Determination of hepatitis delta virus ribozyme N(-1) nucleobase and functional group specificity using internal competition kinetics

Hierarchical Reactivity of Enzyme-Mediated Phosphorus Recycling from Organic Mixtures by Aspergillus niger Phytase

Biological recycling of inorganic phosphorus (P_i) from organic phosphorus (P_o) compounds by phosphatase-type enzymes, including phytases, is an important contributor to the pool of bioavailable P to plants and microorganisms. However, studies of mixed-substrate reactions with these enzymes are lacking. Here, we explore the reactivity of a phytase extract from the fungus Aspergillus niger toward a heterogeneous mixture containing, in addition to phytate, different structures of environmentally relevant P_o compounds such as ribonucleotides and sugar phosphates. Using a high-resolution liquid chromatography-mass spectrometry method to monitor simultaneously the parent P_o compounds and their by-products, we captured sequential substrate-specific evolution of P_i from the mixture, with faster hydrolysis of multiphosphorylated compounds (phytate, diphosphorylated sugars, and di- and tri-phosphorylated ribonucleotides) than hydrolysis of monophosphorylated compounds (monophosphorylated sugars and monophosphorylated ribonucleotides). The interaction mechanisms and energies revealed by molecular docking simulations of each P_o compound within the enzyme's active site explained the substrate hierarchy observed experimentally. Specifically, the favorable orientation for binding of the negatively charged phosphate moieties with respect to the positive potential surface of the active site was important. Collectively, our findings provide mechanistic insights about the broad but hierarchical role of phytase-type enzymes in P_i recycling from the heterogeneous assembly of P_o compounds in agricultural soils or wastes.

Cotranscriptional 3'-End Processing of T7 RNA Polymerase Transcripts by a Smaller HDV Ribozyme

In vitro run-off transcription by T7 RNA polymerase generates heterogeneous 3'-ends because the enzyme tends to add untemplated adenylates. To generate homogeneous 3'-termini, HDV ribozymes have been used widely. Their sequences are added to the 3'-terminus such that co-transcriptional self-cleavage generates homogeneous 3'-ends. A shorter HDV sequence that cleaves itself efficiently would be advantageous. Here we show that a recently discovered, small HDV ribozyme is a good alternative to the previously used HDV ribozyme. The new HDV ribozyme is more efficient in some sequence contexts, and less efficient in other sequence contexts than the previously used HDV ribozyme. The smaller size makes the new HDV ribozyme a good alternative for transcript 3'-end processing.

Evidence That Nucleophile Deprotonation Exceeds Bond Formation in the HDV Ribozyme Transition State

Steric constraints imposed by the active sites of protein and RNA enzymes pose major challenges to the investigation of structure-function relationships within these systems. As a strategy to circumvent such constraints in the HDV ribozyme, we have synthesized phosphoramidites from propanediol derivatives and incorporated them at the 5'-termini of RNA and DNA oligonucleotides to generate a series of novel substrates with nucleophiles perturbed electronically through geminal fluorination. In nonenzymatic, hydroxide-catalyzed intramolecular transphosphorylation of the DNA substrates, pH-rate profiles revealed that fluorine substitution reduces the maximal rate and the kinetic p K_a, consistent with the expected electron-withdrawing effect. In HDV ribozyme reactions, we observed that the RNA substrates undergo transphosphorylation relatively efficiently, suggesting that the conformational constraints imposed by a ribofuranose ring are not strictly required for ribozyme catalysis. In contrast to the nonenzymatic reactions, however, substrate fluorination modestly increases the ribozyme reaction rate, consistent with a mechanism in which (1) the 2'-hydroxyl nucleophile exists predominantly in its neutral, protonated form in the ground state and (2) the 2'-hydroxyl bears some negative charge in the rate-determining step, consistent with a transition state in which the extent of 2'-OH deprotonation exceeds the extent of P-O bond formation.

Investigating the Relationship between the Substrates' Consumption and Their Abundances in a Complex Enzymatic System

The enzymatic process involving the incubation of a library of substrates with an enzyme is the key step for a few important experiments for bioanalytical chemistry including proteomics analysis, enzymatic labeling, substrate screening, etc. The relationship between the substrates' consumption and their abundances in a complex enzymatic system with a huge number of coexisting substrates of different abundances was not well-known. In this study, we have demonstrated theoretically and experimentally that the priority of substrate consumption depended on their specificity constants but not abundances. We derived the expression between the fractions of the substrates consumed (p_i) and their specificity constants. Using the enzymatic system of five synthetic peptide substrates of trypsin, we validated through 24 experiments that the ln(1 - p_i) values of competing substrates have linear correlation with their specificity constants, and thus, the priority of substrate depletion has no relation with their abundances. Using a state of the art quantitative proteomics approach, we found that the ln(1 - p_i) values of 144 competing substrates between any two of four experiments have a linear relationship and the prioritization of substrates can be achieved by sorting their consumption rates in the experiment. This study will improve our understanding of the enzymatic kinetics in the complex system and will benefit the design of enzymatic analytical approaches.

How to understand atomistic molecular dynamics simulations of RNA and protein-RNA complexes?

We provide a critical assessment of explicit-solvent atomistic molecular dynamics (MD) simulations of RNA and protein/RNA complexes, written primarily for non-specialists with an emphasis to explain the limitations of MD. MD simulations can be likened to hypothetical single-molecule experiments starting from single atomistic conformations and investigating genuine thermal sampling of the biomolecules. The main advantage of MD is the unlimited temporal and spatial resolution of positions of all atoms in the simulated systems. Fundamental limitations are the short physical time-scale of simulations, which can be partially alleviated by enhanced-sampling techniques, and the highly approximate atomistic force fields describing the simulated molecules. The applicability and present limitations of MD are demonstrated on studies of tetranucleotides, tetraloops, ribozymes, riboswitches and protein/RNA complexes. Wisely applied simulations respecting the approximations of the model can successfully complement structural and biochemical experiments. WIREs RNA 2017, 8:e1405. doi: 10.1002/wrna.1405 For further resources related to this article, please visit the WIREs website.

Optimization of high-throughput sequencing kinetics for determining enzymatic rate constants of thousands of RNA substrates

Quantification of the specificity of RNA binding proteins and RNA processing enzymes is essential to understanding their fundamental roles in biological processes. High-throughput sequencing kinetics (HTS-Kin) uses high-throughput sequencing and internal competition kinetics to simultaneously monitor the processing rate constants of thousands of substrates by RNA processing enzymes. This technique has provided unprecedented insight into the substrate specificity of the tRNA processing endonuclease ribonuclease P. Here, we investigated the accuracy and robustness of measurements associated with each step of the HTS-Kin procedure. We examine the effect of substrate concentration on the observed rate constant, determine the optimal kinetic parameters, and provide guidelines for reducing error in amplification of the substrate population. Importantly, we found that high-throughput sequencing and experimental reproducibility contribute to error, and these are the main sources of imprecision in the quantified results when otherwise optimized guidelines are followed.