Insights into the mechanism(s) of digestion of crystalline cellulose by plant class C GH9 endoglucanases

Structure elucidation of a multi-modular recombinant endoglucanase, AtGH9C-CBM3A-CBM3B from Acetivibrio thermocellus ATCC 27405 and its substrate binding analysis

Cellulases from GH9 family show endo-, exo- or processive endocellulase activity, but the reason behind the variation is unclear. A GH9 recombinant endoglucanase, AtGH9C-CBM3A-CBM3B from Acetivibrio thermocellus was structurally characterized for conformation, binding and dynamics assessment. Modeled AtGH9C-CBM3A-CBM3B depicted (α/α)6-barrel structure with Asp98, Asp101 and Glu489 acting as catalytic triad. CD results revealed 25.2 % α-helix, 18.4 % β-sheet and rest 56.4 % of random coils, corroborating with predictions from PSIPRED and SOPMA. MD simulation of AtGH9C-CBM3A-CBM3B bound cellotetraose showed structural stability and global compactness with lowered RMSD values (1.5 nm) as compared with only AtGH9C-CBM3A-CBM3B (1.8 nm) for 200 ns. Higher fluctuation in RMSF values in far-positioned CBM3B pointed to its redundancy in substrate binding. Docking studies showed maximum binding with cellotetraose (ΔG = -5.05 kcal/mol), with reduced affinity towards ligands with degree of polymerization (DP) lower (DP < 4) or higher than 4 (DP > 4). Processivity index displayed the enzyme to be processive with loop 3 (342-379 aa) possibly blocking the non-reducing end of cellulose chain, resulting in cellotetraose release. SAXS analysis of AtGH9C-CBM3A-CBM3B at 5 mg/mL displayed monodispersed state with fist-and-elbow shape in solution. Negative zeta potential of -24 mV at 5 mg/mL indicated stability and free from aggregation.

Modeling ligand-macromolecular interactions as eigenvalue-based transition-state dissociation constants may offer insights into biochemical function of the resulting complexes

A ligand when bound to a macromolecule (protein, DNA, RNA) will influence the biochemical function of that macromolecule. This observation is empirical and attributable to the association of the ligand with the amino acids/nucleotides that comprise the macromolecule. The binding affinity is a measure of the strength-of-association of a macromolecule for its ligand and is numerically characterized by the association/dissociation constant. However, despite being widely used, a mathematically rigorous explanation by which the association/dissociation constant can influence the biochemistry and molecular biology of the resulting complex is not available. Here, the ligand-macromolecular complex is modeled as a homo- or hetero-dimer with a finite and equal number of atoms/residues per monomer. The pairwise interactions are numeric, empirically motivated and are randomly chosen from a standard uniform distribution. The transition-state dissociation constants are the strictly positive real part of all complex eigenvalues of this interaction matrix, belong to the open interval (0,1), and form a sequence whose terms are finite, monotonic, non-increasing and convergent. The theoretical results are rigorous, presented as theorems, lemmas and corollaries and are complemented by numerical studies. An inferential analysis of the clinical outcomes of amino acid substitutions of selected enzyme homodimers is also presented. These findings are extendible to higher-order complexes such as those likely to occur in vivo. The study also presents a schema by which a ligand can be annotated and partitioned into high- and low-affinity variants. The influence of the transition-state dissociation constants on the biochemistry and molecular biology of non-haem iron (Ⅱ)- and 2-oxoglutarate-dependent dioxygenases (catalysis) and major histocompatibility complex (Ⅰ) mediated export of high-affinity peptides (non-enzymatic association/dissociation) are examined as special cases.

Emerging Roles of β-Glucanases in Plant Development and Adaptative Responses

Plant β-glucanases are enzymes involved in the synthesis, remodelling and turnover of cell wall components during multiple physiological processes. Based on the type of the glycoside bond they cleave, plant β-glucanases have been grouped into three categories: (i) β-1,4-glucanases degrade cellulose and other polysaccharides containing 1,4-glycosidic bonds to remodel and disassemble the wall during cell growth. (ii) β-1,3-glucanases are responsible for the mobilization of callose, governing the symplastic trafficking through plasmodesmata. (iii) β-1,3-1,4-glucanases degrade mixed linkage glucan, a transient wall polysaccharide found in cereals, which is broken down to obtain energy during rapid seedling growth. In addition to their roles in the turnover of self-glucan structures, plant β-glucanases are crucial in regulating the outcome in symbiotic and hostile plant-microbe interactions by degrading non-self glucan structures. Plants use these enzymes to hydrolyse β-glucans found in the walls of microbes, not only by contributing to a local antimicrobial defence barrier, but also by generating signalling glucans triggering the activation of global responses. As a counterpart, microbes developed strategies to hijack plant β-glucanases to their advantage to successfully colonize plant tissues. This review outlines our current understanding on plant β-glucanases, with a particular focus on the latest advances on their roles in adaptative responses.

ProTG4: A Web Server to Approximate the Sequence of a Generic Protein From an in Silico Library of Translatable G-Quadruplex (TG4)-Mapped Peptides

An RNA G-quadruplex in the protein coding segment of mRNA is translatable (TG4) and may potentially impact protein translation. This can be consequent to staggered ribosomal synthesis and/or result in an increased frequency of missense translational events. A mathematical model of the peptides that encompass the substituted amino acids, ie, the TG4-mapped peptidome, has been previously studied. However, the significance and relevance to disease biology of this model remains to be established. ProTG4 computes a confidence-of-sequence-identity (γ)-score, which is the average weighted length of every matched TG4-mapped peptide in a generic protein sequence. The weighted length is the product of the length of the peptide and the probability of its non-random occurrence in a library of randomly generated sequences of equivalent lengths. This is then averaged over the entire length of the protein sequence. ProTG4 is simple to operate, has clear instructions, and is accompanied by a set of ready-to-use examples. The rationale of the study, algorithms deployed, and the computational pipeline deployed are also part of the web page. Analyses by ProTG4 of taxonomically diverse protein sequences suggest that there is significant homology to TG4-mapped peptides. These findings, especially in potentially infectious and infesting agents, offer plausible explanations into the aetiology and pathogenesis of certain proteopathies. ProTG4 can also provide a quantitative measure to identify and annotate the canonical form of a generic protein sequence from its known isoforms. The article presents several case studies and discusses the relevance of ProTG4-assisted peptide analysis in gaining insights into various mechanisms of disease biology (mistranslation, alternate splicing, amino acid substitutions).

Fe(2)OG: an integrated HMM profile-based web server to predict and analyze putative non-haem iron(II)- and 2-oxoglutarate-dependent dioxygenase function in protein sequences

Objective

Non-haem iron(II)- and 2-oxoglutarate-dependent dioxygenases (i2OGdd), are a taxonomically and functionally diverse group of enzymes. The active site comprises ferrous iron in a hexa-coordinated distorted octahedron with the apoenzyme, 2-oxoglutarate and a displaceable water molecule. Current information on novel i2OGdd members is sparse and relies on computationally-derived annotation schema. The dissimilar amino acid composition and variable active site geometry thereof, results in differing reaction chemistries amongst i2OGdd members. An additional need of researchers is a curated list of sequences with putative i2OGdd function which can be probed further for empirical data.

Results

This work reports the implementation of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fe\left(2\right)OG$$\end{document}Fe2OG, a web server with dual functionality and an extension of previous work on i2OGdd enzymes \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(Fe\left(2\right)OG\equiv \{H2OGpred,DB2OG\}\right)$$\end{document}Fe2OG≡{H2OGpred,DB2OG}. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fe\left(2\right)OG$$\end{document}Fe2OG, in this form is completely revised, updated (URL, scripts, repository) and will strengthen the knowledge base of investigators on i2OGdd biochemistry and function. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fe\left(2\right)OG$$\end{document}Fe2OG, utilizes the superior predictive propensity of HMM-profiles of laboratory validated i2OGdd members to predict probable active site geometries in user-defined protein sequences. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fe\left(2\right)OG$$\end{document}Fe2OG, also provides researchers with a pre-compiled list of analyzed and searchable i2OGdd-like sequences, many of which may be clinically relevant. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Fe(2)OG$$\end{document}Fe(2)OG, is freely available (http://204.152.217.16/Fe2OG.html) and supersedes all previous versions, i.e., H2OGpred, DB2OG.

Genomic and transcriptomic landscapes and evolutionary dynamics of molluscan glycoside hydrolase families with implications for algae-feeding biology

•

Genome-wide characterization of GH families is conducted for Mollusca.

•

GH9, GH10, GH18 and GH20 families are remarkably expanded in molluscs.

•

The wide adoption of CBMs likely facilitates the hydrolysis of polysaccharides.

•

Hepatopancreas is the main organ for the prominent expression of GH families.

•

Functional divergence of GH families possibly contributes to their adaptive roles.

The hydrolysis of sugar-containing compounds by glycoside hydrolases (GHs) plays essential roles in many major biological processes, but to date our systematic understanding of the functional diversity and evolution of GH families remains largely limited to a few well-studied terrestrial animals. Molluscs represent the largest marine phylum in the animal kingdom, and many of them are herbivorous that utilize algae as a main nutritional source, making them good subjects for studying the functional diversity and adaptive evolution of GH families. In the present study, we conducted genome-wide identification and functional and evolutionary analysis of all GH families across major molluscan lineages. We revealed that the remarkable expansion of the GH9, GH10, GH18 and GH20 families and the wide adoption of carbohydrate-binding modules in molluscan expanded GH families likely contributed to the efficient hydrolysis of marine algal polysaccharides and were involved in the consolidation of molluscan algae-feeding habits. Gene expression and network analysis revealed the hepatopancreas as the main organ for the prominent expression of approximately half of the GH families (well corresponding to the digestive roles of the hepatopancreas) and key or hub GHs in the coexpression gene network with potentially diverse functionalities. We also revealed the evolutionary signs of differential expansion and functional divergence of the GH family, which possibly contributed to lineage-specific adaptation. Systematic analysis of GH families at both genomic and transcriptomic levels provides important clues for understanding the functional divergence and evolution of GH gene families in molluscs in relation to their algae-feeding biology.