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Transmembrane helix folding and self-association play important roles in biological signaling and transportation pathways across biomembranes. With molecular simulations, studies to explore the structural biochemistry of this process have been limited to focusing on individual fragments of this process – either helix formation or dimerization. While at an atomistic resolution, it can be prohibitive to access long spatio-temporal scales, at the coarse grained (CG) level, current methods either employ additional constraints to prevent spontaneous unfolding or have a low resolution on sidechain beads that restricts the study of dimer disruption caused by mutations. To address these research gaps, in this work, we apply our recent, in-house developed CG model ( ProMPT ) to study the folding and dimerization of Glycophorin A (GpA) and its mutants in the presence of Dodecyl-phosphocholine (DPC) micelles. Our results first validate the two-stage model that folding and dimerization are independent events for transmembrane helices and found a positive correlation between helix folding and DPC-peptide contacts. The wild type (WT) GpA is observed to be a right-handed dimer with specific GxxxG contacts, which agrees with experimental findings. Specific point mutations reveal several features responsible for the structural stability of GpA. While the T87L mutant forms anti-parallel dimers due to an absence of T87 interhelical hydrogen bonds, a slight loss in helicity and a hinge-like feature at the GxxxG region develops for the G79L mutant. We note that the local changes in the hydrophobic environment, affected by the point mutation, contribute to the development of this helical bend. This work presents a holistic overview of the structural stability of GpA in a micellar environment, while taking secondary structural fluctuations into account. Moreover, it presents opportunities for applications of computationally efficient CG models to study conformational alterations of transmembrane proteins that have physiological relevance. 

Accumulation of protein-based (Aβ) aggregates on cellular membranes with varying structural properties is commonly recognized as the key step in Alzheimer's pathogenesis. But experimental and computational challenges have made this biophysical characterization difficult. In particular, studies connecting biological membrane organization and Aβ aggregation are limited. While experiments have suggested that an increased membrane curvature results in faster Aβ peptide aggregation in the context of Alzheimer's disease, a mechanistic explanation for this relation is missing. In this work, we are leveraging molecular simulations with a physics-based coarse grained model to address and understand the relationships between curved cellular membranes and aggregation of a model template peptide Aβ 16–22. In agreement with experimental results, our simulations also suggest a positive correlation between increased peptide aggregation and membrane curvature. More curved membranes have higher lipid packing defects that engage peptide hydrophobic groups and promote faster diffusion leading to peptide fibrillar structures. In addition, we curated the effects of peptide aggregation on the membrane's structure and organization. Interfacial peptide aggregation results in heterogeneous headgroup–peptide interactions and an induced crowding effect at the lipid headgroup region, leading to a more ordered headgroup region and disordered lipid-tails at the membrane core. This work presents a mechanistic and morphological overview of the relationships between the biomembrane local structure and organization, and Aβ peptide aggregation. 

Peptide misfolding and aberrant assembly in membranous micro-environments have been associated with numerous neurodegenerative diseases. The biomolecular mechanisms and biophysical implications of these amyloid membrane interactions have been under extensive research and can assist in understanding disease pathogenesis and potential development of rational therapeutics. But, the complex nature and diversity of biomolecular interactions, structural transitions, and dependence on local environmental conditions have made accurate microscopic characterization challenging. In this review, using cases of Alzheimer's disease (amyloid-beta peptide), Parkinson's disease (alpha-synuclein peptide) and Huntington's disease (huntingtin protein), we illustrate existing challenges in experimental investigations and summarize recent relevant numerical simulation studies into amyloidogenic peptide–membrane interactions. In addition we project directions for future in silico studies and discuss shortcomings of current computational approaches. 

Aggregation of misfolded oligomeric amyloid-beta (Aβ) peptides on lipid membranes has been identified as a primary event in Alzheimer's pathogenesis. However, the structural and dynamical features of this membrane assisted Aβ aggregation have not been well characterized. The microscopic characterization of dynamic molecular-level interactions in peptide aggregation pathways has been challenging both computationally and experimentally. In this work, we explore differential patterns of membrane-induced Aβ 16–22 (K–L–V–F–F–A–E) aggregation from the microscopic perspective of molecular interactions. Physics-based coarse-grained molecular dynamics (CG-MD) simulations were employed to investigate the effect of lipid headgroup charge – zwitterionic (1-palmitoyl-2-oleoyl- sn-glycero -3-phosphocholine: POPC) and anionic (1-palmitoyl-2-oleoyl- sn-glycero -3-phospho- l -serine: POPS) – on Aβ 16–22 peptide aggregation. Our analyses present an extensive overview of multiple pathways for peptide absorption and biomechanical forces governing peptide folding and aggregation. In agreement with experimental observations, anionic POPS molecules promote extended configurations in Aβ peptides that contribute towards faster emergence of ordered β-sheet-rich peptide assemblies compared to POPC, suggesting faster fibrillation. In addition, lower cumulative rates of peptide aggregation in POPS due to higher peptide–lipid interactions and slower lipid diffusion result in multiple distinct ordered peptide aggregates that can serve as nucleation seeds for subsequent Aβ aggregation. This study provides an in-silico assessment of experimentally observed aggregation patterns, presents new morphological insights and highlights the importance of lipid headgroup chemistry in modulating the peptide absorption and aggregation process.