In recent years, scientists have created music based on the structure of proteins as a creative way to popularize science better to the general public, but the resulting songs have not always been pleasing to the ears. In a study published on September 29 in the journal Heliyon, researchers use the style of existing musical genres to guide the structure of protein vocals to make it more musical. Using the style of Frédéric Chopin Impromptu fantasy and other classical pieces as a guide, the researchers were able to convert protein into song with greater musicality.
The creation of unique melodies from proteins is achieved using a protein-music algorithm. This algorithm incorporates specific elements of proteins – such as the size and position of amino acids – and maps them to various musical elements to create an auditory “blueprint” of protein structure.
“The existing protein music was primarily designed by simply mapping certain amino acid patterns to fundamental musical characteristics such as pitches and note lengths, but they do not match well with more complex musical characteristics such as rhythm. and harmony, ”says lead author Yu Zong. Chen, professor in the Department of Pharmacy at the National University of Singapore. “By focusing on a musical style, we can guide more complex mappings of amino acid motif combinations with various musical characteristics.”
For their experiment, the researchers analyzed the pitch, length, octaves, chords, dynamics, and main theme of four pieces from the Romantic era of classical music of the mid-1800s. These pieces, including Impromptu fantasy by Chopin and Vagabond’s fantasy by Franz Schubert, were selected to represent the fantastic-impromptu genre that emerged around this time.
“We chose the specific musical style of a Fantasy-Impromptu because it is characterized by freedom of expression, which we believe would complement the way proteins regulate a large part of our bodily functions, including our moods.” , explains co-author Peng Zhang (@ zhangpeng1202), post-doctoral researcher at Rockefeller University
Likewise, several of the proteins in the study were chosen for their similarities to key attributes of the Fantasy-Impromptu style. Most of the 18 proteins tested regulate functions such as human emotion, cognition, sensation or performance which, according to the authors, are related to emotional and gender expression.
Next, they mapped 104 structural, physicochemical, and amino acid binding properties of these proteins to six musical characteristics. “We compared the quantitative profile of each amino acid property to the quantified values of the different musical characteristics to find the optimal mapped pairings. at a shorter note length, ”Chen explains.
Of all the proteins tested, the researchers found that the musicality of the proteins was significantly improved. In particular, the oxytocin protein receptor (OXTR) was found to have one of the greatest increases in musicality when using the gender-guided algorithm, compared to an earlier version of the protein-music algorithm.
“The oxytocin receptor protein generated our favorite song,” says Zhang. “This protein sequence produced an identifiable main theme that repeats in rhythm throughout the piece, as well as interesting patterns and patterns that recur independently of our algorithm. There were also pleasant harmonic progressions; for example , many seventh chords resolve naturally. “
The authors note, however, that while the guided algorithm has increased the overall musicality of the protein songs, there is still a long way to go before it sounds like real human music.
“We believe that a next step is to explore more musical styles and more complex combinations of amino acid properties for improved musicality and new pieces of music. Another step, a very important step, is to apply the ‘artificial intelligence to jointly learn the complex properties of amino acids and their combinations with respect to the characteristics of various musical styles to create protein music with enhanced musicality,’ explains Chen.
Research supported by the National Key Research and Development Program of China, the National Natural Science Foundation of China, and Singapore University Funds.
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