Insights into the solubility of γ $$ \gamma $$ D-crystallin from multiscale atomistic simulations

Advanced computational approaches to understand protein aggregation

Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.

Molecular Insights into the Inhibitory Role of α-Crystallin against γD-Crystallin Aggregation

Cataracts, a major cause of global blindness, contribute significantly to the overall prevalence of blindness. The opacification of the lens, resulting in cataract formation, primarily occurs due to the aggregation of crystallin proteins within the eye lens. Despite the high concentration of these crystallins, they remarkably maintain the lens transparency and refractive index. α-Crystallins (α-crys), acting as chaperones, play a crucial role in preventing crystallin aggregation, although the exact molecular mechanism remains uncertain. In this study, we employed a combination of molecular docking, all-atom molecular dynamics simulations, and advanced free energy calculations to investigate the interaction between γD-crystallin (γD-crys), a major structural protein of the eye lens, and α-crystallin proteins. Our findings demonstrate that α-crys exhibits an enhanced affinity for the NTD2 and CTD4 regions of γD-crys. The NTD2 and CTD4 regions form the interface between the N-terminal domain (NTD) and the C-terminal domain (CTD) of the γD-crys protein. By binding to the interface region between the NTD and CTD of the protein, α-crys effectively inhibits the formation of domain-swapped aggregates and mitigates protein aggregation. Analysis of the Markov state models using molecular dynamics trajectories confirms that minimum free energy conformations correspond to the binding of the α-crystallin domain (ACD) of α-crys to NTD2 and CTD4 that form the interdomain interface.