Dipeptidyl Peptidase Inhibition Enhances CD8 T Cell Recruitment and Activates Intrahepatic Inflammasome in a Murine Model of Hepatocellular Carcinoma

The mRNA expression of the dipeptidyl peptidase 4 (DPP4) gene family is highly upregulated in human hepatocellular carcinoma (HCC) and is associated with poor survival in HCC patients. Compounds that inhibit the DPP4 enzyme family, such as talabostat and ARI-4175, can mediate tumour regression by immune-mediated mechanisms that are believed to include NLRP1 activation. This study investigated the expression and activity of the DPP4 family during the development of HCC and evaluated the efficacy of ARI-4175 in the treatment of early HCC in mice. This first report on this enzyme family in HCC-bearing mice showed DPP9 upregulation in HCC, whereas intrahepatic DPP8/9 and DPP4 enzyme activity levels decreased with age. We demonstrated that ARI-4175 significantly lowered the total number of macroscopic liver nodules in these mice. In addition, ARI-4175 increased intrahepatic inflammatory cell infiltration, including CD8+ T cell numbers, into the HCC-bearing livers. Furthermore, ARI-4175 activated a critical component of the inflammasome pathway, caspase-1, in these HCC-bearing livers. This is the first evidence of caspase-1 activation by a pan-DPP inhibitor in the liver. Our data suggest that targeting the DPP4 enzyme family may be a novel and effective approach to promote anti-tumour immunity in HCC via caspase-1 activation.

Special Issue “APOBECs and Virus Restriction”

The apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) enzyme family in humans has 11 members with diverse functions in metabolism and immunity [...]

Lytic Polysaccharide Monooxygenases as Chitin-Specific Virulence Factors in Crayfish Plague

The oomycete pathogen Aphanomyces astaci, also known as “crayfish plague”, is an obligate fungal-like parasite of freshwater crustaceans and is considered responsible for the ongoing decline of native European crayfish populations. A. astaci is thought to secrete a wide array of effectors and enzymes that facilitate infection, however their molecular mechanisms have been poorly characterized. Here, we report the identification of AA15 lytic polysaccharide monooxygenases (LPMOs) as a new group of secreted virulence factors in A. astaci. We show that this enzyme family has greatly expanded in A. astaci compared to all other oomycetes, and that it may facilitate infection through oxidative degradation of crystalline chitin, the most abundant polysaccharide found in the crustacean exoskeleton. These findings reveal new roles for LPMOs in animal–pathogen interactions, and could help inform future strategies for the protection of farmed and endangered species.

Recent Advances in Kinase Drug Discovery Part I: The Editors’ Take

This special issue on Advances in Kinase Drug Discovery provides a selection of research articles and topical reviews covering all aspects of drug discovery targeting the phosphotransferase enzyme family [...]

Peptidyl-prolyl cis/trans isomerases in GtoPdb v.2021.2

Peptidyl-prolyl cis/trans isomerases (PPIases) are an enzyme family which catalyse the cis/trans isomerisation of proline peptide bonds to promote the folding and re-folding of peptides and proteins. Three subfamilies have been identified: cyclophilins, FK506-binding proteins and parvulins. Individual PPIases are overexpressed in a number of cancers [59], and family members have been targetted for immunosuppressant effects.

Machine learning models for classification tasks related to drug safety

In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015–2021). The study focuses only on classification models with large datasets (i.e. more than a thousand compounds). A comprehensive literature search and meta-analysis was carried out for nine different targets: hERG-mediated cardiotoxicity, blood–brain barrier penetration, permeability glycoprotein (P-gp) substrate/inhibitor, cytochrome P450 enzyme family, acute oral toxicity, mutagenicity, carcinogenicity, respiratory toxicity and irritation/corrosion. The comparison of the best classification models was targeted to reveal the differences between machine learning algorithms and modeling types, endpoint-specific performances, dataset sizes and the different validation protocols. Based on the evaluation of the data, we can say that tree-based algorithms are (still) dominating the field, with consensus modeling being an increasing trend in drug safety predictions. Although one can already find classification models with great performances to hERG-mediated cardiotoxicity and the isoenzymes of the cytochrome P450 enzyme family, these targets are still central to ADMET-related research efforts. Graphical abstract

The PARP Enzyme Family and the Hallmarks of Cancer Part 1. Cell Intrinsic Hallmarks

The 17-member poly (ADP-ribose) polymerase enzyme family, also known as the ADP-ribosyl transferase diphtheria toxin-like (ARTD) enzyme family, contains DNA damage-responsive and nonresponsive members. Only PARP1, 2, 5a, and 5b are capable of modifying their targets with poly ADP-ribose (PAR) polymers; the other PARP family members function as mono-ADP-ribosyl transferases. In the last decade, PARP1 has taken center stage in oncology treatments. New PARP inhibitors (PARPi) have been introduced for the targeted treatment of breast cancer 1 or 2 (BRCA1/2)-deficient ovarian and breast cancers, and this novel therapy represents the prototype of the synthetic lethality paradigm. Much less attention has been paid to other PARPs and their potential roles in cancer biology. In this review, we summarize the roles played by all PARP enzyme family members in six intrinsic hallmarks of cancer: uncontrolled proliferation, evasion of growth suppressors, cell death resistance, genome instability, reprogrammed energy metabolism, and escape from replicative senescence. In a companion paper, we will discuss the roles of PARP enzymes in cancer hallmarks related to cancer-host interactions, including angiogenesis, invasion and metastasis, evasion of the anticancer immune response, and tumor-promoting inflammation. While PARP1 is clearly involved in all ten cancer hallmarks, an increasing body of evidence supports the role of other PARPs in modifying these cancer hallmarks (e.g., PARP5a and 5b in replicative immortality and PARP2 in cancer metabolism). We also highlight controversies, open questions, and discuss prospects of recent developments related to the wide range of roles played by PARPs in cancer biology. Some of the summarized findings may explain resistance to PARPi therapy or highlight novel biological roles of PARPs that can be therapeutically exploited in novel anticancer treatment paradigms.

Thiamin-Diphosphate Enzymes Are an Ancient Family of Repeat Proteins

ABSTRACTA repeating sequence and structure pattern that is highly similar to the canonical cofactor binding motif has been identified in the thiamin-diphosphate dependent (ThDP) enzyme family. We have identified more than a thousand of these repeats in a non-redundant set (N = 58) of ThDP enzyme structures. The repeating element has a helix-turn-strand secondary structure which typically begins with an [G/A]{X(1,2)}[G/A] sequence motif with a typical length of 29 residues. The catalytically important diphosphate and aminopyrimidine interacting domains are comprised of a set of six of these repeats in a conserved architecture with a flavodoxin-like 213465 strand order. The canonical ThDP binding motif is the fourth repeat in the ThDP binding domain, while the conserved aminopyrimidine interacting glutamate is part of the second repeat in its domain. The third and fourth repeats form a contact between the functional domains, while the fifth repeat in the N-terminal domain forms an inter-chain contact. The conservation of these functional properties highlights the role of these repeats in the function and structure of this well-studied enzyme family and agrees with the principle of modular assembly in protein ancestry.

Peptidylarginine Deiminase (PAD) and Post-Translational Protein Deimination—Novel Insights into Alveolata Metabolism, Epigenetic Regulation and Host–Pathogen Interactions

The alveolates (Superphylum Alveolata) comprise a group of primarily single-celled eukaryotes that have adopted extremely diverse modes of nutrition, such as predation, photoautotrophy and parasitism. The alveolates consists of several major phyla including the apicomplexans, a large group of unicellular, spore forming obligate intracellular parasites, and chromerids, which are believed to be the phototrophic ancestors of the parasitic apicomplexans. Molecular pathways involved in Alveolata host–pathogen interactions, epigenetic regulation and metabolism in parasite development remain to be fully understood. Peptidylarginine deiminases (PADs) are a phylogenetically conserved enzyme family which causes post-translational protein deimination, affecting protein function through the conversion of arginine to citrulline in a wide range of target proteins, contributing to protein moonlighting in physiological and pathological processes. The identification of deiminated protein targets in alveolate parasites may therefore provide novel insight into pathogen survival and host-pathogen interactions. The current study assessed PAD homologues and deiminated protein profiles of two alveolate parasites, Piridium sociabile (Chromerida) and Merocystis kathae (Apicomplexa). Histological analysis verified strong cytoplasmic PAD expression in both Alveolates, detected deiminated proteins in nuclear and cytoplasmic compartments of the alveolate parasites and verified the presence of citrullinated histone H3 in Alveolata nucleus, indicating roles in epigenetic regulation. Histone H3 citrullination was also found significantly elevated in the host tissue, indicative of neutrophil extracellular trap formation, a host-defence mechanism against a range of pathogens, particularly those that are too large for phagocytosis. Proteomic analysis of deiminated proteins from both Alveolata identified GO and KEGG pathways strongly relating to metabolic and genetic regulation, with some species-specific differences between the apicomplexan and the chromerid. Our findings provide novel insights into roles for the conserved PAD/ADI enzyme family in the regulation of metabolic and epigenetic pathways in alveolate parasites, possibly also relating to their life cycle and host–pathogen interactions.

Functional Annotation of an Enzyme Family by Integrated Strategy Combining Bioinformatics with Microanalytical and Microfluidic Technologies

<p>Next-generation sequencing technologies enable doubling of the genomic databases every 2.5 years. Collected sequences represent a rich source of novel biocatalysts. However, the rate of accumulation of sequence data exceeds the rate of functional studies, calling for acceleration and miniaturization of biochemical assays. Here, we present an integrated platform employing bioinformatics, <a></a><a>microanalytics, </a>and microfluidics and its application for exploration of unmapped sequence space, using haloalkane dehalogenases as model enzymes. First, we employed bioinformatic analysis for identification of 2,905 putative dehalogenases and rational selection of 45 representative enzymes. Second, we expressed and experimentally characterized 24 enzymes showing sufficient solubility for microanalytical and microfluidic testing. Miniaturization increased the throughput to 20,000 reactions per day with 1000-fold lower protein consumption compared to conventional assays. A single run of the platform doubled dehalogenation toolbox of family members characterized over three decades. Importantly, the dehalogenase activities of nearly one-third of these novel biocatalysts far exceed that of most published HLDs. Two enzymes showed unusually narrow substrate specificity, never before reported for this enzyme family. The strategy is generally applicable to other enzyme families, paving the way towards the acceleration of the process of identification of novel biocatalysts for industrial applications but also for the collection of homogenous data for machine learning. The automated <i>in silico</i> workflow has been released as a user-friendly web-tool EnzymeMiner: https://loschmidt.chemi.muni.cz/enzymeminer/.</p>