Rotavirus RNA chaperone mediates global transcriptome-wide increase in RNA backbone flexibility

Due to genome segmentation, rotaviruses must co-package a set of eleven distinct genomic RNAs. The packaging is mediated by virus-encoded RNA chaperones, such as the rotavirus (RV) NSP2 protein. While the activities of distinct viral RNA chaperones are well studied on synthetic RNA substrates, little is known about their global effect on the entire viral transcriptome. Here we used Selective 2′-hydroxyl Acylation Analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP) to systematically examine the secondary structure of the RV transcriptome composed of eleven distinct transcripts in the absence and presence of increasing concentrations of RV NSP2. Surprisingly, SHAPE-MaP data reveals that despite the well-documented helix-unwinding activity of NSP2 in vitro, its incubation with cognate RV transcripts does not induce a significant change in the SHAPE reactivities. However, a quantitative analysis of the per nucleotide mutation rate measured by mutational profiling, from which SHAPE reactivities are derived, reveals a global five-fold rate increase in the presence of molar excess of NSP2. We demonstrate that the standard normalization procedure used in deriving SHAPE reactivities from mutation rates can mask an important global effect of an RNA chaperone activity. Further analysis of the mutation rate in the context of structural classification reveals a larger effect on stems rather than loop elements. Together, these data provide the first experimentally derived secondary structure model of the RV transcriptome and reveal that NSP2 acts by globally increasing RNA backbone flexibility in a concentration-dependent manner, consistent with its promiscuous RNA-binding nature.

Protein-protein docking with large-scale backbone flexibility

Structure prediction of protein-protein complexes is one of the most critical challenges in computational structural biology. It is often difficult to predict the complex structure, even for relatively rigid proteins. Modeling significant structural flexibility in protein docking remains an unsolved problem. This work demonstrates a protein-protein docking protocol with enhanced sampling that accounts for large-scale backbone flexibility. The docking protocol starts from unbound x-ray structures and is not using any binding site information. In docking, one protein partner undergoes multiple fold rearrangements, rotations, and translations during docking simulations, while the other protein exhibits small backbone fluctuations. Including significant backbone flexibility during the search for the binding site has been made possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics. In our simulations, we obtained acceptable quality models for the set of 12 protein-protein complexes, while for selected cases, models were close to high accuracy.

Combined Effects of Methylated Cytosine and Molecular Crowding on the Thermodynamic Stability of DNA Duplexes

Methylated cytosine within CpG dinucleotides is a key factor for epigenetic gene regulation. It has been revealed that methylated cytosine decreases DNA backbone flexibility and increases the thermal stability of DNA. Although the molecular environment is an important factor for the structure, thermodynamics, and function of biomolecules, there are few reports on the effects of methylated cytosine under a cell-mimicking molecular environment. Here, we systematically investigated the effects of methylated cytosine on the thermodynamics of DNA duplexes under molecular crowding conditions, which is a critical difference between the molecular environment in cells and test tubes. Thermodynamic parameters quantitatively demonstrated that the methylation effect and molecular crowding effect on DNA duplexes are independent and additive, in which the degree of the stabilization is the sum of the methylation effect and molecular crowding effect. Furthermore, the effects of methylation and molecular crowding correlate with the hydration states of DNA duplexes. The stabilization effect of methylation was due to the favorable enthalpic contribution, suggesting that direct interactions of the methyl group with adjacent bases and adjacent methyl groups play a role in determining the flexibility and thermodynamics of DNA duplexes. These results are useful to predict the properties of DNA duplexes with methylation in cell-mimicking conditions.

Constructing 3-Dimensional Atomic-Resolution Models of Nonsulfated Glycosaminoglycans with Arbitrary Lengths Using Conformations from Molecular Dynamics

Glycosaminoglycans (GAGs) are the linear carbohydrate components of proteoglycans (PGs) and are key mediators in the bioactivity of PGs in animal tissue. GAGs are heterogeneous, conformationally complex, and polydisperse, containing up to 200 monosaccharide units. These complexities make studying GAG conformation a challenge for existing experimental and computational methods. We previously described an algorithm we developed that applies conformational parameters (i.e., all bond lengths, bond angles, and dihedral angles) from molecular dynamics (MD) simulations of nonsulfated chondroitin GAG 20-mers to construct 3-D atomic-resolution models of nonsulfated chondroitin GAGs of arbitrary length. In the current study, we applied our algorithm to other GAGs, including hyaluronan and nonsulfated forms of dermatan, keratan, and heparan and expanded our database of MD-generated GAG conformations. Here, we show that individual glycosidic linkages and monosaccharide rings in 10- and 20-mers of hyaluronan and nonsulfated dermatan, keratan, and heparan behave randomly and independently in MD simulation and, therefore, using a database of MD-generated 20-mer conformations, that our algorithm can construct conformational ensembles of 10- and 20-mers of various GAG types that accurately represent the backbone flexibility seen in MD simulations. Furthermore, our algorithm efficiently constructs conformational ensembles of GAG 200-mers that we would reasonably expect from MD simulations.

Efficient Construction of Atomic-Resolution Models of Non-Sulfated Chondroitin Glycosaminoglycan Using Molecular Dynamics Data

Glycosaminoglycans (GAGs) are linear, structurally diverse, conformationally complex carbohydrate polymers that may contain up to 200 monosaccharides. These characteristics present a challenge for studying GAG conformational thermodynamics at atomic resolution using existing experimental methods. Molecular dynamics (MD) simulations can overcome this challenge but are only feasible for short GAG polymers. To address this problem, we developed an algorithm that applies all conformational parameters contributing to GAG backbone flexibility (i.e., bond lengths, bond angles, and dihedral angles) from unbiased all-atom explicit-solvent MD simulations of short GAG polymers to rapidly construct models of GAGs of arbitrary length. The algorithm was used to generate non-sulfated chondroitin 10- and 20-mer ensembles which were compared to MD-generated ensembles for internal validation. End-to-end distance distributions in constructed and MD-generated ensembles have minimal differences, suggesting that our algorithm produces conformational ensembles that mimic the backbone flexibility seen in simulation. Non-sulfated chondroitin 100- and 200-mer ensembles were constructed within a day, demonstrating the efficiency of the algorithm and reduction in time and computational cost compared to simulation.