Spin observables of the reactions NN -> DeltaN and pd -> Delta (pp)(1S0) in collinear kinematics

A general formalism for double and triple spin-correlations of the reaction NN -> DeltaN is developed for the case of collinear kinematics. A complete polarization experiment allowing to reconstruct all of the four amplitudes describing this process is suggested. Furthermore, the spin observables of the inelastic charge-exchange reaction pd -> Delta^0(pp)(1S0) are analyzed in collinear kinematics within the single pN scattering mechanism involving the subprocess pn -> Delta^0p. The full set of spin observables related to the polarization of one or two initial particles and one final particle is obtained in terms of three invariant amplitudes of the reaction pd -> Delta (pp)(1S0) and the transition form factor d->(pp)(1S0). A complete polarization experiment for the reaction pd -> Delta^0(pp)(1S0) is suggested which allows one to determine three independent combinations of the four amplitudes of the elementary subprocess NN -> DeltaN.Comment: 12 pages, 1 figur

Single-Molecule Imaging of an in Vitro-Evolved RNA Aptamer Reveals Homogeneous Ligand Binding Kinetics

Many studies of RNA folding and catalysis have revealed conformational heterogeneity, metastable folding intermediates, and long-lived states with distinct catalytic activities. We have developed a single-molecule imaging approach for investigating the functional heterogeneity of in vitro-evolved RNA aptamers. Monitoring the association of fluorescently labeled ligands with individual RNA aptamer molecules has allowed us to record binding events over the course of multiple days, thus providing sufficient statistics to quantitatively define the kinetic properties at the single-molecule level. The ligand binding kinetics of the highly optimized RNA aptamer studied here displays a remarkable degree of uniformity and lack of memory. Such homogeneous behavior is quite different from the heterogeneity seen in previous single-molecule studies of naturally derived RNA and protein enzymes. The single-molecule methods we describe may be of use in analyzing the distribution of functional molecules in heterogeneous evolving populations or even in unselected samples of random sequences

An updated analysis of NN elastic scattering data to 1.6 GeV

An energy-dependent and set of single-energy partial-wave analyses of $NN$ elastic scattering data have been completed. The fit to 1.6~GeV has been supplemented with a low-energy analysis to 400 MeV. Using the low-energy fit, we study the sensitivity of our analysis to the choice of $\pi NN$ coupling constant. We also comment on the possibility of fitting $np$ data alone. These results are compared with those found in the recent Nijmegen analyses. (Figures may be obtained from the authors upon request.)Comment: 17 pages of text, VPI-CAPS-7/

Experimental Facilities Development

This research was sponsored by the National Science Foundation Grant NSF PHy 87-1440

Molecular Dynamics and Quantum Mechanics of RNA: Conformational and Chemical Change We Can Believe In

Structure and dynamics are both critical to RNA’s vital functions in biology. Numerous techniques can elucidate the structural dynamics of RNA, but computational approaches based on experimental data arguably hold the promise of providing the most detail. In this Account, we highlight areas wherein molecular dynamics (MD) and quantum mechanical (QM) techniques are applied to RNA, particularly in relation to complementary experimental studies

Revision of AMBER Torsional Parameters for RNA Improves Free Energy Predictions for Tetramer Duplexes with GC and iGiC Base Pairs

All-atom force fields are important for predicting thermodynamic, structural, and dynamic properties of RNA. In this paper, results are reported for thermodynamic integration calculations of free energy differences of duplex formation when CG pairs in the RNA duplexes r(CCGG)2, r(GGCC)2, r(GCGC)2, and r(CGCG)2 are replaced by isocytidine–isoguanosine (iCiG) pairs. Agreement with experiment was improved when ε/ζ, α/γ, β, and χ torsional parameters in the AMBER99 force field were revised on the basis of quantum mechanical calculations. The revised force field, AMBER99TOR, brings free energy difference predictions to within 1.3, 1.4, 2.3, and 2.6 kcal/mol at 300 K, respectively, compared to experimental results for the thermodynamic cycles of CCGG → iCiCiGiG, GGCC → iGiGiCiC, GCGC → iGiCiGiC, and CGCG → iCiGiCiG. In contrast, unmodified AMBER99 predictions for GGCC → iGiGiCiC and GCGC → iGiCiGiC differ from experiment by 11.7 and 12.6 kcal/mol, respectively. In order to test the dynamic stability of the above duplexes with AMBER99TOR, four individual 50 ns molecular dynamics (MD) simulations in explicit solvent were run. All except r(CCGG)2 retained A-form conformation for ≥82% of the time. This is consistent with NMR spectra of r(iGiGiCiC)2, which reveal an A-form conformation. In MD simulations, r(CCGG)2 retained A-form conformation 52% of the time, suggesting that its terminal base pairs may fray. The results indicate that revised backbone parameters improve predictions of RNA properties and that comparisons to measured sequence dependent thermodynamics provide useful benchmarks for testing force fields and computational methods

Understanding the Origins of Bacterial Resistance to Aminoglycosides through Molecular Dynamics Mutational Study of the Ribosomal A-Site

Paromomycin is an aminoglycosidic antibiotic that targets the RNA of the bacterial small ribosomal subunit. It binds in the A-site, which is one of the three tRNA binding sites, and affects translational fidelity by stabilizing two adenines (A1492 and A1493) in the flipped-out state. Experiments have shown that various mutations in the A-site result in bacterial resistance to aminoglycosides. In this study, we performed multiple molecular dynamics simulations of the mutated A-site RNA fragment in explicit solvent to analyze changes in the physicochemical features of the A-site that were introduced by substitutions of specific bases. The simulations were conducted for free RNA and in complex with paromomycin. We found that the specific mutations affect the shape and dynamics of the binding cleft as well as significantly alter its electrostatic properties. The most pronounced changes were observed in the U1406C∶U1495A mutant, where important hydrogen bonds between the RNA and paromomycin were disrupted. The present study aims to clarify the underlying physicochemical mechanisms of bacterial resistance to aminoglycosides due to target mutations

Molecular modelling of the GIR1 branching ribozyme gives new insight into evolution of structurally related ribozymes

Twin-ribozyme introns contain a branching ribozyme (GIR1) followed by a homing endonuclease (HE) encoding sequence embedded in a peripheral domain of a group I splicing ribozyme (GIR2). GIR1 catalyses the formation of a lariat with 3 nt in the loop, which caps the HE mRNA. GIR1 is structurally related to group I ribozymes raising the question about how two closely related ribozymes can carry out very different reactions. Modelling of GIR1 based on new biochemical and mutational data shows an extended substrate domain containing a GoU pair distinct from the nucleophilic residue that dock onto a catalytic core showing a different topology from that of group I ribozymes. The differences include a core J8/7 region that has been reduced and is complemented by residues from the pre-lariat fold. These findings provide the basis for an evolutionary mechanism that accounts for the change from group I splicing ribozyme to the branching GIR1 architecture. Such an evolutionary mechanism can be applied to other large RNAs such as the ribonuclease P

Single Molecule Analysis Research Tool (SMART): An Integrated Approach for Analyzing Single Molecule Data

Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data