Redirecting RiPP biosynthetic enzymes to proteins and backbone-modified substrates

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are peptide-derived natural products that include the FDA-approved analgesic ziconotide1,2 as well as compounds with potent antibiotic, antiviral, and anticancer properties.3 RiPP enzymes known as cyclodehydratases and dehydrogenases represent an exceptionally well-studied enzyme class.3 These enzymes work together to catalyze intramolecular, interresidue condensation3,4 and aromatization reactions that install oxazoline/oxazole and thiazoline/thiazole heterocycles within ribosomally produced polypeptide chains. Here we show that the previously reported enzymes MicD-F and ArtGox accept backbone-modified monomers, including aramids and beta-amino acids, within leader-free polypeptides, even at positions immediately preceding or following the site of cyclization/dehydrogenation. The products are sequence-defined chemical polymers with multiple, diverse, non-alpha-amino acid subunits. We show further that MicD-F and ArtGox can install heterocyclic backbones within protein loops and linkers without disrupting the native tertiary fold. Calculations reveal the extent to which these heterocycles restrict conformational space; they also eliminate a peptide bond. Both features could improve the stability or add function to linker sequences now commonplace in emerging biotherapeutics. Moreover, as thiazoles and thiazoline heterocycles are replete in natural products,5,6,7 small molecule drugs,8,9 and peptide-mimetic therapeutics,10 their installation in protein-based biotherapeutics could improve or augment performance, activity, stability, and/or selectivity. This work represents a general strategy to expand the chemical diversity of the proteome beyond and in synergy with what can now be accomplished by expanding the genetic code.

Experimental and computational investigation of enzyme functional annotations uncovers misannotation in the EC 1.1.3.15 enzyme class

Only a small fraction of genes deposited to databases have been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy within individual enzyme classes are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in the BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity or domain architecture to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.

Glycomic and glycotranscriptomic profiling of mucin-type O-glycans in planarian Schmidtea mediterranea

O-Glycans on cell surfaces play important roles in cell-cell, cell-matrix, and receptor-ligand interaction. Therefore, glycan-based interactions are important for tissue regeneration and homeostasis. Free-living flatworm Schmidtea mediterranea, because of its robust regenerative potential, is of great interest in the field of stem cell biology and tissue regeneration. Nevertheless, information on the composition and structure of O-glycans in planaria is unknown. Using mass spectrometry and in silico approaches, we characterized the glycome and the related transcriptome of mucin-type O-glycans of planarian S. mediterranea. Mucin-type O-glycans were composed of multiple isomeric, methylated, and unusually extended mono- and di-substituted O-GalNAc structures. Extensions made of hexoses and 3-O methyl hexoses were the glycoforms observed. From glycotranscriptomic analysis, sixty genes belonging to five distinct enzyme classes were identified to be involved in mucin-type O-glycan biosynthesis. These genes shared homology with those in other invertebrate systems. While a majority of the genes involved in mucin-type O-glycan biosynthesis was highly expressed during organogenesis and in differentiated cells, a few select genes in each enzyme class were specifically enriched during early embryogenesis. Our results indicate a unique temporal and spatial role for mucin-type O-glycans during embryogenesis and organogenesis and in adulthood. In summary, this is the first report on O-glycans in planaria. This study expands the structural and biosynthetic possibilities in cellular glycosylation in the invertebrate glycome and provides a framework towards understanding the biological role of mucin-type O-glycans in tissue regeneration using planarians.

Allosteric cooperation in β-lactam binding to a non-classical transpeptidase

Mycobacterium tuberculosis peptidoglycan (PG) is atypical as its synthesis involves a new enzyme class, L,D-transpeptidases. Prior studies of L,D-transpeptidases have identified only the catalytic site that binds to peptide moiety of the PG substrate or β-lactam antibiotics. This insight was leveraged to develop mechanism of its activity and inhibition by β-lactams. Here we report identification of an allosteric site at a distance of 21 Å from the catalytic site that binds the sugar moiety of PG substrates (hereafter referred to as the S-pocket). This site also binds a second β-lactam molecule and influences binding at the catalytic site. We provide evidence that two β-lactam molecules bind co-operatively to this enzyme, one non covalently at the S-site and one covalently at the catalytic site. This dual β-lactam binding phenomenon is previously unknown and is an observation that may offer novel approaches for the structure-based design of new β-lactam antibiotics for M. tuberculosis.

Aryl-CoA Ligases, subfamily of the adenylate-forming enzyme superfamily

Aryl-CoA ligases belong to class I of the adenylate-forming enzyme superfamily (ANL superfamily) and catalyze the formation of thioester bonds between aromatic compounds and Coenzyme A (CoA) and occur in nearly all forms of life. These ligases are involved in various metabolic pathways degrading benzene, toluene, ethylbenzene, and xylene (BTEX) or polycyclic aromatic hydrocarbons (PAHs). They are often necessary to produce the central intermediate benzoyl-CoA that occurs in various anaerobic pathways. The substrate specificity is very diverse between enzymes within the same class, while the dependency on Mg 2+ , ATP and CoA as well as oxygen insensitivity are characteristics shared by the whole enzyme-class. Some organisms employ the same aryl-CoA ligase when growing aerobically and anaerobically, while others induce different enzymes depending on the environmental conditions. Aryl-CoA ligases can be divided into two major groups, benzoate:CoA ligase-like enzymes and phenylacetate:CoA ligase-like enzymes. They are widely distributed between the phylogenetic clades of the ANL superfamily and show closer relations within the subfamilies than to other aryl-CoA ligases. This, together with residual CoA-ligase activity in various other enzymes of the ANL superfamily, leads to the conclusion that CoA ligases might be the ancestral proteins from which all other ANL superfamily enzymes developed.

A modular two yeast species secretion system for the production and preparative application of unspecific peroxygenases

Fungal unspecific peroxygenases (UPOs) represent an enzyme class catalysing versatile oxyfunctionalisation reactions on a broad substrate scope. They are occurring as secreted, glycosylated proteins bearing a haem-thiolate active site and rely on hydrogen peroxide as the oxygen source. However, their heterologous production in a fast-growing organism suitable for high throughput screening has only succeeded once—enabled by an intensive directed evolution campaign. We developed and applied a modular Golden Gate-based secretion system, allowing the first production of four active UPOs in yeast, their one-step purification and application in an enantioselective conversion on a preparative scale. The Golden Gate setup was designed to be universally applicable and consists of the three module types: i) signal peptides for secretion, ii) UPO genes, and iii) protein tags for purification and split-GFP detection. The modular episomal system is suitable for use in Saccharomyces cerevisiae and was transferred to episomal and chromosomally integrated expression cassettes in Pichia pastoris. Shake flask productions in Pichia pastoris yielded up to 24 mg/L secreted UPO enzyme, which was employed for the preparative scale conversion of a phenethylamine derivative reaching 98.6 % ee. Our results demonstrate a rapid, modular yeast secretion workflow of UPOs yielding preparative scale enantioselective biotransformations.

Experimental investigation of enzyme functional annotations reveals extensive annotation error

Only a small fraction of genes deposited to databases has been experimentally characterised. The majority of proteins have their function assigned automatically, which can result in erroneous annotations. The reliability of current annotations in public databases is largely unknown; experimental attempts to validate the accuracy of existing annotations are lacking. In this study we performed an overview of functional annotations to the BRENDA enzyme database. We first applied a high-throughput experimental platform to verify functional annotations to an enzyme class of S-2-hydroxyacid oxidases (EC 1.1.3.15). We chose 122 representative sequences of the class and screened them for their predicted function. Based on the experimental results, predicted domain architecture and similarity to previously characterised S-2-hydroxyacid oxidases, we inferred that at least 78% of sequences in the enzyme class are misannotated. We experimentally confirmed four alternative activities among the misannotated sequences and showed that misannotation in the enzyme class increased over time. Finally, we performed a computational analysis of annotations to all enzyme classes in BRENDA database, and showed that nearly 18% of all sequences are annotated to an enzyme class while sharing no similarity to experimentally characterised representatives. We showed that even well-studied enzyme classes of industrial relevance are affected by the problem of functional misannotation.

ABLE: Attention Based Learning for Enzyme Classification

Classifying proteins into their respective enzyme class is an interesting question for researchers for a variety of reasons. The open source Protein Data Bank (PDB) contains more than 1,60,000 structures, with more being added everyday. This paper proposes an attention-based bidirectional-LSTM model (ABLE) trained on oversampled data generated by SMOTE to analyse and classify a protein into one of the six enzyme classes or a negative class using only the primary structure of the protein described as a string by the FASTA sequence as an input. We achieve the highest F1-score of 0.834 using our proposed model on a dataset of proteins from the PDB. We baseline our model against seventeen other machine learning and deep learning models, including CNN, LSTM, BILSTM and GRU. We perform extensive experimentation and statistical testing to corroborate our results.

Human 2-oxoglutarate-dependent oxygenases: nutrient sensors, stress responders, and disease mediators

Fe(II)/2-oxoglutarate (2OG)-dependent oxygenases are a conserved enzyme class that catalyse diverse oxidative reactions across nature. In humans, these enzymes hydroxylate a broad range of biological substrates including DNA, RNA, proteins and some metabolic intermediates. Correspondingly, members of the 2OG-dependent oxygenase superfamily have been linked to fundamental biological processes, and found dysregulated in numerous human diseases. Such findings have stimulated efforts to understand both the biochemical activities and cellular functions of these enzymes, as many have been poorly studied. In this review, we focus on human 2OG-dependent oxygenases catalysing the hydroxylation of protein and polynucleotide substrates. We discuss their modulation by changes in the cellular microenvironment, particularly with respect to oxygen, iron, 2OG and the effects of oncometabolites. We also describe emerging evidence that these enzymes are responsive to cellular stresses including hypoxia and DNA damage. Moreover, we examine how dysregulation of 2OG-dependent oxygenases is associated with human disease, and the apparent paradoxical role for some of these enzymes during cancer development. Finally, we discuss some of the challenges associated with assigning biochemical activities and cellular functions to 2OG-dependent oxygenases.