Bharath Kumar Chagaleti , Arafat Toghan , Magdi E.A. Zaki , Ali Oubella , Reda A. Haggam
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引用次数: 0
Abstract
Breast cancer remains a leading cause of mortality among women, necessitating the development of non-invasive diagnostic methods. Formaldehyde (FA) has emerged as a potential biomarker for early detection of breast cancer in urine. This study explores the efficacy of boron-nitrogen-doped C60 heterofullerenes (BN(5,6)C58 and BN(6,6)C58) as highly sensitive and selective biosensors for FA detection using density functional theory (DFT). A comprehensive set of electronic, thermodynamic, and quantum chemical descriptors was employed to evaluate the sensing potential. Key computed parameters (including a significantly reduced energy gap (HLG = 0.49 eV), a high adsorption energy (Eads = −12.55 kcal/mol), a favorable Gibbs free energy change (ΔG = −12.73 kcal/mol), an enhanced dipole moment (μ = 7.425 D), increased polarizability (α = 525.640), and non-covalent interaction (NCI) analysis) collectively confirmed that BN doping significantly enhances the interaction strength with FA, with BN(6,6)C58 exhibiting the highest sensitivity (1.9 ×1017). Electronic property analyses demonstrated a reduced energy gap and enhanced charge transfer in BN(6,6)C58@FA, corroborated by molecular electrostatic potential and NCI analyses. The sensor's rapid recovery time (1.65 ×10−3 s) and high electrical conductivity (16 A.m−2) further underscore its potential for real-time breath analysis. These findings highlight BN(6,6)C58 as a promising candidate for non-invasive breast cancer diagnostics, paving the way for developing advanced electrochemical biosensors.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
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