Sounds interesting: can sonification help us design new proteins?
Expert Rev Proteomics
; 16(11-12): 875-879, 2019.
Article
in En
| MEDLINE
| ID: mdl-31756126
ABSTRACT
Introduction:
The practice of turning scientific data into music, a practice known as sonification, is a growing field. Driven by analogies between the hierarchical structures of proteins and many forms of music, multiple attempts of mapping proteins to music have been made. Previous works have either worked at a low level, mapping amino acid to notes, or at a higher level, using the overall structure as a basis for composition.Areas covered We report a comprehensive mapping strategy that encompasses the encoding of the geometry of proteins, in addition to the amino acid sequence and secondary structure information. This leads to a piece of music that is both more complete and closely linked to the original protein. By using this mapping, we can invert the process and map music to proteins, retrieving not only the amino acid sequence but also the secondary structure and folding from musical data.Expert opinion We can train a machine learning model on 'protein music' to generate new music that can be translated to new proteins. By selecting proper datasets and conditioning parameters on the generative model, we could tune de novo proteins with high level parameters to achieve certain protein design features.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Proteins
/
Machine Learning
/
Music
Limits:
Humans
Language:
En
Journal:
Expert Rev Proteomics
Journal subject:
BIOQUIMICA
Year:
2019
Document type:
Article
Affiliation country:
United States