Protein engineering of Pseudomonas fluorescens peroxidase Dyp1B for oxidation of phenolic and polymeric lignin substrates

Directed evolution was applied to dye-decolourizing peroxidase Dyp1B from Pseudomonas fluorescens Pf-5, in order to enhance the activity for oxidation of phenolic and lignin substrates. Saturation mutagenesis was used to generate focused libraries at 7 active site residues in the vicinity of the heme cofactor, and the libraries were screened for activity towards 2,6-dichlorophenol. Mutants N193 L and H169 L were found to show 7–8 fold enhanced kcat/KM towards DCP, and replacements at Val205 and Ala209 also showed enhanced activity towards alkali Kraft lignin. Residues near the predicted Mn(II) binding site were also investigated by site-directed mutagenesis, and mutants S223 N and H127R showed 4-7-fold increased kcat/KM for Mn(II) oxidation. Mutant F128R also showed enhanced thermostability, compared to wild-type Dyp1B. Testing of mutants for low molecular weight product release from Protobind alkali lignin revealed that mutant H169 L showed enhanced product release, compared with WT enzyme, and the formation of three low molecular weight metabolites by this mutant was detected by reverse phase HPLC analysis

A structural view of microRNA-target recognition

It is well established that the correct identification of the messenger RNA targeted by a given microRNA (miRNA) is a difficult problem, and that available methods all suffer from low specificity. We hypothesize that the correct identification of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process. Therefore, we developed a strategy named MiREN for building and scoring three-dimensional models of the ternary complex formed by AGO, a miRNA and 22 nt of a target mRNA that putatively interacts with it. We show here that MiREN can be used to assess the likelihood that an RNA molecule is the target of a given miRNA and that this approach is more accurate than other existing methods, usually based on sequence or sequence-related features. Our results also suggest that AGO plays a relevant role in the selection of the miRNA targets. Our method can represent an additional step for refining predictions made by faster but less accurate classical methods for the identification of miRNA targets

do_x3dna: A tool to analyze structural fluctuations of dsDNA or dsRNA from molecular dynamics simulations.

The do_x3dna package has been developed to analyze the structural fluctuations of DNA or RNA during molecular dynamics simulations. It extends the capability of the 3DNA package to GROMACS MD trajectories and includes new methods to calculate the global-helical axis of DNA and bending fluctuations during simulations. The package also includes a Python module dnaMD to perform and visualize statistical analyses of complex data obtained from the trajectories

Pyrone-based inhibitors of metalloproteinase types 2 and 3 may work as conformation-selective inhibitors.

Matrix metalloproteinases are zinc-containing enzymes capable of degrading all components of the extracellular matrix. Owing to their role in human disease, matrix metalloproteinase have been the subject of extensive study. A bioinorganic approach was recently used to identify novel inhibitors based on a maltol zinc-binding group, but accompanying molecular-docking studies failed to explain why one of these inhibitors, AM-6, had approximately 2500-fold selectivity for MMP-3 over MMP-2. A number of studies have suggested that the matrix-metalloproteinase active site is highly flexible, leading some to speculate that differences in active-site flexibility may explain inhibitor selectivity. To extend the bioinorganic approach in a way that accounts for MMP-2 and MMP-3 dynamics, we here investigate the predicted binding modes and energies of AM-6 docked into multiple structures extracted from matrix-metalloproteinase molecular dynamics simulations. Our findings suggest that accounting for protein dynamics is essential for the accurate prediction of binding affinity and selectivity. Additionally, AM-6 and other similar inhibitors likely select for and stabilize only a subpopulation of all matrix-metalloproteinase conformations sampled by the apo protein. Consequently, when attempting to predict ligand affinity and selectivity using an ensemble of protein structures, it may be wise to disregard protein conformations that cannot accommodate the ligand