Is the Association of the Rare rs35667974 IFIH1 Gene Polymorphism With Autoimmune Diseases a Case of RNA Epigenetics?

Interferon induced with helicase C domain-containing protein 1 (IFIH1) gene encodes a cytoplasmic RNA helicase otherwise known as melanoma differentiation-associated 5 (MDA5), a RIG-1-like RNA helicase that recognizes viral RNA and is involved in innate immunity through recognition of viral RNA. Upon binding to double-stranded (ds) RNA, MDA5 forms a filamentous assembly along the length of dsRNA and utilizes molecular signatures to discriminate self, versus non-self on the basis of dsRNA length and methylation. Its missense variant rs35667974 is protective for type 1 diabetes, psoriasis, and psoriatic arthritis, but is also found to be associated with an increased risk for ankylosing spondylitis, Crohn's disease, and ulcerative colitis. To gain insight into the complex role of this variant we performed a structural analysis of MDA5 in complex with dsRNA using molecular dynamics simulations. Our data suggest that while the Ile923Val mutation of the rs35667974 variant does not affect binding to native dsRNA significantly, it displays a destabilizing effect in the presence of 2'-O uridine methylation. Thus, the presence of 2'-O-methylation at the dsRNA introduces a sensing signature that leads to selective reduction of the overall MDA catalytic activity. This study represents an evaluation of the role of the shared rs35667974 variant of autoimmune locus IFIH1, reported to lead to selectively reduced catalytic activity of the modified MDA5 phenotype and, as a consequence, reduced negative feedback on cytokine and chemokine signaling and selectively protection against autoimmunity.

Human Breast Milk Omics and Neurodevelopment.

Breast milk is the ideal food for the premature and mature babies and has undoubtedly immediate and ultimate benefits. Among other things, it protects against infections, reduces the risk of necrotizing enterocolitis and retinopathy of the premature babies, improves neurodevelopmental outcome, and reduces the risk of obesity and metabolic syndrome later in life. In the present study, breast milk will be studied with all the available omics technologies. More specifically, functional genomics, comparative genomics, transcriptomics, sequencing, proteomics, and metabolomics will be performed. The above results and this multidimensional information will be coordinated under the framework of a holistic approach of systems biology and bioinformatic analysis. Important IncRNAs and protein molecules will be validated as candidate biomarkers in exosomes of a larger group of breast milk and blood/serum samples. Validated ncRNAs/proteins will be analyzed in exudates of breast milk and bovine, goat, and sheep milk to explore new ways to improve milk synthesis. Expression of ncRNAs, unlike mRNAs, is a direct indicator of their functional presence. The information to be generated in this study will be analyzed by mining and data combining techniques and algorithms. After defining breast milk molecular fingerprinting, an attempt will be made to enhance the commercial product. The benefits of breast milk are attributed to its various components, including nutrients, hormones, growth factors, immune cells, antibodies, cytokines, antimicrobial peptides, and extracellular vesicles.

Endosymbiosis in Nature and the Gut-Brain Axis.

Exploring the origin of plastids is an interesting theme for study because it enhances our knowledge of the basis of photosynthesis in flora. Plastids, which are organelles, are actually the major sites of photosynthesis in eukaryotic cells. Plastids are also every chloroplast which contains cytoplasmic organelles, enabling the harvesting and conversion of light and carbon dioxide into food and energy. Plastids can be found in eukaryotic cells, and according to their structure in their membrane, they can be separated in primary (which can be found in most algae and plants) and secondary plastids (which can be found in plankton).

Computational Methods for Anticancer Drug Discovery; The MCT4 Paradigm.

Modern anticancer research has employed advanced computational techniques and artificial intelligence methods for drug discovery and development, along with the massive amount of generated clinical and in silico data over the last decades. Diverse computational techniques and state-of-the-art algorithms are being developed to enhance traditional Rational Drug Design pipelines and achieve cost-efficient and successful anticancer candidates to promote human health. Towards this direction, we have developed a pharmacophore- based drug design approach against MCT4, a member of the monocarboxylate transporter family (MCT), which is the main carrier of lactate across the membrane and highly involved in cancer cell metabolism. Specifically, MCT4 is a promising target for therapeutic strategies as it overexpresses in glycolytic tumors, and its inhibition has shown promising anticancer effects. Due to the lack of experimentally determined structure, we have elucidated the key features of the protein through an in silico drug design strategy, including for molecular modelling, molecular dynamics, and pharmacophore elucidation, towards the identification of specific inhibitors as a novel anti-cancer strategy.

Semantic and Population Analysis of the Genetic Targets Related to COVID-19 and Its Association with Genes and Diseases.

SARS-CoV-2 is a coronavirus responsible for one of the most serious, modern worldwide pandemics, with lasting and multifaceted effects. By late 2021, SARS-CoV-2 has infected more than 180 million people and has killed more than 3 million. The virus gains entrance to human cells through binding to ACE2 via its surface spike protein and causes a complex disease of the respiratory system, termed COVID-19. Vaccination efforts are being made to hinder the viral spread, and therapeutics are currently under development. Toward this goal, scientific attention is shifting toward variants and SNPs that affect factors of the disease such as susceptibility and severity. This genomic grammar, tightly related to the dark part of our genome, can be explored through the use of modern methods such as natural language processing. We present a semantic analysis of SARS-CoV-2-related publications, which yielded a repertoire of SNPs, genes, and disease ontologies. Population data from the 1000 Genomes Project were subsequently integrated into the pipeline. Data mining approaches of this scale have the potential to elucidate the complex interaction between COVID-19 pathogenesis and host genetic variation; the resulting knowledge can facilitate the management of high-risk groups and aid the efforts toward precision medicine.

ADRA2B and HTR1A: An Updated Study of the Biogenic Amine Receptors Reveals Novel Conserved Motifs Which Play Key Role in Mental Disorders.

Mental disorders are strongly connected with several psychiatric conditions including depression, bipolar disorder, schizophrenia, eating disorder, and suicides. There are many biological conditions and pathways that define these complicated illnesses. For example, eating disorders are complex mental health conditions that require the intervention of geneticists, psychiatrists, and medical experts in order to alleviate their symptoms. A patient with suicidal ideation should first be identified and consequently monitored by a similar team of specialists. Both genetics and epigenetics can shed light on eating disorders and suicides as they are found in the main core of such investigations. In the present study, an analysis has been performed on two specific members of the GPCR family toward drawing conclusions regarding their functionality and implementation in mental disorders. Specifically, evolutionary and structural studies on the adrenoceptor alpha 2b (ADRA2B) and the 5-hydroxytryptamine receptor 1A (HTR1A) have been carried out. Both receptors are classified in the biogenic amine receptors sub-cluster of the GPCRs and have been connected in many studies with mental diseases and malnutrition conditions. The major goal of this study is the investigation of conserved motifs among biogenic amine receptors that play an important role in this family signaling pathway, through an updated evolutionary analysis and the correlation of this information with the structural features of the HTR1A and ADRA2B. Furthermore, the structural comparison of ADRA2B, HTR1A, and other members of GPCRs related to mental disorders is performed.

A Genomic Study of the Japanese Population Focusing on the Glucocorticoid Receptor Interactome Highlights Distinct Genetic Characteristics Associated with Stress Response.

All living organisms have been programmed to maintain a complex inner equilibrium called homeostasis, despite numerous adversities during their lifespan. Any threatening or perceived as such stimuli for homeostasis is termed a stressor, and a highly conserved response system called the stress response system has been developed to cope with these stimuli and maintain or reinstate homeostasis. The glucocorticoid receptor, a transcription factor belonging to the nuclear receptors protein superfamily, has a major role in the stress response system, and research on its interactome may provide novel information regarding the mechanisms underlying homeostasis maintenance. A list of 149 autosomal genes that have an essential role in GR function or are prime examples of GRE-containing genes was composed in order to gain a comprehensive view of the GR interactome. A search for SNPs on those particular genes was conducted on a dataset of 3554 Japanese individuals, with mentioned polymorphisms being annotated with relevant information from the ClinVar, LitVar, and dbSNP databases. Forty-two SNPs of interest and their genomic locations were identified. These SNPs have been associated with drug metabolism and neuropsychiatric, metabolic, and immune system disorders, while most of them were located in intronic regions. The frequencies of those SNPs were later compared with a dataset consisting of 1465 Korean individuals in order to find population-specific characteristics based on some of the identified SNPs of interest. The results highlighted.that rs1043618 frequencies were different in the two populations, with mentioned polymorphism having a potential role in chronic obstructive pulmonary disease in response to environmental stressors. This SNP is located in the HSPA1A gene, which codes for an essential GR co-chaperone, and such information showcases that similar gene may be novel genomic targets for managing or combatting stress-related pathologies.

An Updated Evolutionary and Structural Study of TBK1 Reveals Highly Conserved Motifs as Potential Pharmacological Targets in Neurodegenerative Diseases.

TANK-binding kinase 1 protein (TBK1) is a kinase that belongs to the IκB (IKK) family. TBK1, also known as T2K, FTDALS4, NAK, IIAE8, and NF-κB, is responsible for the phosphorylation of the amino acid residues, serine and threonine. This enzyme is involved in various key biological processes, including interferon activation and production, homeostasis, cell growth, autophagy, insulin production, and the regulation of TNF-α, IFN-ß, and IL-6. Mutations in the TBK1 gene alter the protein's normal function and may lead to an array of pathological conditions, including disorders of the central nervous system. The present study sought to elucidate the role of the TBK1 protein in amyotrophic lateral sclerosis (ALS), a human neurodegenerative disorder. A broad evolutionary and phylogenetic analysis of TBK1 was performed across numerous organisms to distinguish conserved regions important for the protein's function. Subsequently, mutations and SNPs were explored, and their potential effect on the enzyme's function was investigated. These analytical steps, in combination with the study of the secondary, tertiary, and quaternary structure of TBK1, enabled the identification of conserved motifs, which can function as novel pharmacological targets and inform therapeutic strategies for amyotrophic lateral sclerosis.

DRDs and Brain-Derived Neurotrophic Factor Share a Common Therapeutic Ground: A Novel Bioinformatic Approach Sheds New Light Toward Pharmacological Treatment of Cognitive and Behavioral Disorders.

Cognitive and behavioral disorders are subgroups of mental health disorders. Both cognitive and behavioral disorders can occur in people of different ages, genders, and social backgrounds, and they can cause serious physical, mental, or social problems. The risk factors for these diseases are numerous, with a range from genetic and epigenetic factors to physical factors. In most cases, the appearance of such a disorder in an individual is a combination of his genetic profile and environmental stimuli. To date, researchers have not been able to identify the specific causes of these disorders, and as such, there is urgent need for innovative study approaches. The aim of the present study was to identify the genetic factors which seem to be more directly responsible for the occurrence of a cognitive and/or behavioral disorder. More specifically, through bioinformatics tools and software as well as analytical methods such as systemic data and text mining, semantic analysis, and scoring functions, we extracted the most relevant single nucleotide polymorphisms (SNPs) and genes connected to these disorders. All the extracted SNPs were filtered, annotated, classified, and evaluated in order to create the "genomic grammar" of these diseases. The identified SNPs guided the search for top suspected genetic factors, dopamine receptors D and neurotrophic factor BDNF, for which regulatory networks were built. The identification of the "genomic grammar" and underlying factors connected to cognitive and behavioral disorders can aid in the successful disease profiling and the establishment of novel pharmacological targets and provide the basis for personalized medicine, which takes into account the patient's genetic background as well as epigenetic factors.

Structure-Based Discovery of Receptor Activator of Nuclear Factor-κB Ligand (RANKL)-Induced Osteoclastogenesis Inhibitors.

Receptor activator of nuclear factor-κB ligand (RANKL) has been actively pursued as a therapeutic target for osteoporosis, given that RANKL is the master mediator of bone resorption as it promotes osteoclast differentiation, activity and survival. We employed a structure-based virtual screening approach comprising two stages of experimental evaluation and identified 11 commercially available compounds that displayed dose-dependent inhibition of osteoclastogenesis. Their inhibitory effects were quantified through TRAP activity at the low micromolar range (IC50 < 5 µΜ), but more importantly, 3 compounds displayed very low toxicity (LC50 > 100 µΜ). We also assessed the potential of an N-(1-aryl-1H-indol-5-yl)aryl-sulfonamide scaffold that was based on the structure of a hit compound, through synthesis of 30 derivatives. Their evaluation revealed 4 additional hits that inhibited osteoclastogenesis at low micromolar concentrations; however, cellular toxicity concerns preclude their further development. Taken together with the structure-activity relationships provided by the hit compounds, our study revealed potent inhibitors of RANKL-induced osteoclastogenesis of high therapeutic index, which bear diverse scaffolds that can be employed in hit-to-lead optimization for the development of therapeutics against osteolytic diseases.

Increased risk of rheumatoid arthritis in patients with endometriosis: genetic aspects.

RA is an inflammatory joint disease of an autoimmune nature, with a complex mode of inheritance characterized by chronic and destructive inflammation in the peripheral joints of the hands and feet and irreversible disability. This disorder occurs more often in women, and reproductive and hormonal factors have been shown to be related to increased risk. Endometriosis is a chronic, complex, oestrogen-dependent and progressive gynaecological disorder characterized by the growth of endometrial tissue outside the uterine cavity. Thus far, substantial abnormalities in the immune system of women with endometriosis have been demonstrated. Epidemiological data have suggested a link between endometriosis and the risk of incident RA. The similarities between molecular and cellular pathways of endometriosis and RA may implicate a partially shared genetic background. In this review we present an overview of the shared genetic factors known thus far that are associated with the development of both disorders.

A Holistic Evolutionary and 3D Pharmacophore Modelling Study Provides Insights into the Metabolism, Function, and Substrate Selectivity of the Human Monocarboxylate Transporter 4 (hMCT4).

Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy.

Molecular and clinical spectrum of four pedigrees of TRAPS in Greece: results from a national referral center.

OBJECTIVE: Tumor necrosis factor receptor-associated periodic syndrome (TRAPS) is a rare autosomal dominantly inherited autoinflammatory disease caused by mutations of the TNFRSF1A gene. To address the association between TNFRSF1A mutations and clinical phenotype, we analyzed four pedigrees of TRAPS patients. METHODS: Four Greek patients with TRAPS-like clinical features were screened for TNFRSF1A mutations by sequencing exons 2, 3 and 4. Following positive testing, twenty-two members of their families were also genetically and clinically screened. RESULTS: Twenty-six members of four unrelated Greek families were investigated. The C73Y (c.305G>A) mutation of the TNFRSF1A gene was identified in five patients, with two of the five carrying a concomitant R92Q variation. We also identified seven C73W (c.306C>G), two T50M (c.236C>T) and seven R92Q (c.362G>A) carriers. Symptoms varied and the C73Y, C73W and T50M mutations were associated with the most severe clinical manifestations. The R92Q phenotype ranged from asymptomatic to mild disease. Molecular modelling linked pathogenicity with aberrant TNFRSF1A disulphide bond formation. CONCLUSION: In this first pedigree analysis of TRAPS in Greece, we identified the rare C73Y TNFRSF1A mutation. A wide clinical spectrum was observed with the C73Y, C73W and T50M mutations that affect TNFRSF1A disulphide bonds and are associated with worse symptoms.

Identification and characterization of a rare variant in apolipoprotein A-IV, p.(V336M), and evaluation of HDL functionality in a Greek cohort with extreme HDL cholesterol levels.

High-Density Lipoprotein cholesterol (HDL-C) levels do not correlate well with Coronary Artery Disease (CAD) risk, while HDL functionality affects atherogenesis and is a better prognostic marker for CAD. Often, the extreme HDL-C levels have a multigenic origin. Here, we searched for single-nucleotide polymorphisms (SNPs) in ten genes of HDL metabolism in a Greek cohort with very low (<10th percentile, n = 13) or very high (>90th percentile, n = 21) HDL-C. We also evaluated the association between HDL-C levels, HDL functionality (anti-oxidant capacity) and CAD in the subjects of this cohort. Individuals with low HDL-C levels had higher triglyceride levels, lower apoA-I levels, decreased HDL anti-oxidant capacity and higher incidence of CAD compared with individuals with control or high HDL-C levels. With next generation sequencing we identified 18 exonic SNPs in 6 genes of HDL metabolism and for selected amino acid changes we performed computer-aided structural analysis and modeling. A previously uncharacterized rare apolipoprotein A-IV variant, apoA-IV [V336M], present in a subject with low HDL-C (14 mg/dL) and CAD, was expressed in recombinant form and structurally and functionally characterized. ApoA-IV [V336M] had similar α-helical content to WT apoA-IV but displayed a small thermodynamic stabilization by chemical unfolding analysis. ApoA-IV [V336M] was able to associate with phospholipids but presented reduced kinetics compared to WT apoA-IV. Overall, we identified a rare apoA-IV variant in a subject with low HDL levels and CAD with altered biophysical and phospholipid binding properties and showed that subjects with very low HDL-C presented with HDL dysfunction and higher incidence of CAD in a Greek cohort.

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.

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.

Nicotinic Cholinergic System and COVID-19: In Silico Identification of an Interaction between SARS-CoV-2 and Nicotinic Receptors with Potential Therapeutic Targeting Implications.

While SARS-CoV-2 uses angiotensin converting enzyme 2 (ACE2) as the receptor for cell entry, it is important to examine other potential interactions between the virus and other cell receptors. Based on the clinical observation of low prevalence of smoking among hospitalized COVID-19 patients, we examined and identified a "toxin-like" amino acid (aa) sequence in the Receptor Binding Domain of the Spike Glycoprotein of SARS-CoV-2 (aa 375-390), which is homologous to a sequence of the Neurotoxin homolog NL1, one of the many snake venom toxins that are known to interact with nicotinic acetylcholine receptors (nAChRs). We present the 3D structural location of this "toxin-like" sequence on the Spike Glycoprotein and the superposition of the modelled structure of the Neurotoxin homolog NL1 and the SARS-CoV-2 Spike Glycoprotein. We also performed computational molecular modelling and docking experiments using 3D structures of the SARS-CoV-2 Spike Glycoprotein and the extracellular domain of the nAChR α9 subunit. We identified a main interaction between the aa 381-386 of the SARS-CoV-2 Spike Glycoprotein and the aa 189-192 of the extracellular domain of the nAChR α9 subunit, a region which forms the core of the "toxin-binding site" of the nAChRs. The mode of interaction is very similar to the interaction between the α9 nAChR and α-bungarotoxin. A similar interaction was observed between the pentameric α7 AChR chimera and SARS-CoV-2 Spike Glycoprotein. The findings raise the possibility that SARS-CoV-2 may interact with nAChRs, supporting the hypothesis of dysregulation of the nicotinic cholinergic system being implicated in the pathophysiology of COVID-19. Nicotine and other nicotinic cholinergic agonists may protect nAChRs and thus have therapeutic value in COVID-19 patients.

Insights on the alteration of functionality of a tyrosine kinase 2 variant: a molecular dynamics study.

Motivation: The tyrosine kinase 2 protein (Tyk2), encoded by the TYK2 gene, has a crucial role in signal transduction and the pathogenesis of many diseases. A single nucleotide polymorphism of the TYK2 gene, SNP rs34536443, is of major importance, since it has been shown to confer protection against various, mainly, autoimmune diseases. This polymorphism results in a Pro to Ala change at amino acid position 1104 of the encoded Tyk2 protein that affects its enzymatic activity. However, the details of the underlined mechanism are unknown. To address this issue, in this study, we used molecular dynamics simulations on the kinase domains of both wild type and variant Tyk2 protein. Results: Our MD results provided information, at atomic level, on the consequences of the Pro1104 to Ala substitution on the structure and dynamics of the kinase domain of Tyk2 and suggested reduced enzymatic activity of the resulting protein variant due to stabilization of inactive conformations, thus adding to knowledge towards the elucidation of the protection mechanism against autoimmune diseases associated with this point mutation.

Structures of the Peptidoglycan N-Acetylglucosamine Deacetylase Bc1974 and Its Complexes with Zinc Metalloenzyme Inhibitors.

The cell wall peptidoglycan is recognized as a primary target of the innate immune system, and usually its disintegration results in bacterial lysis. Bacillus cereus, a close relative of the highly virulent Bacillus anthracis, contains 10 polysaccharide deacetylases. Among these, the peptidoglycan N-acetylglucosamine deacetylase Bc1974 is the highest homologue to the Bacillus anthracis Ba1977 that is required for full virulence and is involved in resistance to the host's lysozyme. These metalloenzymes belong to the carbohydrate esterase family 4 (CE4) and are attractive targets for the development of new anti-infective agents. Herein we report the first X-ray crystal structures of the NodB domain of Bc1974, the conserved catalytic core of CE4s, in the unliganded form and in complex with four known metalloenzyme inhibitors and two amino acid hydroxamates that target the active site metal. These structures revealed the presence of two conformational states of a catalytic loop known as motif-4 (MT4), which were not observed previously for peptidoglycan deacetylases, but were recently shown in the structure of a Vibrio clolerae chitin deacetylase. By employing molecular docking of a substrate model, we describe a catalytic mechanism that probably involves initial binding of the substrate in a receptive, more open state of MT4 and optimal catalytic activity in the closed state of MT4, consistent with the previous observations. The ligand-bound structures presented here, in addition to the five Bc1974 inhibitors identified, provide a valuable basis for the design of antibacterial agents that target the peptidoglycan deacetylase Ba1977.