Deciphering the Structural Dynamics of Chicken Albumin through Molecular Dynamics Simulations and Deep Learning
Source: PubMed Central Open Access, NCBI / U.S. National Library of Medicine
Serum albumin (SA), the most abundant protein carrier in blood plasma, is a major allergen source. Chicken serum albumin (CHSA) is associated with chicken meat allergy due to its cross-reactivity with human serum albumin (HSA). To elucidate the structural basis underlying this immunological cross-recognition, Molecular Dynamics (MD) simulations combined with data-driven artificial intelligence (AI) analyses were employed to compare the structural and dynamic characteristics of CHSA and HSA. Despite moderate sequence identity (∼46.6%), CHSA displays comparable protein compactness and backbone flexibility to HSA, with slightly greater compactness. Domains I and III of CHSA govern a conserved scissor-like motion like HSA. This dynamic similarity may facilitate structural mimicry, enabling antibody cross-recognition. Moreover, CHSA exhibits larger drug sites (Sudlow sites I and II) than HSA, affecting ligand-binding affinity and specificity. The reactive C34 in CHSA demonstrates a similar hydrogen bond network to that in HSA, suggesting comparable redox reactivity. C34 of CHSA can hydrogen bond with L31, Y84, and S35. Deep learning models distinguished HSA and CHSA based on their MD-derived features. To gain insight into the learned representations, an explainable AI approachTesting with Concept Activation Vectorswas employed. AI-based analysis identifies nuanced differences in spatial organization and dynamics patterns, particularly in flexibility, solvent exposure, and intern
Abstract
Serum albumin (SA), the most abundant protein carrier in blood plasma, is a major allergen source. Chicken serum albumin (CHSA) is associated with chicken meat allergy due to its cross-reactivity with human serum albumin (HSA). To elucidate the structural basis underlying this immunological cross-recognition, Molecular Dynamics (MD) simulations combined with data-driven artificial intelligence (AI) analyses were employed to compare the structural and dynamic characteristics of CHSA and HSA. Despite moderate sequence identity (∼46.6%), CHSA displays comparable protein compactness and backbone flexibility to HSA, with slightly greater compactness. Domains I and III of CHSA govern a conserved scissor-like motion like HSA. This dynamic similarity may facilitate structural mimicry, enabling antibody cross-recognition. Moreover, CHSA exhibits larger drug sites (Sudlow sites I and II) than HSA, affecting ligand-binding affinity and specificity. The reactive C34 in CHSA demonstrates a similar hydrogen bond network to that in HSA, suggesting comparable redox reactivity. C34 of CHSA can hydrogen bond with L31, Y84, and S35. Deep learning models distinguished HSA and CHSA based on their MD-derived features. To gain insight into the learned representations, an explainable AI approachTesting with Concept Activation Vectorswas employed. AI-based analysis identifies nuanced differences in spatial organization and dynamics patterns, particularly in flexibility, solvent exposure, and internal stabilization. These differences, not captured by averaged measures, may influence epitope presentation. This study provides molecular-level insights into CHSA–HSA similarities and differences, informing their potential biomedical applications and highlighting the need for further experimental validation. http://www.w3.org/1999/xlink abs1 float portrait ao6c03484_0008.jpg graphical http://www.w3.org/1999/xlink tgr1 not-for-print float portrait ao6c03484_0006.jpg toc-graphic