 6). To account for anharmonic contributions and conformational variability in X-ray structures, the use of an ensemble of models, as has long been standard practice in structure determination by NMR, has been suggested as a replacement for the traditional single-model approach (7). Multiconformer refinement has been implemented using both real-and reciprocal-space refinement approaches (2,3,(8)(9)(10)(11)(12)(13) and was demonstrated to yield improved agreement with diffraction data in most cases. In the case of molecular replacement phasing, electron density maps are often biased toward the search model; when a structure ensemble is used, however, model bias can be reduced significantly (14).In X-ray structures of the ribosome, the largest asymmetric struct...

Modelling dynamics in protein crystal structures by ensemble refinement

“…However, explicit modelling of such distributions in macromolecules using current methods requires extensive parameterization inappropriate for the diffraction quality of a typical protein crystal. Multi-conformer structures represent both anisotropic and anharmonic disorder, but despite numerous attempts at automating the inclusion of minor conformations (DePristo et al, 2004; Levin et al, 2007; Terwilliger et al, 2007; Korostelev et al, 2009; van den Bedem et al, 2009; Lang et al, 2010), 95% of all protein residues in the Protein Data Bank (PDB) (Berman et al, 2000) derived from diffraction data are modelled with a single conformation (Lang et al, 2010). As opposed to multiple discrete models, a MD simulation with time-averaged restraints (Gros et al, 1990) results in a population of structures in which the individual models are interrelated by a Boltzmann-weighted energy function.…”

Searching for optimal alphabet for data compression using simulated annealing

“…The SA becomes very popular because it is able to solve this problem in very efficient way. But its application cover much larger problem space such as job scheduling [23], optimization of statistical functions [24], automatic docking substrate to macromolecules of known structure [25], restoring ab initio low resolution shape and internal structure of chaotically oriented particles [26], refinement of the crystal structure of the 70S ribosome [27] and many others.…”

2011: 50 Jahre Entdeckung des genetischen Codes

“…[20] In der Tat dauerte es zwanzig Jahre, bis die Struktur des Ribosoms durch die Gruppen von A. Yonath, [39] T. Steitz, [40] V. Ramakrishnan [41] und H. Noller aufgeklärt werden konnte. [42] Die hochaufgelçsten Strukturen liefern eine Fülle wertvoller Informationen, nicht nur bezüglich der Struktur, sondern auch der Funktion von Ribosomen. So ist es inzwischen mçglich, die verschiedenen tRNAs an den ribosomalen A-, P-und E-Bindungsstellen, die von K. Nierhaus und Mitarbeitern entdeckt wurden, [43] zu lokalisieren und ihre Interaktion mit den Codons der mRNAs zu verfolgen.…”