Poster M7 - Exploring the Interplay of Hepcidin in Hemochromatosis: An Integrated Approach with AlphaFold2 and Molecular Dynamics Simulation

Introduction: Hemochromatosis, an autosomal recessive disorder, is marked by excessive iron absorption and deposition in vital organs, leading to conditions such as cirrhosis, diabetes, and heart failure if untreated. Hepcidin, a liver-produced peptide hormone, is central to iron homeostasis by inhibiting intestinal iron absorption and iron release from macrophages. Disruptions in hepcidin regulation can result in iron overload disorders like hereditary hemochromatosis or iron deficiency anemia. This study leverages the advanced predictive capabilities of AlphaFold2 alongside Molecular Dynamics (MD) to elucidate the structural dynamics and functional implications of hepcidin and its variants, thereby enhancing our
understanding of its role in iron metabolism and its potential as a therapeutic target.

Materials and

Methods: Utilizing AlphaFold2, a state-of-the-art deep-learning based computational framework , we predicted the three-dimensional structures of hepcidin and its clinically significant variants, which include substitutions at positions 59 (Arginine to Glycine), 70 (Cysteine to Arginine), 71 (Glycine to Aspartate), and 78 (Cysteine to Tyrosine). These structural predictions were visualized and analyzed using Visual Molecular Dynamics (VMD) and MD to assess their energy minimization and stability. The predicted structures' accuracy and reliability were quantified using metrics such as predicted Local Distance Difference Test (pLDDT) scores and predicted aligned errors (PAE). The impact of these amino acid substitutions was further examined in terms of hydrophobicity changes, charge alterations, and disulfide bond disruption.

Results, Conclusions, and Discussions:

Results:
The analysis revealed that the maximum PAE for hepcidin and its variants reached 31.75 residue units, indicating potential deviations from the true alignment. The pLDDT values, with standard deviations ranging from 15.718 to 19.706, reflected varying degrees of confidence in the structural predictions. PTM values between 0.272 and 0.258 per residue suggest a moderate frequency of post-translational modifications. Despite some structural inaccuracies indicated by average pLDDT scores between 58.372% and 46.738%, the predicted models provided valuable insights. Structural changes due to amino acid substitutions were significant, particularly in the disruption of potential disulfide bonds and alterations in hydrophobicity and charge, impacting hepcidin's stability and interaction with other molecules, including ferroportin.

Conclusions and Discussions:
The combined use of AlphaFold2 and MD has proven to be a powerful approach for investigating protein structures and their functional dynamics. This study highlights that specific amino acid substitutions in hepcidin can markedly alter its conformation and stability, thereby affecting its role in iron regulation. Variants at residue positions 59, 70, 71, and 78 demonstrated critical structural changes that influence hepcidin's function and its interaction with iron transport proteins. These findings underscore the importance of structural integrity in hepcidin's function and offer insights into potential therapeutic strategies for managing iron-related disorders.

Furthermore, for future research endeavors, we plan to incorporate AlphaFold3 and other advanced docking tools to perform computational docking studies. These analyses will provide deeper mechanistic insights into how amino acid substitutions alter hepcidin's interactions with key regulatory proteins, facilitating a comprehensive understanding of hepcidin's role in iron metabolism and its potential as a therapeutic target. Through these multidisciplinary approaches, our research aims to bridge the gap between computational predictions and clinical applications, ultimately improving the diagnosis and management of iron-related diseases.

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