Abstract:
Hemoglobinopathies are a cluster of hereditary disorders that impact the structure and functionality
of hemoglobin. These illnesses include a broad spectrum of irregularities, with sickle cell anemia
being one of the more well-known forms. Sickle cell anemia arises from a genetic mutation
GLU6VAL in the HBB gene that results in the synthesis of abnormal hemoglobin (HbS) and the
characteristic deformation of red blood cells into a sickle shape. Sickle-shaped cells then ultimately
block the flow of normal blood cells causing anemia, organ damage, pain crises, and other
infections that lead to reduced life expectancy. The treatment of sickle cell anemia is complex
because of its genetic origin, needing precise treatments that address the underlying mutation in
the HBB gene.
The research used Molecular Dynamics simulations to investigate the molecular complexities of
normal and fetal hemoglobin, to discover crucial interaction patterns that contribute to their antisickling abilities. Thus, the objective is to probe the binding pattern and the stability of the alphagamma chain complex of the fetal hemoglobin for the modulation of the beta chain in adults to
rescue the mutated function of sickled hemoglobin.
The study used a Structural Bioinformatics approach to conduct Molecular Dynamics (MD)
simulations for 200ns, aiming to examine the dynamic interactions occurring inside the alpha and
beta chains of both wild-type sickled and normal hemoglobin Furthermore, the scope of the
investigation was broadened to examine the patterns of alpha-gamma interaction within fetal
hemoglobin.
The findings of the MD simulations not only enhanced understanding of the structural dynamics
but also provided crucial insights into the modified interactions that underlie the manifestation of
sickle cell anemia. Studying the alpha-gamma patterns in fetal hemoglobin has enhanced
knowledge of the molecular characteristics associated with hemoglobinopathies. Thus, the
identification of interaction patterns not only demonstrates the potential of computational methods
in addressing complex genetic diseases at the molecular level but also offers a practical pathway
for the identification of therapeutic target
