Deciphering the mutagenicity-related toxicity of acrylamide food toxin using computational toxicology, in-silico molecular docking/MD-simulations and bioinformatics

Acrylamide, a widely used chemical and food contaminant, is associated with mutagenicity, neurotoxicity, and carcinogenicity, raising health concerns due to its presence in processed foods and industrial exposure. This study aims to comprehensively characterize acrylamide’s toxicity profile, molecular targets, mutagenicity mechanisms, and protein interactions using computational and bioinformatics approaches. The physicochemical and toxicity profiles of acrylamide were predicted using SwissADME, ADMET-AI, ProTox-II, and ADMETlab 2.0. Target mining was performed via TTD, STITCH, SwissTargetPrediction, ChEMBL, and CTD, with human-specific filtering. Mutagenicity-related targets were retrieved from GeneCards by applying a score cutoff (≥median value) and intersected with acrylamide targets using Venn diagram. Protein-protein interaction (PPI) networks were constructed using STRING 12.0, and the top hub targets were identified by centrality metrics in Cytoscape. Gene ontology (GO) and KEGG pathway enrichment analyses were conducted with Metascape to establish potential toxicity pathways. Molecular docking of acrylamide with AKT1, BCL2, and TP53 was performed by optimizing ligand and protein structures, running CB-DOCK2-based docking, and visualizing interactions via BIOVIA Discovery Studio. A 100-ns molecular dynamics simulation using Desmond assessed the stability and protein–ligand interactions of the complex, with binding free energy calculated by MM-GBSA throughout the trajectory. GEPIA and TIMER were used to analyze gene expression, prognosis, and immune infiltration in relevant cancers. Acrylamide exhibited favorable physicochemical properties (C₃H₅NO, 71.08 g/mol, high solubility, high GI absorption, but no BBB permeability or P-glycoprotein interaction). Toxicity predictions confirmed mutagenic, neurotoxic, and carcinogenic potential. Target mining and filtering identified 68 overlapping mutagenicity-associated targets; PPI network analysis revealed AKT1, TP53, and BCL2 as key hub genes. GO and KEGG analysis showed involvement in stress response, DNA repair, and cancer-related pathways. Molecular docking demonstrated moderate to strong binding affinity of acrylamide for AKT1 (-3.9 kcal/mol), BCL2 (-3.7 kcal/mol), and TP53 (-9.2 kcal/mol), stabilized by van der Waals, hydrogen bonding, and pi-donor interactions. Molecular dynamics simulations showed that acrylamide forms more stable and diverse interactions with TP53 than the known inhibitor pifithrin, as reflected by RMSD, intermolecular contacts, and MM-GBSA binding energies. Bioinformatics analysis linked AKT1, BCL2, and TP53 to key roles in cancer progression, cell survival, and immune modulation. Acrylamide exerts mutagenic and cytotoxic effects through multi-target interactions and pathway modulation, supporting its recognized health hazards and underscoring the need for regulatory vigilance.