👤 Elif İnan Balcı

This study investigates the clustering patterns of human β-secretase 1 (BACE-1) inhibitors using complex network methodologies based on various distance functions, including Euclidean, Tanimoto, Hamming, and Levenshtein distances. Molecular descriptor vectors such as molecular mass, Merck Molecular Force Field (MMFF) energy, Crippen partition coefficient (ClogP), Crippen molar refractivity (MR), eccentricity, Kappa indices, Synthetic Accessibility Score, Topological Polar Surface Area (TPSA), and 2D/3D autocorrelation entropies are employed to capture the diverse properties of these inhibitors. The Euclidean distance network demonstrates the most reliable clustering results, with strong agreement metrics and minimal information loss, indicating its robustness in capturing essential structural and physicochemical properties. Tanimoto and Hamming distance networks yield valuable clustering outcomes, albeit with moderate performance, while the Levenshtein distance network shows significant discrepancies. The analysis of eigenvector centrality across different networks identifies key inhibitors acting as hubs, which are likely critical in biochemical pathways. Community detection results highlight distinct clustering patterns, with well-defined communities providing insights into the functional and structural groupings of BACE-1 inhibitors. The study also conducts non-parametric tests, revealing significant differences in molecular descriptors, validating the clustering methodology. Despite its limitations, including reliance on specific descriptors and computational complexity, this study offers a comprehensive framework for understanding molecular interactions and guiding therapeutic interventions. Future research could integrate additional descriptors, advanced machine learning techniques, and dynamic network analysis to enhance clustering accuracy and applicability. Show less

Genetic factors have a key role in childhood obesity with higher rates in children than adults. Among the monogenic types of non-syndromic obesity, melanocortin-4 receptor (MC4R) deficiency is the most frequent cause. Beside pathogenic variants, single-nucleotide polymorphisms in MC4R gene are also associated with lower energy expenditure. The aim of this study was to estimate the frequency of MC4R variants and polymorphisms in a cohort of Turkish children and adolescents with severe early-onset obesity, and to understand the clinical features of patients. Patients, 1-17 years of age, with the onset of obesity before 10 years of age and a body mass index (BMI) standard deviation score (SDS) of >2.3, and who had a family history of early-onset obesity in at least one of their first-degree relatives were included in the study. Beside routine blood tests genetic analyses for MC4R gene were performed. Analyses of MC4R revealed previously known variations in three (3.5%) patients, and pathogenic polymorphisms related with obesity in four (4.7%) patients. BMI SDS values were between 2.8 and 5.5 SDS in the pathogenic variant carrier group, and 2.8-4.9 SDS in the polymorphism group. Mean BMI SDS in variant-negative group was 3.4 ± 0.82. Investigation of the MC4R in individuals with early-onset obesity and presence of obesity first-degree relatives is important. Hypertension is a rare comorbidity compared to other causes. Contrary to studies reporting that insulin resistance was absent or very rare, we found it as a frequent finding in both pathogenic variants and polymorphisms of MC4R. Show less