Kinetic and in silico analysis of the slow-binding inhibition of human poly(A)-specific ribonuclease (PARN) by novel nucleoside analogues

Quantitative Biochemical Analysis of Deadenylase Enzymes Using Fluorescence and Chemiluminescence-Based Assays

Deadenylase enzymes play a key role in mRNA degradation and RNA processing. In this chapter, we describe two activity assays for the quantitative biochemical analysis of deadenylase enzymes, which can easily be adapted for other nuclease enzymes. The assays use distinct principles of detection, which are based on differential annealing of a probe complementary to the substrate RNA or detection of adenosine monophosphate (AMP). The assays are sensitive, flexible, and can be used in low-throughput tube-based formats and 96-well or 384-well plate formats. The assays rely on plate reader detection and can be carried out using manual pipetting or robotic liquid handling equipment. In addition to two activity assays, we describe differential scanning fluorimetry (thermal shift assay) as a complementary assay that allows the direct characterization of ligand binding to deadenylase enzymes. The assays can be useful for the characterization of deadenylase variants and are particularly suitable for the discovery and development of small-molecule inhibitors of deadenylase enzymes.

Identification of PARN nuclease activity inhibitors by computational-based docking and high-throughput screening

Poly(A)-specific ribonuclease (PARN) is a 3'-exoribonuclease that removes poly(A) tails from the 3' end of RNAs. PARN is known to deadenylate some ncRNAs, including hTR, Y RNAs, and some miRNAs and thereby enhance their stability by limiting the access of 3' to 5' exonucleases recruited by oligo(A) tails. Several PARN-regulated miRNAs target p53 mRNA, and PARN knockdown leads to an increase of p53 protein levels in human cells. Thus, PARN inhibitors might be used to induce p53 levels in some human tumors and act as a therapeutic strategy to treat cancers caused by repressed p53 protein. Herein, we used computational-based molecular docking and high-throughput screening (HTS) to identify small molecule inhibitors of PARN. Validation with in vitro and cell-based assays, identified 4 compounds, including 3 novel compounds and pyrimidopyrimidin-2-one GNF-7, previously shown to be a Bcr-Abl inhibitor, as PARN inhibitors. These inhibitors can be used as tool compounds and as lead compounds for the development of improved PARN inhibitors.

Epitranscriptomics of cardiovascular diseases (Review)

RNA modifications have recently become the focus of attention due to their extensive regulatory effects in a vast array of cellular networks and signaling pathways. Just as epigenetics is responsible for the imprinting of environmental conditions on a genetic level, epitranscriptomics follows the same principle at the RNA level, but in a more dynamic and sensitive manner. Nevertheless, its impact in the field of cardiovascular disease (CVD) remains largely unexplored. CVD and its associated pathologies remain the leading cause of death in Western populations due to the limited regenerative capacity of the heart. As such, maintenance of cardiac homeostasis is paramount for its physiological function and its capacity to respond to environmental stimuli. In this context, epitranscriptomic modifications offer a novel and promising therapeutic avenue, based on the fine‑tuning of regulatory cascades, necessary for cardiac function. This review aimed to provide an overview of the most recent findings of key epitranscriptomic modifications in both coding and non‑coding RNAs. Additionally, the methods used for their detection and important associations with genetic variations in the context of CVD were summarized. Current knowledge on cardiac epitranscriptomics, albeit limited still, indicates that the impact of epitranscriptomic editing in the heart, in both physiological and pathological conditions, holds untapped potential for the development of novel targeted therapeutic approaches in a dynamic manner.

Drugena: A Fully Automated Immunoinformatics Platform for the Design of Antibody-Drug Conjugates Against Neurodegenerative Diseases

Antibodies are proteins that are the first line of defense in the adaptive immune response of vertebrates. Thereby, they are involved in a multitude of biochemical mechanisms and clinical manifestations with significant medical interest, such as autoimmunity, the regulation of infection, and cancer. An emerging field in antibody science that is of huge medicinal interest is the development of novel antibody-interacting drugs. Such entities are the antibody-drug conjugates (ADCs), which are a new type of targeted therapy, which consist of an antibody linked to a payload drug. Overall, the underlying principle of ADCs is the discerning delivery of a drug to a target, hoping to increase the potency of the original drug. Drugena suite is a pioneering platform that employs state-of-the-art computational biology methods in the fight against neurodegenerative diseases using ADCs. Drugena encompasses an up-to-date structural database of specialized antibodies for neurological disorders and the NCI database with over 96 million entities for the in silico development of ADCs. The pipeline of the Drugena suite has been divided into several steps and modules that are closely related with a synergistic fashion under a user-friendly graphical user interface.

Structural Study of the DNA: Clock/Bmal1 Complex Provides Insights for the Role of Cortisol, hGR, and HPA Axis in Stress Management and Sleep Disorders

Herein, we deploy an in silico pipeline of structural bioinformatics, thermodynamics, and molecular dynamics to investigate the role of cortisol in circadian rhythms, biorhythms, stress response, and even sleep disorders. Our study shows that high concentrations of cortisol intercalate in the minor groove of DNA. This phenomenon widens the adjacent major grooves and provides the Clock/Bmal1 complex with more space to dock and interact with DNA. Then, the strong charges of cortisol pull the alpha helices of the Clock/Bmal1 complex and bend it inward, thus establishing stronger interactions and prolonged signaling. Our results indicate that elevated cortisol levels play an important role in stress, inflammation, and sleep disorders as a result of prolonged and stronger dsDNA - Clock/Bmal1 interactions.

Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties

Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas. Although several approaches have been proposed for antibody clustering, still no consensus has been reached. Numerous attempts use information from genes, protein sequences, 3D structures, and 3D surfaces in an effort to elucidate unknown action mechanisms directly related to their function and to either link them directly to diseases or drive the discovery of new medicines, such as antibody drug conjugates (ADC). Herein, we describe a new V domain antibody clustering method based on the comparison of the interaction sites between each antibody and its antigen. A more specific clustering analysis of the antibody's V domain was provided using deep learning and data mining techniques. The multidimensional information was extracted from the structural resolved antibodies when they were captured to interact with other proteins. The available 3D structures of protein antigen-antibody (Ag-Ab) interfaces contain information about how antibody V domains recognize antigens as well as about which amino acids are involved in the recognition. As such, the antibody surface holds information about antigens' folding that reside with the Ab-Ag interface residues and how they interact. In order to gain insight into the nature of such interactions, we propose a new simple philosophy to transform the conserved framework (fragment regions, complementarity-determining regions) of antibody V domain in a binary form using structural features of antibody-antigen interactions, toward identifying new antibody signatures in V domain binding activity. Finally, an advanced three-level hybrid classification scheme has been set for clustering antibodies in subgroups, which can combine the information from the protein sequences, the three-dimensional structures, and specific "key patterns" of recognized interactions. The clusters provide multilevel information about antibodies and antibody-antigen complexes.

Olive Oil Polyphenols in Neurodegenerative Pathologies

Neurodegenerative diseases lead to the death of nerve cells in the brain or the spinal cord. A wide range of diseases are included within the group of neurodegenerative disorders, with the most common ones being dementia, Alzheimer's, and Parkinson's diseases. Millions of older people are suffering from such pathologies. The global increase of life expectancy unavoidably leads to a consequent increase in the number of people who will be at some degree affected by neurodegenerative-related diseases. At this moment, there is no effective therapy or treatment that can reverse the loss of neurons. A growing number of studies highlight the value of the consumption of medical foods, and in particular olive oil, as one of the most important components of the Mediterranean diet. A diet based on extra virgin olive oil seems to contribute toward the lowering of risk of age-related pathologies due to high phenol concentration. The link of a polyphenol found in extra virgin olive oil, namely, tyrosol, with the protein tyrosinase, associated to Parkinson's disease is underlined as a paradigm of affiliation between polyphenols and neurodegenerative disorders.

DrugOn: a fully integrated pharmacophore modeling and structure optimization toolkit

During the past few years, pharmacophore modeling has become one of the key components in computer-aided drug design and in modern drug discovery. DrugOn is a fully interactive pipeline designed to exploit the advantages of modern programming and overcome the command line barrier with two friendly environments for the user (either novice or experienced in the field of Computer Aided Drug Design) to perform pharmacophore modeling through an efficient combination of the PharmACOphore, Gromacs, Ligbuilder and PDB2PQR suites. Our platform features a novel workflow that guides the user through each logical step of the iterative 3D structural optimization setup and drug design process. For the pharmacophore modeling we are focusing on either the characteristics of the receptor or the full molecular system, including a set of selected ligands. DrugOn can be freely downloaded from our dedicated server system at www.bioacademy.gr/bioinformatics/drugon/.

A fluorescence-based assay suitable for quantitative analysis of deadenylase enzyme activity

In eukaryotic cells, the shortening and removal of the poly(A) tail of cytoplasmic mRNA by deadenylase enzymes is a critical step in post-transcriptional gene regulation. The ribonuclease activity of deadenylase enzymes is attributed to either a DEDD (Asp-Glu-Asp-Asp) or an endonuclease–exonuclease–phosphatase domain. Both domains require the presence of two Mg²⁺ ions in the active site. To facilitate the biochemical analysis of deadenylase enzymes, we have developed a fluorescence-based deadenylase assay. The assay is based on end-point measurement, suitable for quantitative analysis and can be adapted for 96- and 384-well microplate formats. We demonstrate the utility of the assay by screening a chemical compound library, resulting in the identification of non-nucleoside inhibitors of the Caf1/CNOT7 enzyme, a catalytic subunit of the Ccr4–Not deadenylase complex. These compounds may be useful tools for the biochemical analysis of the Caf1/CNOT7 deadenylase subunit of the Ccr4–Not complex and indicate the feasibility of developing selective inhibitors of deadenylase enzymes using the fluorescence-based assay.

Distinct roles of the R3H and RRM domains in poly(A)-specific ribonuclease structural integrity and catalysis

Deadenylases specifically catalyze the degradation of eukaryotic mRNA poly(A) tail in the 3'- to 5'-end direction with the release of 5'-AMP as the product. Among the deadenylase family, poly(A)-specific ribonuclease (PARN) is unique in its domain composition, which contains three potential RNA-binding domains: the catalytic nuclease domain, the R3H domain and the RRM domain. In this research, we investigated the roles of these RNA-binding domains by comparing the structural features and enzymatic properties of mutants lacking either one or two of the three RNA-binding domains. The results showed that the R3H domain had the ability to bind various oligonucleotides at the micromolar level with no oligo(A) specificity. The removal of the R3H domain dissociated PARN into monomers, which still possessed the RNA-binding ability and catalytic functions. Unlike the critical role of the RRM domain in PARN processivity, the removal of the R3H domain did not affect the catalytic pattern of PARN. Our results suggested that both R3H and RRM domains were essential for the high affinity of long poly(A) substrate, but the R3H domain did not contribute to the substrate recognition of PARN. Compared to the RRM domain, the R3H domain played a more important role in the structural integrity of the dimeric PARN. The multiple RNA-binding domain architecture endows PARN the property of highly efficient catalysis in a highly processive mode.

Kiss your tail goodbye: the role of PARN, Nocturnin, and Angel deadenylases in mRNA biology

PARN, Nocturnin and Angel are three of the multiple deadenylases that have been described in eukaryotic cells. While each of these enzymes appear to target poly(A) tails for shortening and influence RNA gene expression levels and quality control, the enzymes differ in terms of enzymatic mechanisms, regulation and biological impact. The goal of this review is to provide an in depth biochemical and biological perspective of the PARN, Nocturnin and Angel deadenylases. Understanding the shared and unique roles of these enzymes in cell biology will provide important insights into numerous aspects of the post-transcriptional control of gene expression. This article is part of a Special Issue entitled: RNA Decay mechanisms.

An integrated in silico approach to design specific inhibitors targeting human poly(a)-specific ribonuclease

Poly(A)-specific ribonuclease (PARN) is an exoribonuclease/deadenylase that degrades 3′-end poly(A) tails in almost all eukaryotic organisms. Much of the biochemical and structural information on PARN comes from the human enzyme. However, the existence of PARN all along the eukaryotic evolutionary ladder requires further and thorough investigation. Although the complete structure of the full-length human PARN, as well as several aspects of the catalytic mechanism still remain elusive, many previous studies indicate that PARN can be used as potent and promising anti-cancer target. In the present study, we attempt to complement the existing structural information on PARN with in-depth bioinformatics analyses, in order to get a hologram of the molecular evolution of PARNs active site. In an effort to draw an outline, which allows specific drug design targeting PARN, an unequivocally specific platform was designed for the development of selective modulators focusing on the unique structural and catalytic features of the enzyme. Extensive phylogenetic analysis based on all the publicly available genomes indicated a broad distribution for PARN across eukaryotic species and revealed structurally important amino acids which could be assigned as potentially strong contributors to the regulation of the catalytic mechanism of PARN. Based on the above, we propose a comprehensive in silico model for the PARN’s catalytic mechanism and moreover, we developed a 3D pharmacophore model, which was subsequently used for the introduction of DNP-poly(A) amphipathic substrate analog as a potential inhibitor of PARN. Indeed, biochemical analysis revealed that DNP-poly(A) inhibits PARN competitively. Our approach provides an efficient integrated platform for the rational design of pharmacophore models as well as novel modulators of PARN with therapeutic potential.