Theses (MSc. Molecular Medicine)

Objectives: To fabricate carbon quantum dots (CQDs) and evaluate its effects on structure and crystal orientation and mechanical, and antibacterial properties of enamel. Materials and Methods: Enamel specimens of 4 mm x 4 mm x 3 mm were cut from extracted teeth. study. CQDs were prepared using ammonium citrate and sodium hydroxide solution dialysed in deionised water. After microwave reaction, Teflon tubes were left in machine for 30 minutes to cool. Enamel block specimens were divided into 4 groups (salineS, *CQD0.1%-, **CQD0.2%-, ***CQD0.3%-, and *****CQD0.5%-) in each of the treatment solutions, soaking for about 2 weeks. X-ray diffraction analysis (XRD) was performed on enamel to determine density functional theory (DFT) calculations. Transmission electron microscopy (TEM) and zeta potentials (ζ) were performed for CQDs. After modification, enamel was evaluated using Raman mapping, TEM, and Xray diffraction (XRD) analysis. Mechanical and antibacterial properties were evaluated using atomic force microscopy and TEM/SEM. For statistical analysis, null hypothesis was set at p<0.05 probability level. Results: Discrepancies in peak position between experimental and theoretical XRD diffraction patterns are due to differences in calculated parameters of ***CQD0.3%- and ***CQD0.5%- groups bringing conformational changes. Zeta potential values were least for salineS and maximum for *****CQD0.5%-. **CQD0.2%- group exhibited reduced v₁PO₄³⁻ intensity, with *****CQD0.5%- demonstrating the highest. The groups, arranged by ascending intensity, are salineS <*CQD0.1%-, <**CQD0.2%-, <***CQD0.3%-, < *****CQD0.5%-. TEM indicated spherical carbon dots with increase in enamel lattice parameter relative to the HAP unit cell in *****CQD0.5%- groups. *****CQD0.5%- group had highest elastic modulus and nano hardness. Bond length and angles show higher significant measures in CQD groups. CQD groups demonstrated higher antibacterial activities engulfing bacteria.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterised by amyloid beta (Aβ) plaque deposition and chronic neuroinflammation. Emerging evidence implicate microglial activation via pattern recognition receptors, particularly dectin-1, as a driver of immune dysregulation in AD. Laminarin, a marine-derived β-glucan, exhibits antioxidant and immunomodulatory properties, however, its potential to modulate neuroimmune receptor interactions remains underexplored. This study aimed to investigate whether laminarin can alter the interaction between dectin-1 and Aβ using an in silico approach. The three-dimensional (3D) structure of human dectin-1 was retrieved from public databases and sequentially docked with Aβ and laminarin using ClusPro and AutoDock Vina, respectively. The resulting ternary complex was subjected to 300-nanosecond molecular dynamics (MD) simulations using GROMACS. Structural stability and conformational changes were assessed through root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF) and radius of gyration (Rg), while binding free energies were estimated using the MM-PBSA method. Results showed that laminarin bound adjacent to the Aβ interface on dectin-1 with moderate affinity (–6.0 kcal/mol). Suggesting a potential allosteric rather than competitive interaction. MD simulations revealed that the laminarin-bound system had a lower average RMSD (3.03 nm) and a more compact conformation than the dectin-1- Aβ (unbound) system (3.37 nm). RMSF analysis revealed increased flexibility in loop regions associated with dectin-1 activation. MM-PBSA results further indicated enhanced van der Waals contributions and reduced electrostatic contributions, upon laminarin binding, indicative of an allosteric stabilisation mechanism. These findings suggest that laminarin may stabilise the dectin- 1-Aβ complex through conformational modulation, potential altering microglial signalling and attenuating neuroinflammation in AD. The study provides computational evidence supporting the immunomodulatory potential of laminarin and highlights its relevance as a candidate for further experimental validation in AD. Keywords: Alzheimer’s disease, laminarin, Dectin-1, amyloid beta, molecular dynamics, MM-PBSA, neuroinflammation, in silico

Porphyromonas gingivalis is implicated in chronic periodontal disease and secretes virulence factors, including Porphyromonas gingivalis peptidylarginine deiminase (PPAD), which catalyzes the conversion of arginine to citrulline in proteins, leading to the production of autoantigens. These autoantigens are associated with autoimmune responses in rheumatoid arthritis (RA). Epidemiological studies suggest a link between periodontal disease and RA, highlighting the potential of PPAD inhibition as a therapeutic strategy [1,2]. The present study aims to identify potential inhibitors of PPAD through a combination of 2D ligand-based similarity search, molecular docking and clustering studies from approved drugs databases as well as structural features essential for the inhibitory activity against PPAD [2]. The study employed a ligand-based virtual screening (LBVS) approach, leveraging the SwissSimilarity web tool to perform 2D similarity searches [3]. Hit compounds identified from prior PPAD inhibitory activity studies, namely Flucytosine, Cl-Amidine, Cytarabine and Carmustine, served as query molecules for this process [5]. 15 hits with the highest similarity score under each fingerprinting method of respective query molecules were identified from the similarity search, which were subjected to molecular docking via Schrödinger Glide docking program to evaluate their binding interactions in the PPAD binding site and structural determinants [4]. 5 final hit compounds were found to have higher docking scores than that of dipeptide reference ligand (-4.913 kcal/mol) ranging between -5.487 kcal/mol to -7.076 kcal/mol. Additionally, ChemMine web tool was used to cluster compounds obtained from similarity search of respective query molecules by structural similarities. 4 out 5 final hit compounds identified from molecular docking studies were found clustered in the respective major cluster bin consisting of higher number of compounds with similar structures than the other cluster bins, thus suggesting the corresponding chemical motif that contributes to ligand recognition within the PPAD binding pocket [5]. It was generally found that structural features, particularly hydrogen bond acceptors with electronegative oxygen atoms or nitrogen atoms, aromatic ring or heterocycle, cyclic ring with hydroxyl groups are essential for the inhibition of PPAD. Indeed, this silico study has identified potential PPAD inhibitors and provided insights into the structural features that could be crucial for PPAD inhibitory activity.

Type 2 diabetes (T2DM) represents a major global public health challenge. Despite being a common chronic illness, its underlying disease mechanism remains highly complex, driven by a multifactorial interplay between genetic predisposition and lifestyle exposures. Numerous genetic variants associated with the susceptibility of T2DM have been identified, allowing the development of polygenic risk score (PRS) to predict an individual’s risk in disease development, yet to which extend such PRS is applicable in Malaysian cohort has not been assessed. This study evaluates a polygenic risk score (PRS) model for T2DM within a Malaysian cohort. Genetic variants associated to T2DM were curated using proprietary methods informed by prior research on the UK Biobank dataset. For the current evaluation study, anonymized data from 613 Malaysian individuals was used. PRS calculations and model assessments were conducted using customised R scripts. A total of 1,983 single nucleotide polymorphisms (SNPs) were included in the final dataset. Logistic regression was employed to test the association between PRS and T2DM status. The model demonstrated strong discriminative performance, with an area under the curve (AUC) of 0.96 (CI: 0.95-0.97). Additional evaluation metrics, including positive predictive value (PPV), negative predictive value (NPV), Sensitivity and Specificity, all ranged between 0.8 to 0.9, showing high predictive robustness. Calibration analysis further supported the model’s reliability, with a Brier score of 0.077. Beyond the primary analysis, a comparative evaluation was conducted to refine the model. Fisher’s exact test was applied to filter SNPs with less discriminatory power (p < 0.01), resulting in a reduced variant panel and a subsequent drop in performance metrics. This highlights the trade-off between statistical stringency and predictive coverage. Overall, these findings validate the potential of SNPs for prediction in a multi-ethnic Malaysian population. While current model shows strong predictive capability, future work is needed to enhance its generalizability and clinical utility. This study validates a UK Biobank derived PRS for T2DM in a Malaysian cohort, demonstrating its practicability within an industry-led dataset.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by an asymptomatic disease course, high mortality rate, and resistance to conventional cancer treatments in advanced stage. However, membrane proteins are underexplored as potential therapeutic targets in metastatic PDAC for molecular-targeted therapy. To address these hurdles, we extracted and profiled the membrane proteins in both metastatic PDAC AsPC-1 and SW1990 cell lines using the LCMS/ MS approach, followed by pathway analysis with STRING and REACTOME bioinformatics databases. Based on our findings, both AsPC-1 and SW1990 cell lines shared seven membrane and membrane-associated proteins that related to cancer invasion, including annexin A2 (ANXA2), vimentin (VIM), keratin type I cytoskeletal 18 (KRT18), keratin type I cytoskeletal 19 (KRT19), keratin type II cytoskeletal 8 (KRT8), actin cytoplasmic 2 (ACTG1), and plectin (PLEC). Meanwhile, we also identified another two membrane-associated proteins that related to the metastasis event in the SW1990 cell line, namely galectin-1 (LGALS1) and alpha-actinin-1 (ACTN1). Our GO enrichment analysis results from STRING indicated that these identified proteins are highly interconnected and play essential roles in cancer invasion. They often act collectively and synergistically to modulate the cytoskeletal network within the cell to facilitate cancer invasion. Additionally, we also managed to identify both cell lines shared nine enriched pathways that related to carcinogenesis. Among nine enriched pathways, the collagen formation (R-HSA-1474290) is particularly noteworthy. On top of that, we identified another two enriched pathways that related to the tumour formation in the AsPC-1 cell line, namely the metabolism of serotonin (R-HSA-380612) and assembly of collagen fibrils and other multimeric structures (R-HSA-2022090). As for the SW1990 cell line, another three enriched pathways that related to cancer progression were determined, namely cell recruitment (pro-inflammatory response) (R-HSA-9664424), interleukin-12 signalling (R-HSA-9020591) and cell surface interactions at the vascular wall (R-HSA-202733). In conclusion, our study provides valuable insights into key membrane and membrane-associated proteins, and enriched pathways involved in PDAC invasion and metastasis. These findings contribute to a deeper understanding of PDAC molecular mechanisms and may aid in the development of targeted therapies for metastatic PDAC in the future.