bioRxivBiochemistryPreprint
Effect of Pressure on the Conformational Landscape of Human γD-crystallin from Replica Exchange Molecular Dynamics Simulations
Abstract
Human{gamma} D-crystallin belongs to a crucial family of proteins known as crystallins located in fiber cells of the human lens. Since crystallins do not undergo any turnover after birth, they need to possess remarkable thermodynamic stability. However, their sporadic misfolding and aggregation, triggered by environmental perturbations or genetic mutations, constitute the molecular basis of cataracts, which is the primary cause of blindness in the globe according to the World Health Organization. Here, we investigate the impact of high pressure on the conformational landscape of the wild-type H{gamma}D-crystallin using replica exchange molecular dynamics simulations augmented with principal component analysis. We find pressure to have a modest impact on global measures of protein stability, such as root mean square displacement and radius of gyration. Upon projecting our trajectories along the first two principal components from PO_SCPLOWCAC_SCPLOW, however, we observe the emergence of distinct free energy basins at high pressures. By screening local order parameters previously shown or hypothesized as markers of H{gamma}D-crystallin stability, we establish correlations between a tyrosine-tyrosine aromatic contact within the N-terminal domain and the proteins end-to-end distance with projections along the first and second principal components, respectively. Furthermore, we observe the simultaneous contraction of the hydrophobic core and its intrusion by water molecules. This exploration sheds light on the intricate responses of H{gamma}D-crystallin to elevated pressures, offering insights into potential mechanisms underlying its stability and susceptibility to environmental perturbations, crucial for understanding cataract formation.
- organism: human
- assay: protein structure
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
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