Bacterial expression, purification and biophysical characterization of the smallest plant reticulon isoform, RTNLB13.

Reticulons are a large family of integral membrane proteins that are ubiquitous in eukaryotes and play a key role in functional remodelling of the endoplasmic reticulum membrane. The reticulon family is especially large in plants, with the Arabidopsis thaliana genome containing twenty-one isoforms. Reticulons vary in length but all contain a conserved C-terminal reticulon homology domain (RHD) that associates with membranes. An understanding of the structure and membrane interactions of RHDs is key to unlocking their mechanism of function, however no three-dimensional structure has been solved. We believe that this is, in part, due to difficulties in obtaining reticulon proteins in yields sufficient for structural study. To address this, we report here the first bacterial overexpression, purification, and biophysical investigation of a reticulon protein from plants, the RTNLB13 protein from A. thaliana. RTNLB13 is the smallest plant reticulon and is made up of a single RHD. We used circular dichroism, SDS-PAGE and analytical ultracentrifugation to reveal that RTNLB13 is 45% α-helical in a number of detergent environments, monomeric at low concentrations, and capable of self-association at higher concentrations. We used solution-state NMR to screen the effect of detergent type on the fold of isotopically-enriched RTNLB13, and found that ∼60% of the expected protein peaks were broadened due to slow dynamics. This broadening points toward a large network of protein-membrane interactions throughout the sequence. We have interpreted our results in light of current literature and suggest a preliminary description of RTNLB13 structure and topology.

Synthesis, Docking Study and Kinase Inhibitory Activity of a Number of New Substituted Pyrazolo[3,4-c]pyridines.

A series of new pyrazolo[3,4-c]pyridines bearing various 1, 3, 5 or 1, 3, 7 pattern substitutions, were designed and synthesized. Some of them showed interesting inhibitory activity mainly against glycogen synthase kinase 3 (GSK3)α/ß as well as against cdc2-like kinases 1 (CLK1) and dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), with good selectivity and remarkable structure-activity relationships (SARs), without being cytotoxic. Molecular simulations in correlation with biological data revealed the importance of the existence of N1-H as well as the absence of a bulky 7-substituent.

Protein secondary structure prediction from circular dichroism spectra using a self-organizing map with concentration correction.

Collecting circular dichroism (CD) spectra for protein solutions is a simple experiment, yet reliable extraction of secondary structure content is dependent on knowledge of the concentration of the protein--which is not always available with accuracy. We previously developed a self-organizing map (SOM), called Secondary Structure Neural Network (SSNN), to cluster a database of CD spectra and use that map to assign the secondary structure content of new proteins from CD spectra. The performance of SSNN is at least as good as other available protein CD structure-fitting algorithms. In this work we apply SSNN to a collection of spectra of experimental samples where there was suspicion that the nominal protein concentration was incorrect. We show that by plotting the normalized root mean square deviation of the SSNN predicted spectrum from the experimental one versus a concentration scaling-factor it is possible to improve the estimate of the protein concentration while providing an estimate of the secondary structure. For our implementation (51 data points 240-190 nm in nm increments) good fits and structure estimates were obtained if the NRMSD (normalized root mean square displacement, RMSE/data range) is <0.03; reasonable for NRMSD <0.05; and variable above this. We also augmented the reference database with 100% helical spectra and truly random coil spectra.