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Using a graph representation of RNA structures, we have studied the ensembles of secondary and tertiary graphs of two sets of RNA with Monte Carlo simulations. The first consisted of 91 target ribozyme and riboswitch sequences of moderate lengths (<150 nt) having a variety of secondary, H-type pseudoknots and kissing loop interactions. The second set consisted of 71 more diverse sequences across many RNA families. Using a simple empirical energy model for tertiary interactions and only sequence information for each target as input, the simulations examined how tertiary interactions impact the statistical mechanics of the fold ensembles. The results show that the graphs proliferate enormously when tertiary interactions are possible, producing an entropic driving force for the ensemble to access folds having tertiary structures even though they are overall energetically unfavorable in the energy model. For each of the targets in the two test sets, we assessed the quality of the model and the simulations by examining how well the simulated structures were able to predict the native fold, and compared the results to fold predictions from ViennaRNA. Our model generated good or excellent predictions in a large majority of the targets. Overall, this method was able to produce predictions of comparable quality to Vienna, but it outperformed Vienna for structures with H-type pseudoknots. The results suggest that while tertiary interactions are predicated on real-space contacts, their impacts on the folded structure of RNA can be captured by graph space information for sequences of moderate lengths, using a simple tertiary energy model for the loops, the base pairs, and base stacks. 

Performing full-resolution atomistic simulations of nucleic acid folding has remained a challenge for biomolecular modeling. Understanding how nucleic acids fold and how they transition between different folded structures as they unfold and refold has important implications for biology. This paper reports a theoretical model and computer simulation of the ab initio folding of DNA inverted repeat sequences. The formulation is based on an all-atom conformational model of the sugar-phosphate backbone via chain closure, and it incorporates three major molecular-level driving forces—base stacking, counterion-induced backbone self-interactions, and base pairing—via separate analytical theories designed to capture and reproduce the effects of the solvent without requiring explicit water and ions in the simulation. To accelerate computational throughput, a mixed numerical/analytical algorithm for the calculation of the backbone conformational volume is incorporated into the Monte Carlo simulation, and special stochastic sampling techniques were employed to achieve the computational efficiency needed to fold nucleic acids from scratch. This paper describes implementation details, benchmark results, and the advantages and technical challenges with this approach. 

Abstract Activation-induced deoxycytidine deaminase (AID) initiates somatic hypermutation (SHM) in immunoglobulin variable (IgV) genes to produce high-affinity antibodies. SHM requires IgV transcription by RNA polymerase II (Pol II). A eukaryotic transcription system including AID has not been reported previously. Here, we reconstitute AID-catalyzed deamination during Pol II transcription elongation in conjunction with DSIF transcription factor. C→T mutations occur at similar frequencies on non-transcribed strand (NTS) and transcribed strand (TS) DNA. In contrast, bacteriophage T7 Pol generates NTS mutations predominantly. AID-Pol II mutations are strongly favored in WRC and WGCW overlapping hot motifs (W = A or T, R = A or G) on both DNA strands. Single mutations occur on 70% of transcribed DNA clones. Mutations are correlated over a 15 nt distance in multiply mutated clones, suggesting that deaminations are catalyzed processively within a stalled or backtracked transcription bubble. Site-by-site comparisons for biochemical and human memory B-cell mutational spectra in an IGHV3-23*01 target show strongly favored deaminations occurring in the antigen-binding complementarity determining regions (CDR) compared to the framework regions (FW). By exhibiting consistency with B-cell SHM, our in vitro data suggest that biochemically defined reconstituted Pol II transcription systems can be used to investigate how, when and where AID is targeted.