ATPase cycle and DNA unwinding kinetics of RecG helicase

The superfamily 2 bacterial helicase, RecG, is a monomeric enzyme with a role in DNA repair by reversing stalled replication forks. The helicase must act specifically and rapidly to prevent replication fork collapse. We have shown that RecG binds tightly and rapidly to four-strand oligonucleotide junctions, which mimic a stalled replication fork. The helicase unwinds such DNA junctions with a step-size of approximately four bases per ATP hydrolyzed. To gain an insight into this mechanism, we used fluorescent stopped-flow and quenched-flow to measure individual steps within the ATPase cycle of RecG, when bound to a DNA junction. The fluorescent ATP analogue, mantATP, was used throughout to determine the rate limiting steps, effects due to DNA and the main states in the cycle. Measurements, when possible, were also performed with unlabeled ATP to confirm the mechanism. The data show that the chemical step of hydrolysis is the rate limiting step in the cycle and that this step is greatly accelerated by bound DNA. The ADP release rate is similar to the cleavage rate, so that bound ATP and ADP would be the main states during the ATP cycle. Evidence is provided that the main structural rearrangements, which bring about DNA unwinding, are linked to these states

ATPase mechanism of the 5'-3' DNA helicase, RecD2: evidence for a pre-hydrolysis conformation change

The superfamily 1 helicase, RecD2, is a monomeric, bacterial enzyme with a role in DNA repair, but with 5'-3' activity unlike most enzymes from this superfamily. Rate constants were determined for steps within the ATPase cycle of RecD2 in the presence of ssDNA. The fluorescent ATP analog, mantATP (2'(3')-O-(N-methylanthraniloyl)ATP), was used throughout to provide a complete set of rate constants and determine the mechanism of the cycle for a single nucleotide species. Fluorescence stopped-flow measurements were used to determine rate constants for adenosine nucleotide binding and release, quenched-flow measurements were used for the hydrolytic cleavage step, and the fluorescent phosphate biosensor was used for phosphate release kinetics. Some rate constants could also be measured using the natural substrate, ATP, and these suggested a similar mechanism to that obtained with mantATP. The data show that a rearrangement linked to Mg(2+) coordination, which occurs before the hydrolysis step, is rate-limiting in the cycle and that this step is greatly accelerated by bound DNA. This is also shown here for the PcrA 3'-5' helicase and so may be a general mechanism governing superfamily 1 helicases. The mechanism accounts for the tight coupling between translocation and ATPase activity

The ATPase cycle of PcrA helicase and its coupling to translocation on DNA.

The superfamily 1 bacterial helicase PcrA has a role in the replication of certain plasmids, acting with the initiator protein (RepD) that binds to and nicks the double-stranded origin of replication. PcrA also translocates single-stranded DNA with discrete steps of one base per ATP hydrolyzed. Individual rate constants have been determined for the DNA helicase PcrA ATPase cycle when bound to either single-stranded DNA or a double-stranded DNA junction that also has RepD bound. The fluorescent ATP analogue 2'(3')-O-(N-methylanthraniloyl)ATP was used throughout all experiments to provide a complete ATPase cycle for a single nucleotide species. Fluorescence intensity and anisotropy stopped-flow measurements were used to determine rate constants for binding and release. Quenched-flow measurements provided the kinetics of the hydrolytic cleavage step. The fluorescent phosphate sensor MDCC-PBP was used to measure phosphate release kinetics. The chemical cleavage step is the rate-limiting step in the cycle and is essentially irreversible and would result in the bound ATP complex being a major component at steady state. This cleavage step is greatly accelerated by bound DNA, producing the high activation of this protein compared to the protein alone. The data suggest the possibility that ADP is released in two steps, which would result in bound ADP also being a major intermediate, with bound ADP.P(i) being a very small component. It therefore seems likely that the major transition in structure occurs during the cleavage step, rather than P(i) release. ATP rebinding could then cause reversal of this structural transition. The kinetic mechanism of the PcrA ATPase cycle is very little changed by potential binding to RepD, supporting the idea that RepD increases the processivity of PcrA by increasing affinity to DNA rather than affecting the enzymatic properties per se

DSD – An integrated, web-accessible database of Dehydrogenase Enzyme Stereospecificities

BACKGROUND: Dehydrogenase enzymes belong to the oxidoreductase class and utilise the coenzymes NAD and NADP. Stereo-selectivity is focused on the C4 hydrogen atoms of the nicotinamide ring of NAD(P). Depending upon which hydrogen is transferred at the C4 location, the enzyme is designated as A or B stereospecific. DESCRIPTION: The Dehydrogenase Stereospecificity Database v1.0 (DSD) provides a compilation of enzyme stereochemical data, as sourced from the primary literature, in the form of a web-accessible database. There are two search engines, a menu driven search and a BLAST search. The entries are also linked to several external databases, including the NCBI and the Protein Data Bank, providing wide background information. The database is freely available online at: CONCLUSION: DSD is a unique compilation available on-line for the first time which provides a key resource for the comparative analysis of reductase hydrogen transfer stereospecificity. As databases increasingly form the backbone of science, largely complete databases such as DSD, are a vital addition

PPD v1.0—an integrated, web-accessible database of experimentally determined protein pK(a) values

The Protein pK(a) Database (PPD) v1.0 provides a compendium of protein residue-specific ionization equilibria (pK(a) values), as collated from the primary literature, in the form of a web-accessible postgreSQL relational database. Ionizable residues play key roles in the molecular mechanisms that underlie many biological phenomena, including protein folding and enzyme catalysis. The PPD serves as a general protein pK(a) archive and as a source of data that allows for the development and improvement of pK(a) prediction systems. The database is accessed through an HTML interface, which offers two fast, efficient search methods: an amino acid-based query and a Basic Local Alignment Search Tool search. Entries also give details of experimental techniques and links to other key databases, such as National Center for Biotechnology Information and the Protein Data Bank, providing the user with considerable background information. The database can be found at the following URL:

Alpha helical trans-membrane proteins: Enhanced prediction using a Bayesian approach

Membrane proteins, which constitute approximately 20% of most genomes, are poorly tractable targets for experimental structure determination, thus analysis by prediction and modelling makes an important contribution to their on-going study. Membrane proteins form two main classes: alpha helical and beta barrel trans-membrane proteins. By using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we addressed α-helical topology prediction. This method has accuracies of 77.4% for prokaryotic proteins and 61.4% for eukaryotic proteins. The method described here represents an important advance in the computational determination of membrane protein topology and offers a useful, and complementary, tool for the analysis of membrane proteins for a range of applications

TATPred:a Bayesian method for the identification of twin arginine translocation pathway signal sequences

The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942

LIPPRED: A web server for accurate prediction of lipoprotein signal sequences and cleavage sites

Bacterial lipoproteins have many important functions and represent a class of possible vaccine candidates. The prediction of lipoproteins from sequence is thus an important task for computational vaccinology. Naïve-Bayesian networks were trained to identify SpaseII cleavage sites and their preceding signal sequences using a set of 199 distinct lipoprotein sequences. A comprehensive range of sequence models was used to identify the best model for lipoprotein signal sequences. The best performing sequence model was found to be 10-residues in length, including the conserved cysteine lipid attachment site and the nine residues prior to it. The sensitivity of prediction for LipPred was 0.979, while the specificity was 0.742. Here, we describe LipPred, a web server for lipoprotein prediction; available at the URL: http://www.jenner.ac.uk/LipPred/. LipPred is the most accurate method available for the detection of SpaseIIcleaved lipoprotein signal sequences and the prediction of their cleavage sites

A predictor of membrane class: Discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications