The roles of protonated nucleobases in stabilizing different structural motifs and in facilitating catalytic functions of RNA are well known. Among different polar sites of all the nucleobases, N7 of guanine has the highest protonation propensity at physiological pH. However, unlike other easily protonable sites such as N1 and N3 of adenine or N3 of cytosine, N7 protonation of guanine does not lead to the stabilization of base pairs involving its protonated Hoogsteen edge. It also does not facilitate its participation in any acid-base catalysis process. To explore the possible roles of N7 protonated guanine, we have studied its base pairing potentials involving WatsonCrick and sugar edges, which undergo major charge redistribution upon N7 protonation. We have carried out quantum chemical geometry optimization at the M05-2X/6-311G+(2d,2p) level, followed by interaction energy calculation at the MP2/aug-cc-pVDZ level, along with the analysis of the context of occurrence for selected base pairs involving the sugar edge or the WatsonCrick edge of guanine within a non-redundant set of 167 RNA crystal structures. Our results suggest that, four base pairs - G:C W:W trans, G:rC W:S cis, G:G W:H cis and G:G S:H trans may involve N7 protonated guanine. These base pairs deviate significantly from their respective experimental geometries upon QM optimization, but they retain their experimental geometries if guanine N7 protonation is considered during optimization. Our study also reveals the role of guanine N7 protonation (i) in stabilizing important RNA structural motifs, (ii) in providing a framework for designing pH driven molecular motors and (iii) in providing an alternative strategy to mimic the effect of post-transcriptional changes.

The astonishing diversity in folding patterns of RNA threedimensional (3D) structures is crafted by myriads of noncovalent contacts, of which base pairing and stacking are the most prominent. A systematic and comprehensive classification and annotation of these interactions is necessary for a molecular-level understanding of their roles. However, unlike in the case of base pairing, where a widely accepted nomenclature and classification scheme exists in the public domain, currently available classification schemes for base−base stacking need major enhancements to comprehensively capture the necessary features underlying the rich stacking diversity in RNA. Here, we extend the previous stacking classification based on nucleobase interacting faces by introducing a structurally intuitive geometry-cum topology-based scheme. Specifically, a stack is first classified in terms of the geometry described by the relative orientation of the glycosidic bonds, which generates eight basic stacking geometric families for heterodimeric stacks and six of those for homodimeric stacks. Further annotation in terms of the identity of the bases and the region of involvement of purines (five-membered, six-membered, or both rings) leads to the enumeration of 384 distinct RNA base stacks. Based on our classification scheme, we present an algorithm for automated identification of stacks in RNA crystal structures and analyze the stacking context in selected RNA structures. Overall, the work described here is expected to greatly facilitate the structure-based RNA research.

Protonated nucleobases have significant roles in facilitating catalytic functions of RNA, and in stabilizing different structural motifs. Reported pKa values of nucleobase protonation suggest that the population of neutral nucleobases is 10(3)-10(4) times higher than that of protonated nucleobases under physiological conditions (pH ∼ 7.4). Therefore, a molecular level understanding of various putative roles of protonated nucleobases cannot be achieved without addressing the question of how their occurrence propensities and stabilities are related to the free energy costs associated with the process of protonation under physiological conditions. With water as the proton donor, we use advanced QM methods to evaluate the site specific protonation propensities of nucleobases in terms of their associated free energy changes (ΔGprot). Quantitative follow up on the energetics of base pair formation and database search for evaluating their occurrence frequencies, reveal a lack of correlation between base pair stability and occurrence propensities on the one hand, and ease of protonation on the other. For example, although N7 protonated adenine (ΔGprot = 40.0 kcal mol(-1)) is found to participate in stable base pairing, base pairs involving N7 protonated guanine (ΔGprot = 36.8 kcal mol(-1)), on geometry optimization, converge to a minima where guanine transfers its extra proton to its partner base. Such observations, along with examples of weak base pairs involving N3 protonation of cytosine (ΔGprot = 37.0 kcal mol(-1)) are rationalized by analysing the protonation induced charge redistributions which are found to significantly influence, both positively and negatively, the hydrogen bonding potentials of different functional sites of individual nucleobases. Protonation induced charge redistribution is also found to strongly influence (i) the aromatic character of the rings of the participating bases and (ii) hydrogen bonding potential of the free edges of the protonated base pair. Comprehensive analysis of a non-redundant RNA crystal structure dataset further reveals that, while availability of stabilization possibilities determine the feasibility of occurrence of protonated bases, their occurrence context and specific functional roles are important factors determining their occurrence propensities.

Efficiency of 6-ethynylpyridone (E), a potential thymine (T) analogue, which forms high-fidelity base pairs with adenine (A) and gives rise to stabler DNA duplexes, with stability comparable to those containing canonical cytosine(C):guanine(G) base pairs, has been reported recently. Estimates of the interaction energies, involving geometry optimization at the DFT level (including middle range dispersion interactions) followed by single point energy calculation at MP2 level, in excellent correlation with the experimentally observed trends, show that E binds more strongly and more discriminately with A than T does. Detailed analysis reveals that the increase in base-base interaction arises out of conjugation of acetylenic π electrons with the ring π system of E, which results in not only an extra stabilizing C-H···π interaction in the EA pair, but also a strengthening of the conventional hydrogen bonds. However, the computed base-base interaction energy for the EA pair was found to be much less than that of the canonical CG pair, implying that the difference in the TA versus EA base pairing interaction alone cannot explain the large experimentally observed increase in the thermostability of DNA duplexes, where a TA pair is replaced with an EA pair. Our computations show that the conjugation of acetylenic π electrons with the ring π system also possibly plays a role in increasing the stacking potential of the EA pair, which in turn can explain its marked influence in the enhancement of duplex stability.

Structural bioinformatics of RNA has evolved mainly in response to the rapidly accumulating evidence that non-(protein)-coding RNAs (ncRNAs) play critical roles in gene regulation and development. The structures and functions of most ncRNAs are however still unknown. Most of the available RNA structural databases rely heavily on known 3D structures, and contextually correlate base pairing geometry with actual 3D RNA structures. None of the databases provide any direct information about stabilization energies. However, the intrinsic interaction energies of constituent base pairs can provide significant insights into their roles in the overall dynamics of RNA motifs and structures. Quantum mechanical (QM) computations provide the only approach toward their accurate quantification and characterization. ‘RNA Base Pair Count, Geometry and Stability’ (http://bioinf.iiit.ac.in/RNABPCOGEST) brings together information, extracted from literature data, regarding occurrence frequency, experimental and quantum chemically optimized geometries, and computed interaction energies, for non-canonical base pairs observed in a non-redundant dataset of functional RNA structures. The database is designed to enable the QM community, on the one hand, to identify appropriate biologically relevant model systems and also enable the biology community to easily sift through diverse computational results to gain theoretical insights which could promote hypothesis driven biological research.Database URL: http://bioinf.iiit.ac.in/RNABPCOGEST