Correlation between amino acid residues converted by RNA editing and functional residues in protein three-dimensional structures in plant organelles

<p>Abstract</p> <p>Background</p> <p>In plant organelles, specific messenger RNAs (mRNAs) are subjected to conversion editing, a process that often converts the first or second nucleotide of a codon and hence the encoded amino acid. No systematic patterns in converted sites were found on mRNAs, and the converted sites rarely encoded residues located at the active sites of proteins. The role and origin of RNA editing in plant organelles remain to be elucidated.</p> <p>Results</p> <p>Here we study the relationship between amino acid residues encoded by edited codons and the structural characteristics of these residues within proteins, e.g., in protein-protein interfaces, elements of secondary structure, or protein structural cores. We find that the residues encoded by edited codons are significantly biased toward involvement in helices and protein structural cores. RNA editing can convert codons for hydrophilic to hydrophobic amino acids. Hence, only the edited form of an mRNA can be translated into a polypeptide with helix-preferring and core-forming residues at the appropriate positions, which is often required for a protein to form a functional three-dimensional (3D) structure.</p> <p>Conclusion</p> <p>We have performed a novel analysis of the location of residues affected by RNA editing in proteins in plant organelles. This study documents that RNA editing sites are often found in positions important for 3D structure formation. Without RNA editing, protein folding will not occur properly, thus affecting gene expression. We suggest that RNA editing may have conferring evolutionary advantage by acting as a mechanism to reduce susceptibility to DNA damage by allowing the increase in GC content in DNA while maintaining RNA codons essential to encode residues required for protein folding and activity.</p

Revisiting gap locations in amino acid sequence alignments and a proposal for a method to improve them by introducing solvent accessibility

In comparative modeling, the quality of amino acid sequence alignment still constitutes a major bottleneck in the generation of high quality models of protein three-dimensional (3D) structures. Substantial efforts have been made to improve alignment quality by revising the substitution matrix, introducing multiple sequences, replacing dynamic programming with hidden Markov models, and incorporating 3D structure information. Improvements in the gap penalty have not been a major focus, however, following the development of the affine gap penalty and of the secondary structure dependent gap penalty. We revisited the correlation between protein 3D structure and gap location in a large protein 3D structure data set, and found that the frequency of gap locations approximated to an exponential function of the solvent accessibility of the inserted residues. The nonlinearity of the gap frequency as a function of accessibility corresponded well to the relationship between residue mutation pattern and residue accessibility. By introducing this relationship into the gap penalty calculation for pairwise alignment between template and target amino acid sequences, we were able to obtain a sequence alignment much closer to the structural alignment. The quality of the alignments was substantially improved on a pair of sequences with identity in the “twilight zone” between 20 and 40%. The relocation of gaps by our new method made a significant improvement in comparative modeling, exemplified here by the Bacillus subtilis yitF protein. The method was implemented in a computer program, ALAdeGAP (ALignment with Accessibility dependent GAp Penalty), which is available at http://cib.cf.ocha.ac.jp/target_protein/. Proteins 2011; © 2011 Wiley-Liss, Inc

Key Interactions in Integrin Ectodomain Responsible for Global Conformational Change Detected by Elastic Network Normal-Mode Analysis

AbstractIntegrin, a membrane protein with a huge extracellular domain, participates in cell-cell and cell-extracellular-matrix interactions for metazoan. A group of integrins is known to perform a large-scale structural change when the protein is activated, but the activation mechanism and generality of the conformational change remain to be elucidated. We performed normal-mode analysis of the elastic network model on integrin αVβ3 ectodomain in the bent form and identified key residues that influenced molecular motions. Iterative normal-mode calculations demonstrated that the specific nonbonded interactions involving the key residues work as a snap to keep integrin in the bent form. The importance of the key residues for the conformational change was further verified by mutation experiments, in which integrin αIIbβ3 was used. The conservation pattern of amino acid residues among the integrin family showed that the characteristic pattern of residues seen around these key residues is found in the limited groups of integrin β-chains. This conservation pattern suggests that the molecular mechanism of the conformational change relying on the interactions found in integrin αVβ3 is unique to the limited types of integrins

Development of Convolutional Neural Networks for an Electron-Tracking Compton Camera

Electron-tracking Compton camera, which is a complete Compton camera with tracking Compton scattering electron by a gas micro time projection chamber, is expected to open up MeV gamma-ray astronomy. The technical challenge for achieving several degrees of the point spread function is the precise determination of the electron-recoil direction and the scattering position from track images. We attempted to reconstruct these parameters using convolutional neural networks. Two network models were designed to predict the recoil direction and the scattering position. These models marked 41$~$degrees of the angular resolution and 2.1$~$mm of the position resolution for 75$~$keV electron simulation data in Argon-based gas at 2$~$atm pressure. In addition, the point spread function of ETCC was improved to 15$~$degrees from 22$~$degrees for experimental data of 662$~$keV gamma-ray source. These performances greatly surpassed that using the traditional analysis

Impact of pathogenic mutations of the GLUT1 glucose transporter on solute carrier dynamics using ComDYN enhanced sampling

Background: The solute carrier (SLC) family of membrane proteins is a large class of transporters for many small molecules that are vital for cellular function. Several pathogenic mutations are reported in the glucose transporter subfamily SLC2, causing Glut1-deficiency syndrome (GLUT1DS1, GLUT1DS2), epilepsy (EIG2) and cryohydrocytosis with neurological defects (Dystonia-9). Understanding the link between these mutations and transporter dynamics is crucial to elucidate their role in the dysfunction of the underlying transport mechanism, which we investigate using molecular dynamics simulations. \nMethods: We studied pathogenic and non-pathogenic mutations, using a newly developed coarse-grained simulation approach \xe2\x80\x98ComDYN\xe2\x80\x99, which captures the \xe2\x80\x98COMmon constraints DYNamics\xe2\x80\x99 between both states of the solute carrier protein. To guarantee the sampling of large conformational changes, we only include common constraints of the elastic network introduced upon coarse-graining, which showed similar reference distances between both conformational states (\xe2\x89\xa41 \xc3\x85 difference). \nResults: ComDYN is computationally efficient and sufficiently sensitive to capture effects of different mutations. Our results clearly indicate that the pathogenic mutation in GLUT1, G91D, situated at the highly conserved RXGRR motif between helices 2 and 3, has a strong impact on transporter function, as it blocks the protein from sampling both conformational states. In comparison, predictions from SIFT and PolyPhen only provided an impression of the impact upon mutation in the highly conserved RXGRR motifs, but yielded no clear differentiation between pathogenic and non-pathogenic mutations. \nConclusions: Using our approach, we can explain the pathogenicity of the mutation G91D and some of the effects of other known pathogenic mutations, when we observe the configurations of the transmembrane helices, suggesting that their relative position is crucial for the correct functioning of the GLUT1 protein. To fully understand the impact of other mutations in the future, it is necessary to consider the effect of ligands, e.g., glucose, within the transport mechanism

A Bicyclic 1-Deoxygalactonojirimycin Derivative as a Novel Pharmacological Chaperone for GM1 Gangliosidosis

Lysosomal β-galactosidase (β-Gal) deficiency causes a group of disorders that include neuronopathic GM1 gangliosidosis and non-neuronopathic Morquio B disease. We have previously proposed the use of small molecule ligands of β-Gal as pharmacological chaperones (PCs) for the treatment of GM1 gangliosidosis brain pathology. Although it is still under development, PC therapy has yielded promising preclinical results in several lysosomal diseases. In this study, we evaluated the effect of bicyclic 1-deoxygalactonojirimycin (DGJ) derivative of the sp2-iminosugar type, namely 5N,6S-(N′-butyliminomethylidene)-6-thio-1- deoxygalactonojirimycin (6S-NBI-DGJ), as a novel PC for human mutant β-Gal. In vitro, 6S-NBI-DGJ had the ability to inhibit the activity of human β-Gal in a competitive manner and was able to protect this enzyme from heat-induced degradation. Computational analysis supported that the rigid glycone bicyclic core of 6S-NBI-DGJ binds to the active site of the enzyme, with the aglycone N′-butyl substituent, in a precise E-orientation, located at a hydrophobic region nearby. Chaperone potential profiling indicated significant increases of enzyme activity in 24 of 88 β-Gal mutants, including four common mutations. Finally, oral administration of 6S-NBI-DGJ ameliorated the brain pathology of GM1 gangliosidosis model mice. These results suggest that 6S-NBI-DGJ is a novel PC that may be effective on a broad range of β-Gal mutants.Ministerio de Ciencia e Innovación de España. SAF2010-15670 y CTQ2010-15848Junta de Andalucía. P08-FQM-0371

RESOPS: A Database for Analyzing the Correspondence of RNA Editing Sites to Protein Three-Dimensional Structures

Transcripts from mitochondrial and chloroplast DNA of land plants often undergo cytidine to uridine conversion-type RNA editing events. RESOPS is a newly built database that specializes in displaying RNA editing sites of land plant organelles on protein three-dimensional (3D) structures to help elucidate the mechanisms of RNA editing for gene expression regulation. RESOPS contains the following information: unedited and edited cDNA sequences with notes for the target nucleotides of RNA editing, conceptual translation from the edited cDNA sequence in pseudo-UniProt format, a list of proteins under the influence of RNA editing, multiple amino acid sequence alignments of edited proteins, the location of amino acid residues coded by codons under the influence of RNA editing in protein 3D structures and the statistics of biased distributions of the edited residues with respect to protein structures. Most of the data processing procedures are automated; hence, it is easy to keep abreast of updated genome and protein 3D structural data. In the RESOPS database, we clarified that the locations of residues switched by RNA editing are significantly biased to protein structural cores. The integration of different types of data in the database also help advance the understanding of RNA editing mechanisms. RESOPS is accessible at http://cib.cf.ocha.ac.jp/RNAEDITING/

Amino acid residue doublet propensity in the protein–RNA interface and its application to RNA interface prediction

Protein–RNA interactions play essential roles in a number of regulatory mechanisms for gene expression such as RNA splicing, transport, translation and post-transcriptional control. As the number of available protein–RNA complex 3D structures has increased, it is now possible to statistically examine protein–RNA interactions based on 3D structures. We performed computational analyses of 86 representative protein–RNA complexes retrieved from the Protein Data Bank. Interface residue propensity, a measure of the relative importance of different amino acid residues in the RNA interface, was calculated for each amino acid residue type (residue singlet interface propensity). In addition to the residue singlet propensity, we introduce a new residue-based propensity, which gives a measure of residue pairing preferences in the RNA interface of a protein (residue doublet interface propensity). The residue doublet interface propensity contains much more information than the sum of two singlet propensities alone. The prediction of the RNA interface using the two types of propensities plus a position-specific multiple sequence profile can achieve a specificity of about 80%. The prediction method was then applied to the 3D structure of two mRNA export factors, TAP (Mex67) and UAP56 (Sub2). The prediction enables us to point out candidate RNA interfaces, part of which are consistent with previous experimental studies and may contribute to elucidation of atomic mechanisms of mRNA export