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

Bi-stability of the master gene regulatory network of the common dendritic precursor cell: Implications for cell differentiation

In cell lineage commitment decisions, a gene regulatory network (GRN) consisting of a limited number of transcription factors forms the regulatory pivot. Myeloid lineage dendritic cells or DCs are specialized cells having the antigen-presenting ability and are of immense importance in immune surveillance. In this report, we analyze the GRN that governs the lineage commitment of Common DC Progenitor (CDP) cells to conventional dendritic cells (cDC) and plasmacytoid dendritic cells (pDC). We have analyzed the quantitative behavior of the master regulatory circuit of CDP that governs the lineage commitment. Simulations showed that the GRN displays a bi-stable behavior within a range of parameter values. Several transcription factors, PU.1, IRF8, Flt3, and Stat3, whose concentrations vary significantly in the two steady states, appear to be the key players. We hypothesize that the two stable steady states are precursors of cDC and pDC, and the variation of concentration of these key transcription factors in the two states may be responsible for early events in lineage commitment.

Mechanical Identification of Materials and Structures with Optical Methods and Metaheuristic Optimization

This study presents a hybrid framework for mechanical identification of materials and structures. The inverse problem is solved by combining experimental measurements performed by optical methods and non-linear optimization using metaheuristic algorithms. In particular, we develop three advanced formulations of Simulated Annealing (SA), Harmony Search (HS) and Big Bang-Big Crunch (BBBC) including enhanced approximate line search and computationally cheap gradient evaluation strategies. The rationale behind the new algorithms-denoted as Hybrid Fast Simulated Annealing (HFSA), Hybrid Fast Harmony Search (HFHS) and Hybrid Fast Big Bang-Big Crunch (HFBBBC)-is to generate high quality trial designs lying on a properly selected set of descent directions. Besides hybridizing SA/HS/BBBC metaheuristic search engines with gradient information and approximate line search, HS and BBBC are also hybridized with an enhanced 1-D probabilistic search derived from SA. The results obtained in three inverse problems regarding composite and transversely isotropic hyperelastic materials/structures with up to 17 unknown properties clearly demonstrate the validity of the proposed approach, which allows to significantly reduce the number of structural analyses with respect to previous SA/HS/BBBC formulations and improves robustness of metaheuristic search engines.

Structural evidence for product stabilization by the ribosomal mRNA helicase

Protein synthesis in all organisms proceeds by stepwise translocation of the ribosome along messenger RNAs (mRNAs), during which the helicase activity of the ribosome unwinds encountered structures in the mRNA. This activity is known to occur near the mRNA tunnel entrance, which is lined by ribosomal proteins uS3, uS4, and uS5. However, the mechanism(s) of mRNA unwinding by the ribosome and the possible role of these proteins in the helicase activity are not well understood. Here, we present a crystal structure of the Escherichia coli ribosome in which single-stranded mRNA is observed beyond the tunnel entrance, interacting in an extended conformation with a positively charged patch on ribosomal protein uS3 immediately outside the entrance. This apparent binding specificity for single-stranded mRNA ahead of the tunnel entrance suggests that product stabilization may play a role in the unwinding of structured mRNA by the ribosomal helicase.

Using Molecular Simulation to Model High-Resolution Cryo-EM Reconstructions

An explosion of new data from high-resolution cryo-electron microscopy (cryo-EM) studies has produced a large number of data sets for many species of ribosomes in various functional states over the past few years. While many methods exist to produce structural models for lower resolution cryo-EM reconstructions, high-resolution reconstructions are often modeled using crystallographic techniques and extensive manual intervention. Here, we present an automated fitting technique for high-resolution cryo-EM data sets that produces all-atom models highly consistent with the EM density. Using a molecular dynamics approach, atomic positions are optimized with a potential that includes the cross-correlation coefficient between the structural model and the cryo-EM electron density, as well as a biasing potential preserving the stereochemistry and secondary structure of the biomolecule. Specifically, we use a hybrid structure-based/ab initio molecular dynamics potential to extend molecular dynamics fitting. In addition, we find that simulated annealing integration, as opposed to straightforward molecular dynamics integration, significantly improves performance. We obtain atomistic models of the human ribosome consistent with high-resolution cryo-EM reconstructions of the human ribosome. Automated methods such as these have the potential to produce atomistic models for a large number of ribosome complexes simultaneously that can be subsequently refined manually.

E pluribus unum, no more: from one crystal, many conformations

Several distinct computational approaches have recently been implemented to represent conformational heterogeneity from X-ray crystallography datasets that are averaged in time and space. As these modeling methods mature, newly discovered alternative conformations are being used to derive functional protein mechanisms. Room temperature X-ray data collection is emerging as a key variable for sampling functionally relevant conformations also observed in solution studies. Although concerns about radiation damage are warranted with higher temperature data collection, 'diffract and destroy' strategies on X-ray free electron lasers may permit radiation damage-free data collection. X-ray crystallography need not be confined to 'static unique snapshots'; these experimental and computational advances are revealing how the many conformations populated within a single crystal are used in biological mechanisms.

Modelling dynamics in protein crystal structures by ensemble refinement

Single-structure models derived from X-ray data do not adequately account for the inherent, functionally important dynamics of protein molecules. We generated ensembles of structures by time-averaged refinement, where local molecular vibrations were sampled by molecular-dynamics (MD) simulation whilst global disorder was partitioned into an underlying overall translation–libration–screw (TLS) model. Modeling of 20 protein datasets at 1.1–3.1 Å resolution reduced cross-validated R_free values by 0.3–4.9%, indicating that ensemble models fit the X-ray data better than single structures. The ensembles revealed that, while most proteins display a well-ordered core, some proteins exhibit a ‘molten core’ likely supporting functionally important dynamics in ligand binding, enzyme activity and protomer assembly. Order–disorder changes in HIV protease indicate a mechanism of entropy compensation for ordering the catalytic residues upon ligand binding by disordering specific core residues. Thus, ensemble refinement extracts dynamical details from the X-ray data that allow a more comprehensive understanding of structure–dynamics–function relationships.

DOI:http://dx.doi.org/10.7554/eLife.00311.001

It has been clear since the early days of structural biology in the late 1950s that proteins and other biomolecules are continually changing shape, and that these changes have an important influence on both the structure and function of the molecules. X-ray diffraction can provide detailed information about the structure of a protein, but only limited information about how its structure fluctuates over time. Detailed information about the dynamic behaviour of proteins is essential for a proper understanding of a variety of processes, including catalysis, ligand binding and protein–protein interactions, and could also prove useful in drug design.

Currently most of the X-ray crystal structures in the Protein Data Bank are ‘snap-shots’ with limited or no information about protein dynamics. However, X-ray diffraction patterns are affected by the dynamics of the protein, and also by distortions of the crystal lattice, so three-dimensional (3D) models of proteins ought to take these phenomena into account. Molecular-dynamics (MD) computer simulations transform 3D structures into 4D ‘molecular movies’ by predicting the movement of individual atoms.

Combining MD simulations with crystallographic data has the potential to produce more realistic ensemble models of proteins in which the atomic fluctuations are represented by multiple structures within the ensemble. Moreover, in addition to improved structural information, this process—which is called ensemble refinement—can provide dynamical information about the protein. Earlier attempts to do this ran into problems because the number of model parameters needed was greater than the number of observed data points. Burnley et al. now overcome this problem by modelling local molecular vibrations with MD simulations and, at the same time, using a course-grain model to describe global disorder of longer length scales.

Ensemble refinement of high-resolution X-ray diffraction datasets for 20 different proteins from the Protein Data Bank produced a better fit to the data than single structures for all 20 proteins. Ensemble refinement also revealed that 3 of the 20 proteins had a ‘molten core’, rather than the well-ordered residues core found in most proteins: this is likely to be important in various biological functions including ligand binding, filament formation and enzymatic function. Burnley et al. also showed that a HIV enzyme underwent an order–disorder transition that is likely to influence how this enzyme works, and that similar transitions might influence the interactions between the small-molecule drug Imatinib (also known as Gleevec) and the enzymes it targets. Ensemble refinement could be applied to the majority of crystallography data currently being collected, or collected in the past, so further insights into the properties and interactions of a variety of proteins and other biomolecules can be expected.

DOI:http://dx.doi.org/10.7554/eLife.00311.002

Determining the DNA stability parameters for the breathing dynamics of heterogeneous DNA by stochastic optimization

We suggest that the thermodynamic stability parameters (nearest neighbor stacking and hydrogen bonding free energies) of double-stranded DNA molecules can be inferred reliably from time series of the size fluctuations (breathing) of local denaturation zones (bubbles). On the basis of the reconstructed bubble size distribution, this is achieved through stochastic optimization of the free energies in terms of simulated annealing. In particular, it is shown that even noisy time series allow the identification of the stability parameters at remarkable accuracy. This method will be useful to obtain the DNA stacking and hydrogen bonding free energies from single bubble breathing assays rather than equilibrium data.

The roles of RNA in the synthesis of protein

The crystal structures of ribosomes that have been obtained since 2000 have transformed our understanding of protein synthesis. In addition to proving that RNA is responsible for catalyzing peptide bond formation, these structures have provided important insights into the mechanistic details of how the ribosome functions. This review emphasizes what has been learned about the mechanism of peptide bond formation, the antibiotics that inhibit ribosome function, and the fidelity of decoding.