02370nas a2200445 4500008004100000022001400041245009000055210006900145260001200214300001100226490000800237520103400245653002801279653002201307653002101329653003001350653002701380653001401407653001501421653004501436653002201481653003301503653003301536653002301569653001401592653001801606653002401624100002101648700002101669700002501690700002001715700001701735700002201752700002501774700001701799700002101816700002001837700001901857856004801876 2009 eng d a1091-649000aRibosome-induced changes in elongation factor Tu conformation control GTP hydrolysis.0 aRibosomeinduced changes in elongation factor Tu conformation con c01/2009 a1063-80 v1063 a
In translation, elongation factor Tu (EF-Tu) molecules deliver aminoacyl-tRNAs to the mRNA-programmed ribosome. The GTPase activity of EF-Tu is triggered by ribosome-induced conformational changes of the factor that play a pivotal role in the selection of the cognate aminoacyl-tRNAs. We present a 6.7-A cryo-electron microscopy map of the aminoacyl-tRNA x EF-Tu x GDP x kirromycin-bound Escherichia coli ribosome, together with an atomic model of the complex obtained through molecular dynamics flexible fitting. The model reveals the conformational changes in the conserved GTPase switch regions of EF-Tu that trigger hydrolysis of GTP, along with key interactions, including those between the sarcin-ricin loop and the P loop of EF-Tu, and between the effector loop of EF-Tu and a conserved region of the 16S rRNA. Our data suggest that GTP hydrolysis on EF-Tu is controlled through a hydrophobic gate mechanism.
10aCryoelectron Microscopy10aEnzyme Activation10aEscherichia coli10aEscherichia coli Proteins10aGuanosine Triphosphate10aHistidine10aHydrolysis10aHydrophobic and Hydrophilic Interactions10aModels, Molecular10aPeptide Elongation Factor Tu10aProtein Structure, Secondary10aRibosomal Proteins10aRibosomes10aRNA, Transfer10aSignal Transduction1 aVilla, Elizabeth1 aSengupta, Jayati1 aTrabuco, Leonardo, G1 aLeBarron, Jamie1 aBaxter, Bill1 aShaikh, Tanvir, R1 aGrassucci, Robert, A1 aNissen, Poul1 aEhrenberg, Måns1 aSchulten, Klaus1 aFrank, Joachim uhttp://www.ncbi.nlm.nih.gov/pubmed/1912215001752nas a2200265 4500008004100000022001400041245010100055210006900156260001200225300001000237490000800247520093400255653002801189653002101217653002201238653004001260653001401300100002001314700002501334700002201359700001701381700002101398700001901419856004801438 2008 eng d a1095-865700aExploration of parameters in cryo-EM leading to an improved density map of the E. coli ribosome.0 aExploration of parameters in cryoEM leading to an improved densi c10/2008 a24-320 v1643 aA number of image processing parameters in the 3D reconstruction of a ribosome complex from a cryo-EM data set were varied to test their effects on the final resolution. The parameters examined were pixel size, window size, and mode of Fourier amplitude enhancement at high spatial frequencies. In addition, the strategy of switching from large to small pixel size during angular refinement was explored. The relationship between resolution (in Fourier space) and the number of particles was observed to follow a lin-log dependence, a relationship that appears to hold for other data, as well. By optimizing the above parameters, and using a lin-log extrapolation to the full data set in the estimation of resolution from half-sets, we obtained a 3D map from 131,599 ribosome particles at 6.7A resolution (FSC=0.5).
10aCryoelectron Microscopy10aEscherichia coli10aImage Enhancement10aImage Processing, Computer-Assisted10aRibosomes1 aLeBarron, Jamie1 aGrassucci, Robert, A1 aShaikh, Tanvir, R1 aBaxter, Bill1 aSengupta, Jayati1 aFrank, Joachim uhttp://www.ncbi.nlm.nih.gov/pubmed/1860654902306nas a2200289 4500008004100000022001400041245013100055210006900186260001200255300000900267490000800276520139700284653001501681653002801696653001901724653002201743653004001765653002501805653002601830653001401856100002201870700002001892700002001912700001701932700001901949856004801968 2008 eng d a1095-865700aParticle-verification for single-particle, reference-based reconstruction using multivariate data analysis and classification.0 aParticleverification for singleparticle referencebased reconstru c10/2008 a41-80 v1643 aAs collection of electron microscopy data for single-particle reconstruction becomes more efficient, due to electronic image capture, one of the principal limiting steps in a reconstruction remains particle-verification, which is especially costly in terms of user input. Recently, some algorithms have been developed to window particles automatically, but the resulting particle sets typically need to be verified manually. Here we describe a procedure to speed up verification of windowed particles using multivariate data analysis and classification. In this procedure, the particle set is subjected to multi-reference alignment before the verification. The aligned particles are first binned according to orientation and are binned further by K-means classification. Rather than selection of particles individually, an entire class of particles can be selected, with an option to remove outliers. Since particles in the same class present the same view, distinction between good and bad images becomes more straightforward. We have also developed a graphical interface, written in Python/Tkinter, to facilitate this implementation of particle-verification. For the demonstration of the particle-verification scheme presented here, electron micrographs of ribosomes are used.
10aAlgorithms10aArtificial Intelligence10aClassification10aImage Enhancement10aImage Processing, Computer-Assisted10aMicroscopy, Electron10aMultivariate Analysis10aRibosomes1 aShaikh, Tanvir, R1 aTrujillo, Ramon1 aLeBarron, Jamie1 aBaxter, Bill1 aFrank, Joachim uhttp://www.ncbi.nlm.nih.gov/pubmed/18619547