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Diacylglycerol O-acyltransferase 1 ( DGAT1 ) is a pivotal enzyme catalyzing the final step of triglyceride biosynthesis, playing a central role in lipid metabolism and milk fat synthesis in dairy cattle. This study employs an integrated approach combining in silico structural bioinformatics, molecular docking, genotyping, and in vitro gene expression analyses to elucidate the functional and genetic dynamics of the bovine DGAT1 gene. Initially, protein sequences from DGAT and MOGAT families across multiple species were systematically aligned to identify conserved motifs and phylogenetic relationships, with a focus on bovine DGAT1 . High-confidence three-dimensional DGAT1 structural models were generated using AlphaFold2 and validated by rigorous stereochemical assessments. Molecular docking simulations identified lidocaine—a clinically established local anesthetic—as a candidate inhibitor demonstrating favorable binding affinity at critical regulatory sites of DGAT1, corroborated by detailed post-translational modifications (PTMs) profiling that revealed key phosphorylation sites relevant to enzymatic regulation. Phenotypic data spanning 21 months from a cohort of 800 Holstein cows enabled selective genotyping, where animals with extreme milk fat phenotypes (n=60 per group) were analyzed via PCR-RFLP to determine DGAT1 polymorphisms, identifying three genotypes (KK, KA, AA) with significant frequency disparities. Quantitative PCR-based expression analyses showed that the KK genotype is strongly associated with elevated DGAT1 transcript levels and enhanced milk fat content. Statistical validation through chi-square tests and the method confirmed the genetic influence of DGAT1 variants on lactation performance. These findings substantiate the critical role of DGAT1 genetic variation in modulating milk fat synthesis and highlight the KK genotype as a valuable marker for dairy cattle breeding programs aimed at improving milk quality. Moreover, the identification of lidocaine as a potential DGAT1 modulator provides a framework for exploring pharmacological strategies in lipid metabolism regulation. This comprehensive characterization advances molecular understanding and offers actionable insights for genetic and biochemical interventions targeting milk fat production.