Structural insights into peptide self‐assembly using photo‐induced crosslinking experiments and discontinuous molecular dynamics

Abstract

Determining the structure of the (oligomeric) intermediates that form during the self-assembly of amyloidogenic peptides is challenging because of their heterogeneous and dynamic nature. Thus, there is need for methodology to analyze the underlying molecular structure of these transient species. In this work, a combination of fluorescence quenching, photo-induced crosslinking (PIC) and molecular dynamics simulation was used to study the assembly of a synthetic amyloid-forming peptide, Aβ 16-22. A PIC amino acid containing a trifluormethyldiazirine (TFMD) group-Fmoc (TFMD)Phe-was incorporated into the sequence (Aβ* 16-22). Electrospray ionization ion-mobility spectrometry mass-spectrometry (ESI-IMS-MS) analysis of the PIC products confirmed that Aβ* 16-22 forms assemblies with the monomers arranged as antiparallel, in-register β-strands at all time points during the aggregation assay. The assembly process was also monitored separately using fluorescence quenching to profile the fibril assembly reaction. The molecular picture resulting from discontinuous molecule dynamics simulations showed that Aβ 16-22 assembles through a singlestep nucleation into a β-sheet fibril in agreement with these experimental observations. This study provides detailed structural insights into the Aβ 16-22 self-assembly processes, paving the way to explore the self-assembly mechanism of larger, more complex peptides, including those whose aggregation is responsible for human disease. K E Y W O R D S amyloid-forming peptide, discontinuous molecular dynamics, peptide self assembly, photoinduced crosslinking 1 | INTRODUCTION Self-assembling peptides can be difficult to study in vitro because of their hydrophobicity and propensity to aggregate into high order Samuel J. Bunce and Yiming Wang authors contributed equally to this work.

Evolution of large Aβ16–22 aggregates at atomic details and potential of mean force associated to peptide unbinding and fragmentation events

“…3 Computationally, this is an extremely difficult problem as the free energy landscape increases in complexity as the oligomer size augments. For this reason, most computational studies, with the exception of the simulation of 1000 transthyretin TTR(105-115) fragments 4 and 192 Aβ16-22 peptides, 5 focused on small oligomer sizes <36 peptides. [6][7][8] To accelerate the sampling, they even resort to coarse-grained (CG) models and an implicit solvent representation and enhanced sampling techniques, such as umbrella and path sampling, replica exchange molecular dynamics (REMD), replica exchange with solute scaling (REST2), and metadynamics.…”

Self-Assembly of Amyloid-Beta (Aβ) Peptides from Solution to Near In Vivo Conditions

“…11 Incorporating more degrees of freedom, the aggregation of Aβ16-22 peptides was followed by discrete molecular dynamics (DMD) simulations using the PRIME four-bead coarsegrained protein model with implicit solvent. Assuming a 1SN mechanism, which was confirmed by electron spray ionization ion-mobility spectrometry mass spectrometry, 12 the thermodynamic phase diagram of Aβ16-22 fitted well TEM (transmission electron microscopy) fibrillation experiments at peptide concentrations varying from 10 to 200 μM at 277− 330 K. 13 It is to be noted that the N-and C-terminal unprotected Aβ16-22 peptides at concentration of 30 μM and above show rapid kinetics fibrillation within seconds to minutes consistent with the nucleation−elongation 1SN, and this suggests a nucleus size of 6−7 peptides displaying two perpendicular β-sheets (see Figure 1B). 14 Coarse-grained OPEP lattice−Boltzmann molecular dynamics (LBMD) simulations of 1000 Aβ16-22 peptides protected by acetyl and NH 2 with hydrodynamics also reported critical nuclei of 6−10 mers.…”

Peptide Self-Assembled Nanocarriers for Cancer Drug Delivery

“…While self-assembled peptide nanocarriers for cancer drugs should not be considered a panacea to the challenges of cancer drug delivery, we consider that the intrinsic advantages of self-assembling peptide materials, along with the increasing progress in computational and experimental approaches for their study and design, could possibly lead to novel classes of systems that may provide additional alternatives to current approaches and/or provide a seed for novel multicomponent systems which may partly incorporate peptide self-assembled materials for cancer drug delivery. Importantly, due to the increasing advancement of computing capabilities and the development of novel computational study and design approaches in peptide self-assembly (e.g., refs − ), computations can play a key role in designing multicomponent systems and/or optimizing existing systems, based on feedback that can be provided by experimental in vitro/in vivo studies. Dr. Tamamis and Dr. Gazit envision that the design of novel self-assembling peptide cancer drug nanocarriers can be significantly enabled through integrated and synergistic experimental and computational approaches, with computational feedback provided to experiments and vice versa, ultimately leading to optimized systems and continuous improvment based on the design criteria and ultimately updating and refining the design criteria; such integrative and synergistic approaches could possibly provide means to jointly combat many issues to be addressed in the field, so that novel and improved cancer drug delivery systems, such as self-assembling peptide materials, can potentially and ultimately become translatable from the lab to the clinic.…”