The Expression of Allele Changes in NLRP3 (rs35829419) and IL-1β (+3954) Gene Polymorphisms in Periodontitis and Coronary Artery Disease

Computational approaches to investigate the relationship between periodontitis and cardiovascular diseases for precision medicine

Periodontitis is a highly prevalent inflammatory illness that leads to the destruction of tooth supporting tissue structures and has been associated with an increased risk of cardiovascular disease (CVD). Precision medicine, an emerging branch of medical treatment, aims can further improve current traditional treatment by personalizing care based on one's environment, genetic makeup, and lifestyle. Genomic databases have paved the way for precision medicine by elucidating the pathophysiology of complex, heritable diseases. Therefore, the investigation of novel periodontitis-linked genes associated with CVD will enhance our understanding of their linkage and related biochemical pathways for targeted therapies. In this article, we highlight possible mechanisms of actions connecting PD and CVD. Furthermore, we delve deeper into certain heritable inflammatory-associated pathways linking the two. The goal is to gather, compare, and assess high-quality scientific literature alongside genomic datasets that seek to establish a link between periodontitis and CVD. The scope is focused on the most up to date and authentic literature published within the last 10 years, indexed and available from PubMed Central, that analyzes periodontitis-associated genes linked to CVD. Based on the comparative analysis criteria, fifty-one genes associated with both periodontitis and CVD were identified and reported. The prevalence of genes associated with both CVD and periodontitis warrants investigation to assess the validity of a potential linkage between the pathophysiology of both diseases.

Identification of novel NLRP3 inhibitors as therapeutic options for epilepsy by machine learning-based virtual screening, molecular docking and biomolecular simulation studies

The NOD-Like Receptor Protein-3 (NLRP3) inflammasome is a key therapeutic target for the treatment of epilepsy and has been reported to regulate inflammation in several neurological diseases. In this study, a machine learning-based virtual screening strategy has investigated candidate active compounds that inhibit the NLRP3 inflammasome. As machine learning-based virtual screening has the potential to accurately predict protein-ligand binding and reduce false positives outcomes compared to traditional virtual screening. Briefly, classification models were created using Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) machine learning methods. To determine the most crucial features of a molecule's activity, feature selection was carried out. By utilizing 10-fold cross-validation, the created models were analyzed. Among the generated models, the RF model obtained the best results as compared to others. Therefore, the RF model was used as a screening tool against the large chemical databases. Molecular operating environment (MOE) and PyRx software's were applied for molecular docking. Also, using the Amber Tools program, molecular dynamics (MD) simulation of potent inhibitors was carried out. The results showed that the KNN, SVM, and RF accuracy was 0.911 %, 0.906 %, and 0.946 %, respectively. Moreover, the model has shown sensitivity of 0.82 %, 0.78 %, and 0.86 % and specificity of 0.95 %, 0.96 %, and 0.98 % respectively. By applying the model to the ZINC and South African databases, we identified 98 and 39 compounds, respectively, potentially possessing anti-NLRP3 activity. Also, a molecular docking analysis produced ten ZINC and seven South African compounds that has comparable binding affinities to the reference drug. Moreover, MD analysis of the two complexes revealed that the two compounds (ZINC000009601348 and SANC00225) form stable complexes with varying amounts of binding energy. The in-silico studies indicate that both compounds most likely display their inhibitory effect by inhibiting the NLRP3 protein.

Calprotectin and periostin levels in periodontitis patients with coronary artery disease

OBJECTIVE

The aim of the study was to assess the effect of non-surgical periodontal therapy (NSPT) on periodontal and cardiac parameters as well as on the expression of calprotectin and periostin levels in periodontitis patients with and without coronary artery disease (CAD).

METHODS

Ninety subjects were categorised into three groups: Group H: periodontally and systemically healthy subjects, Group P: stage III grade B periodontitis subjects with no associated systemic diseases and Group P + CAD: stage III grade B periodontitis subjects diagnosed with CAD. Demographic, periodontal and cardiac parameters were recorded at baseline (0 day) and on the 180th day after NSPT. Gingival crevicular fluid was collected from all participants at baseline (0 day) and after the 180th day. Calprotectin and periostin expression were reassessed.

RESULTS

A significant increase in the levels of calprotectin (34.05 ± 11.72) was seen at baseline in the P + CAD group, whereas on the contrary, a decreased periostin (1.59 ± 0.41) was also noted at baseline. The study also showed a significant improvement in periodontal and cardiac parameters on the 180th day following NSPT.

CONCLUSION

Detection of calprotectin and periostin expression in GCF samples could represent a link to the association of periodontitis and CAD.

Identification of new potent NLRP3 inhibitors by multi-level in-silico approaches

Nod-like receptor protein 3 (NLRP-3), is an intracellular sensor that is involved in inflammasome activation, and the aberrant expression of NLRP3 is responsible for diabetes mellitus, its complications, and many other inflammatory diseases. NLRP3 is considered a promising drug target for novel drug design. Here, a pharmacophore model was generated from the most potent inhibitor, and its validation was performed by the Gunner-Henry scoring method. The validated pharmacophore was used to screen selected compounds databases. As a result, 646 compounds were mapped on the pharmacophore model. After applying Lipinski's rule of five, 391 hits were obtained. All the hits were docked into the binding pocket of target protein. Based on docking scores and interactions with binding site residues, six compounds were selected potential hits. To check the stability of these compounds, 100 ns molecular dynamic (MD) simulations were performed. The RMSD, RMSF, DCCM and hydrogen bond analysis showed that all the six compounds formed stable complex with NLRP3. The binding free energy with the MM-PBSA approach suggested that electrostatic force, and van der Waals interactions, played a significant role in the binding pattern of these compounds. Thus, the outcomes of the current study could provide insights into the identification of new potential NLRP3 inflammasome inhibitors against diabetes and its related disorders.

Assessment of NLRP3 Gene Polymorphisms with Periodontitis as Compared with Healthy Periodontium in Iraqi Arabs Patients

OBJECTIVES

 The nod-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome regulates the maturation and release of the cytokines as well as the activation of caspase in response to danger signals derived from pathogenic infection, tissue damage, andmetabolic changes that have a role in the pathogenesis of different diseases as periodontitis. Yet, the susceptibility to this illness could be determined by population-based genetic differences. The aim of this study was to determine whether periodontitis in Arab populations from Iraq is correlated with NLRP3 gene polymorphisms and measure clinical periodontal parameters and investigate their association with genetic polymorphisms of the NLRP3.

MATERIALS AND METHODS

 The study sample consisted of 94 participants ranging from 30 to 55 years old, both males and females who fulfilled the study's criteria. The selected participants were divided into two groups: the periodontitis group (62 subjects) and the healthy control group (32 subjects). The examination of clinical periodontal parameters of all participants was carried out, followed by a collection of venous blood for NLRP3 genetic analysis using the polymerase chain reaction-sequencing technique.

RESULTS

 The genetic analysis of NLRP3 genotypes at four single nucleotide polymorphisms (SNPs) (rs10925024, rs4612666, rs34777555, and rs10754557), by Hardy-Weinberg equilibrium, identified nonsignificant differences in studied groups. The C-T genotype among periodontitis was significantly different from controls, while the C-C genotype among control was significantly different from periodontitis at NLRP3 rs10925024. Overall, there were 35 SNPs in the periodontitis group and 10 SNPs in the control group for rs10925024 with significant differences versus nonsignificant differences of the other SNPs between the studied groups. Clinical attachment loss and NLRP3 rs10925024 additionally demonstrated a significant positive correlation in the periodontitis subjects.

CONCLUSION

 The findings suggested that polymorphisms of the NLRP3 gene may have a role and increasing the genetic susceptibility to periodontal disease in Arabs Iraqi patients.