Characterization of Tertiary Folding of RNA by Circular Dichroism and Urea

CD spectroscopy can be used to monitor RNA tertiary folding transitions that may not be observable by absorbance spectroscopy. With the use of computer‐controlled titrators, data can be acquired rapidly, and accurate thermodynamic properties can be obtained over a wide variety of conditions. Thus, CD spectroscopy provides a useful complement to site‐resolved or chemical modification methods.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143699/1/cpnc1105.pd

On Docking, Scoring and Assessing Protein-DNA Complexes in a Rigid-Body Framework

We consider the identification of interacting protein-nucleic acid partners using the rigid body docking method FTdock, which is systematic and exhaustive in the exploration of docking conformations. The accuracy of rigid body docking methods is tested using known protein-DNA complexes for which the docked and undocked structures are both available. Additional tests with large decoy sets probe the efficacy of two published statistically derived scoring functions that contain a huge number of parameters. In contrast, we demonstrate that state-of-the-art machine learning techniques can enormously reduce the number of parameters required, thereby identifying the relevant docking features using a miniscule fraction of the number of parameters in the prior works. The present machine learning study considers a 300 dimensional vector (dependent on only 15 parameters), termed the Chemical Context Profile (CCP), where each dimension reflects a specific type of protein amino acid-nucleic acid base interaction. The CCP is designed to capture the chemical complementarities of the interface and is well suited for machine learning techniques. Our objective function is the Chemical Context Discrepancy (CCD), which is defined as the angle between the native system's CCP vector and the decoy's vector and which serves as a substitute for the more commonly used root mean squared deviation (RMSD). We demonstrate that the CCP provides a useful scoring function when certain dimensions are properly weighted. Finally, we explore how the amino acids on a protein's surface can help guide DNA binding, first through long-range interactions, followed by direct contacts, according to specific preferences for either the major or minor grooves of the DNA

Modeling the Hydration Layer around Proteins: HyPred

AbstractProtein hydration plays an integral role in determining protein function and stability. We develop a simple method with atomic level precision for predicting the solvent density near the surface of a protein. A set of proximal radial distribution functions are defined and calculated for a series of different atom types in proteins using all-atom, explicit solvent molecular dynamic simulations for three globular proteins. A major improvement in predicting the hydration layer is found when the protein is held immobile during the simulations. The distribution functions are used to develop a model for predicting the hydration layer with sub-1-Ångstrom resolution without the need for additional simulations. The model and the distribution functions for a given protein are tested in their ability to reproduce the hydration layer from the simulations for that protein, as well as those for other proteins and for simulations in which the protein atoms are mobile. Predictions for the density of water in the hydration shells are then compared with high occupancy sites observed in crystal structures. The accuracy of both tests demonstrates that the solvation model provides a basis for quantitatively understanding protein solvation and thereby predicting the hydration layer without additional simulations

Structure of a folding intermediate reveals the interplay between core and peripheral elements in RNA folding

Though the molecular architecture of many native RNA structures has been characterized, the structures of folding intermediates are poorly defined. Here, we present a nucleotide-level model of a highly structured equilibrium folding intermediate of the specificity domain of the Bacillus subtilis RNase P RNA, obtained using chemical and nuclease mapping, circular dichroism spectroscopy, small-angle X-ray scattering and molecular modeling. The crystal structure indicates that the 154 nucleotide specificity domain is composed of several secondary and tertiary structural modules. The structure of the intermediate contains modules composed of secondary structures and short-range tertiary interactions, implying a sequential order of tertiary structure formation during folding. The intermediate lacks the native core and several long-range interactions among peripheral regions, such as a GAAA tetraloop and its receptor. Folding to the native structure requires the local rearrangement of a T-loop in the core in concert with the formation of the GAAA tetraloop-receptor interaction. The interplay of core and peripheral structure formation rationalizes the high degree of cooperativity observed in the folding transition leading to the native structure

Discovering RNA-Protein Interactome by Using Chemical Context Profiling of the RNA-Protein Interface

SummaryRNA-protein (RNP) interactions generally are required for RNA function. At least 5% of human genes code for RNA-binding proteins. Whereas many approaches can identify the RNA partners for a specific protein, finding the protein partners for a specific RNA is difficult. We present a machine-learning method that scores a protein’s binding potential for an RNA structure by utilizing the chemical context profiles of the interface from known RNP structures. Our approach is applicable even when only a single RNP structure is available. We examined 801 mammalian proteins and find that 37 (4.6%) potentially bind transfer RNA (tRNA). Most are enzymes involved in cellular processes unrelated to translation and were not known to interact with RNA. We experimentally tested six positive and three negative predictions for tRNA binding in vivo, and all nine predictions were correct. Our computational approach provides a powerful complement to experiments in discovering new RNPs