Design of parallel ð½-sheet nanofibrils using Monte Carlo search, coarse-grained simulations, and experimental testing.
Protein Sci
; 33(8): e5102, 2024 Aug.
Article
in En
| MEDLINE
| ID: mdl-39037281
ABSTRACT
Peptide self-assembly into amyloid fibrils provides numerous applications in drug delivery and biomedical engineering applications. We augment our previously-established computational screening technique along with experimental biophysical characterization to discover 7-mer peptides that self-assemble into "parallel ß-sheets", that is, ß-sheets with N-terminus-to-C-terminus ð½-strand vectors oriented in parallel. To accomplish the desired ß-strand organization, we applied the PepAD amino acid sequence design software to the Class-1 cross-ß spine defined by Sawaya et al. This molecular configuration includes two layers of parallel ß-sheets stacked such that N-terminus-to-C-terminus vectors are oriented antiparallel for molecules on adjacent ß-sheets. The first cohort of PepAD identified peptides were examined for their fibrillation behavior in DMD/PRIME20 simulations, and the top performing sequence was selected as a prototype for a subsequent round of sequence refinement. The two rounds of design resulted in a library of eight 7-mer peptides. In DMD/PRIME20 simulations, five of these peptides spontaneously formed fibril-like structures with a predominantly parallel ð½-sheet arrangement, two formed fibril-like structure with <50% in parallel ð½-sheet arrangement and one remained a random coil. Among the eight candidate peptides produced by PepAD and DMD/PRIME20, five were synthesized and purified. All five assembled into amyloid fibrils composed of parallel ß-sheets based on Fourier transform infrared spectroscopy, circular dichroism, electron microscopy, and thioflavin-T fluorescence spectroscopy measurements.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Monte Carlo Method
/
Protein Conformation, beta-Strand
Language:
En
Journal:
Protein Sci
Journal subject:
BIOQUIMICA
Year:
2024
Document type:
Article
Affiliation country:
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