Experimentally Consistent Simulation of Aβ_21–30 Peptides with a Minimal NMR Bias

Abstract

Misfolded amyloid peptides are neurotoxic molecules associated with Alzheimer's disease. The Aβ 21−30 peptide fragment is a decapeptide fragment of the complete Aβ42 peptide which is a hypothesized cause of Alzheimer's disease via amyloid fibrillogenesis. Aβ 21−30 is investigated here with a combination of NMR (nuclear magnetic resonance) spectroscopy experiments and molecular dynamics simulations with experiment directed simulation (EDS). EDS is a maximum entropy biasing method that augments a molecular dynamics simulation with experimental data (NMR chemical shifts) to improve agreement with experiments and thus accuracy. EDS molecular dynamics shows that the Aβ 21−30 monomer has a β turn stabilized by the following interactions: S26−K28, D23−S26, and D23−K28. NMR, total correlation spectroscopy, and rotating frame Overhauser effect spectroscopy experiments provide independent agreement. Subsequent two-and four-monomer EDS simulations show aggregation. Diffusion coefficients calculated from molecular simulation also agreed with experimentally measured values only after using EDS, providing independent assessment of accuracy. This work demonstrates how accuracy can be improved by directly using experimental data in molecular dynamics of complex processes like self-assembly.

Peptide framework for screening the effects of amino acids on assembly

“…Enhanced sampling or additional phenomenological modeling must be used to connect the relatively short time scales accessible using MD to the co-assembly experiments. For example, Amirkulova et al ( 31 ) relied on biasing methods to induce a small four-peptide system to aggregate into structures consistent with experimental nuclear magnetic resonance measurements. Thurston et al ( 32 ) used Markov state models from all-atom simulations to model the self-assembly of a larger peptide system.…”

Enhanced sampling methods for molecular dynamics simulations

“…In Ref [349], parallel-bias metadynamics is combined with metainference [350] that is a structural ensemble determination methods that incorporates experimental errors via a Bayesian inference framework. In Ref [351], paralleltempering in the well-tempered ensemble (Section 11.1.4) is combined with experiment directed simulations [352]. A older work along this line is replica-average metadynamics [353,354], where metadynamics or bias-exchange metadynamics is combined with replica-averaging.…”