When Music Unravels Protein Structure and Folding
(November 8th, 2016) Tired of visualising complex protein structures with traditional graphical models? Try it with musical notes!
While listening to the beats of your favourite song, it's hard to imagine that music could be exploited as a scientific analysis tool as well. For most of us, visualising data is a prerequisite for their analysis and interpretation. When it comes to protein research, the traditional graphical illustration of a structure is sometimes difficult to sift through. This common mode of protein visualisation has now been complemented with an alternative approach that uses musical code as a tool for data auditory display. “In protein bioinformatics and biophysics, we are confronted with the question of how protein structure and functions all derive from the coding sequence in the gene. There are multiple overlapping messages. The notion that music can be used as an aid in this endeavour has occurred to several people working in this area,” points out Robert Bywater, a chemical biologist from the Francis Crick Institute in the UK.
He teamed up with Jonathan Middleton, a music scholar and composer with a penchant for maths, from Eastern Washington University, and together they developed a system that turns amino acid residues of a protein sequence into sounds of different pitches, as the most basic sonification elements. Each amino acid residue was assigned with a numerical value, depending on its hydropathy properties, and numbers were then turned into the notes of the music code. The duo’s work was recently published in the open access journal Heliyon, demonstrating the use of musical algorithms to represent not only the primary amino acid sequence of a protein but also to identify its folding type: a coil, a turn, helices and a β-strand were represented by a combination of numbers, and then converted into musical code. Thus, each folding shape had its unique combination of sounds that represented a simple pattern, distinguishable in the melody. Following the changes in a melody, one can keep track of the protein structure.
The potential benefit of this unconventional approach to protein analysis has been explored since the early 1990s, seeking to complement the classical visual data perception. “I was intent on helping scientists and researchers from other disciplines hear their data. In 2005, I developed the online software musicalgorithms with students for the purpose of composing and teaching, and I later learned that it serves as an excellent tool for sonification of data - with analytical purposes,” commented Jonathan, who is currently enrolled as a visiting professor at the University of Tampere, Finland. These musicalgorithms are nowadays a publicly available web tool, where one can easily create music from its own data. This could be helpful, for instance, in looking for irregularities in the sequence or simply in teaching protein science to students.
Robert is now interested in including evolutionary information in the analyses and studying what mutations would "sound like". “Melodic patterns of sound can become tools to assist protein chemists in assigning fold types to a given protein with a known sequence but unknown 3D structure,” anticipated the authors in their research article. Equally, the sonification of DNA sequences is underway and maybe we are only a small step away from listening to our genomes. Data-to-sound mappings already serve well in several disciplines from seismology to biomedicine and interfaces for visually disabled people.
The authors further challenged a group of volunteers (not necessarily with a musical or scientific background) to try connecting the melodies with the traditional visual illustration of protein structures. “A significant majority of listeners can discern correlations between data related images and sounds (…) This suggests that pattern recognition of protein structures can be attained on an intuitive level with little training,” stated Bywater and Middleton. On that note, relax your eyes from reading and indulge in the following protein melody.
Ivana Stražić Geljić