Multiscale computational prediction of β-sheet peptide self-assembly morphology

ABSTRACT

Although nanostructures self-assembled by short peptides are very promising in developing novel biomaterials and nanomaterials, it is still a great challenge to design the peptide molecular structure which will self-assemble into designated nanostructures. By combining elastic theory with molecular dynamics simulations, we introduce a multiscale computational approach to predict the β-sheet morphology self-assembled by short peptides in aqueous solution only based on the molecular structure of the peptide. In our approach, the gap between the elastic model and atomistic model is bridged by the simplified model, whose parameters are determined by enhanced sampling and extensive all-atom molecular dynamics simulation results at different levels. This multiscale approach is applied to two model peptides KIIIIK (KI4K) and IIIIKK (I4K2) to test its validity. The computational results, consistent with the previous experimental observations, show that KI4K with a higher ratio of inter-sheet interaction to intra-sheet interaction tends to form tube-like morphology with a larger width, while I4K2 with a lower ratio tends to form fibril with a smaller width. This methodology is anticipated to be helpful for computer-aided design of nanostructures self-assembled by short peptides.

KEYWORDS:

• Peptide self-assembly
• computer prediction
• multiscale simulation

Acknowledgement

The computations of this work were conducted on the HPC cluster of ITP-CAS.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (grant number XDA17010504), the National Natural Science Foundation of China (grant numbers 11504431 and 11947302), and the CAS Biophysics Interdisciplinary Innovation Team Project (grant number 2060299).