Proceedings of ISon 2016, 5th Interactive Sonification Workshop, CITEC, Bielefeld University, Germany, December 16, 2016

INTERACTIVE SONIFICATION FOR STRUCTURAL BIOLOGY AND STRUCTURE-BASEDDRUG DESIGN
Holger Ballweg1 , Dr Agnieszka K. Bronowska2 , Dr Paul Vickers1
1 - Department of Computer and Information Sciences,
Northumbria University, Newcastle upon Tyne, UK
2 - School of Chemistry, Newcastle University, Newcastle upon Tyne, UKholger.ballweg@northumbria.ac.uk, agnieszka.bronowska@ncl.ac.uk,
paul.vickers@northumbria.ac.uk
ABSTRACTor less flexible. To account for flexibility is very important in certain aspects of structural biology and rational drug design, and representing the flexibility in an accessible and intuitive way is of a
crucial importance for medicinal chemists, in particular for users
without extensive background in computational chemistry. Another limitation is the number of attributes that can be visualised
simultaneously. Only a certain number of attributes can be shownat any time by varying colours or shapes, but being able to assign several molecular attributes to a molecular fragment (such asgroup of atoms, residue, protein domain) and access these in astraightforward way could be pivotal for the drug design community. Both functionalities would also be highly useful in researchoutreach contexts and for crossing boundaries between disciplines(e.g. science-inspired art projects).
In these respects, enhancing molecular graphics software packages with sonification plugins could make dramatic differences in
the accessibility of macromolecular data.
To assess its applicability and feasibility, we have chosen themacromolecular system, in which intrinsic dynamics plays a pivotal role in its biological function - the human nF-kappaB inducible
kinase (NIK). It is a central component of so-called non-canonical
nF-kB pathway, which is upregulated in many inflammatory conditions and cancers, such as T-cells lymphoma (TCL). This is whatmakes NIK an attractive target for cancer research - finding an inhibitor could open new possibilities for treatment of TCL, which
has a very poor prognosis in general. The area around the Adenosine triphosphate (ATP) binding site, which can be druggable byinhibitors, is surrounded by highly flexible loops, including the activation loop, which directly controls the biological activity of the
enzyme (Figure 1). The dynamics of the so-called hinge regionis also involved in regulation of the ligand/drug binding to theprotein. Despite their biological importance, these features may
be challenging to spot in conventional visualisation strategies, i.e.
when a single structure of the protein is visualised.

The visualisation of structural biology data can be quite challenging as the datasets are complex, in particular the intrinsic dynamics/flexibility. Therefore some researchers have looked into the useof sonification for the display of proteins. Combining sonificationand visualisation appears to be well fitted to this problem, but at
the time of writing there are no plugins available for any of the
major molecular visualisation applications.
Therefore we set out to develop a sonification plugin for oneof those applications, released as open-source software, in order tofacilitate scrutiny and evaluation from as many parties as possible.
This paper presents our open source sonification plugin for
UCSF Chimera, which we have developed in collaboration withmedicinal chemists and structural biologists. We determined twotasks that we deemed were not well represented visually and developed sonifications for them. Furthermore, we extended a generalpurpose Chimera tool to map attributes of protein residues to pitch.
We evaluated one of the tasks with eight participants and present
the results of this evaluation.
1. INTRODUCTION
Molecular graphics and visualisation has a long tradition in analysing
and interpreting computational chemistry and structural biology
data. High demand for a powerful software, rendering the structural and dynamic attribute of macromolecular datasets in accurate yet visually elegant and intuitive ways, has resulted in the development of several molecular graphics packages and platforms,
open-source (VMD, UCSF Chimera, PyMol) as well as commercial (MOE, Schrodinger).
UCSF Chimera is one of the leading software packages for interactive visualisation and analysis of macromolecular complexes(protein-protein, protein-ligand, DNA), their structure and dynamics [1]. It is open-source licensed for academic use, has a long
history, a considerable user base, and is constantly in active development. As it provides a Python API it is easily extendable andhas a strong user base developing plug-ins.
Recent advances of visualisation platforms suitable for macromolecular settings exposed the limitations of visualisation as atechnique; namely, its difficulty to deal with intrinsic dynamics
of molecular targets, and limitations in the number of molecular attributes visualised simultaneously. Most molecules are notstatic in time, and different parts of the structures might be more

2. RELATED WORK
Sonification of proteins and DNA has a long history, dating backto Hayashi and Munakata’s mapping of DNA sequences for analysis [2]. Following that, are many more examples of artistic andscientific auditory display mapping the building blocks of proteins,
especially of DNA, to pitches or other attributes of sound. Dunn
and Clark provide a very musical example of this, in an artisticcollaborative project to sonify protein chains [3]. Garcia-Ruiz andISon2016-1

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3. DESIGN
3.1. Spatialisation
As other immersive approaches were successfully using spatialisation as part of the sonification technique, we decided to test thisapproach in our experiments [8, 6]. As we were binding the soundto the visualisation it also seemed the most intuitive choice to bindsound sources corresponding to parts of the protein to virtual spatialised sound sources.
We intended the plugin to easily integrate into the current workflow and technical setup of the intended users. Therefore we used
headphones as preferred delivery method. This also gave us thepossibility to use HRTFs to render a 3D soundfield on standard
stereo headphones.
3.2. Interaction
As macromolecules such as proteins, nucleic acids, and their complexes can be very large and flexible and we wanted to avoid overloading the user with information, we chose to use interactive sonification in the user experience. The user can click on elements ofthe molecules to get sonic feedback and a temporary colour changeof the component which is sonified. This visual feedback provides
a point of reference to the user, especially as spatial distribution in
the sound is not easy to discern when the zoom level is small.
In most tasks where molecular visualisation is used, not only
the current element but also its surroundings are important. Therefore we decided to implement a travelling wave paradigm, i.e., aninteraction based on the idea of a wave circularly spreading outwards in all directions from a point in space. In our case, a wave
front spreads outward from the point the user interacted with, similar to the Data Sonogram method of Model-based Sonification
introduced in [10]. The wave loses energy as it travels, rendering later elements of the sonification less pronounced. The visualfeedback is coupled with the wave front, i.e., the moment an element is “hit”, the temporary colour change occurs with the colour
intensity relative to the energy of the wave.
We plan to use three different wave propagation methods in the
final version of the framework (currently only (1) is implemented):

Figure 1: Ribbon diagram of the kinase domain of human NIK(PDB code 4IDT). The secondary structure is represented as grey
elements (helices, sheets, and loops). The flexible loops aremarked in red circles. The hinge regions is marked in blue circle. The residues involved in the ligand binding are displayed andcoloured by atom.

Gutierrez-Pulido provide an extensive overview of auditory display of molecular structures [4].
The CoRSAIRe project [5, 6] developed a multimodal environment for protein docking analysis. In the project, a researcher
works in a virtual environment interacting with proteins. Sonification is used to augment the display and the interaction of proteinsin 3d space.
Multiple sonification plug-ins have been developed for molecular visualisation software: Grond and Dall’Antonio’s [7] SUMO
framework is a sonification plugin for the molecular visualisation
application PyMOL. In their framework, they implemented two
example sonifications: an amino acid sonification and a B-factor
sonification.
Rau et al. [8] use sonification to augment events extracted
from molecular dynamics simulations in MegaMol, a visualisation
middleware for visualising point-based molecular datasets. They
used OpenAL to provide spatial audio and auditory icons to highlight events happening in the simulation. This aimed to prevent theuser from missing them due to occlusion, e.g., H-Bonds forming
and breaking in the simulation. Presenting the plugin to collaborators in the field of structural biology, they received positive feedback, though they did not see any immediate advantage for their
day-to-day work.
As a side note, the FoldSynth environment for protein folding
synthesis [9] provides an (as of yet) undocumented sonification

1. propagation to the directly connected neighbours of the origin element;
2. propagation as in 1, but also to elements connected with
H-bonds;
3. propagation in 3d space according to the radius of the wave’s
reach.
This will provide the user the choice to concentrate on the immediate vicinity of the element (1), the logical vicinity (2) or the
spatial vicinity (3). We found that in some applications it is beneficial to stagger the wave front in mode (1) to prevent simultaneous
events. This means that instead of playing the element the user
clicked on and then the adjacent elements, the adjacent elements
are staggered, so if the user clicks on element 3 in a chain of 5elements, the elements are played in the order 3, 2, 4, 1, 5 insteadof 3, 2+4, 1+5.
We provide controls to change the propagation rate and radiusof the wave, as well as enable or disable the staggering of the wave.

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3.3. Backgrounding of sound objects

done in Python, other sound rendering options are possible as well,e.g., using Pure Data or Cycling74’s Max, as the OSC commands
used are relatively language-agnostic (see Table 1).
In Python, the individual parts of the sonification are represented by “sound objects”, data structures that correspond to synthesis processes in the sound rendering software. In our current
implementation they correspond to Synths in SuperCollider. Each“sound object” has a unique id shared between sound rendering
software and plugin, and can be modified by setting arbitrary strings
to numerical values, corresponding to arguments to those synthesis
processes.
SuperCollider’s sclang is used to implement handling of soundgeneration and synthesis processes. Sound is spatialised with thehelp of the Ambisonic Toolkit (ATK) [13]. Sounds are placed
according to the position of the represented part of the molecule(atom, residue, bond) in relation to the camera position of theuser’s viewer. Chimera provides a trigger for changes in viewpoint, which is used in our plugin to recalculate all sound objects’spatial positions.
As the listener’s coordinates are taken from the camera position, the user is not able to manipulate the listening position separately from the viewing position. Possible future work could include placing a separate “listener” in the scene, or positioning thelistening position in front of the viewing position.
The plugins GUI enables switching between different Ambisonic decoders. Several decoders for headphone output basedon head-related transfer functions (HRTFs), are provided, with achoice between KEMAR and synthetic HRTFs, enabling 3D soundexperience over stereo headphones. A UHJ stereo decoder is also
provided to enable output over Stereo speakers. The plugin is free
software under the terms of the GNU General Public License andwork-in-progress source code can be found online1 .

We found that with mapping parameters to pitch, high-pitched permanently sounding objects in the soundscape can overburden theuser, especially in our stereo version. Our sonification design demanded some elements of the molecules we deemed important tobe sonified permanently though. Therefore we implemented aninteractive property to enable us to keep sounds in the mix, in a
volume corresponding to their location in space, but still not dominate the soundscape.
The permanently sounding objects are therefore low-pass filtered to 300 Hz (subject to further evaluation) after their creation.
We hope that this puts them in the perceptual background of thescene by removing their dominance in the soundscape. The filter
is lifted for a short amount of time only when a “wave” hits theseelements or the user clicks on them, restoring the backgroundedsound objects to their former spectral glory.

Figure 2: Sonification settings GUI. Allows the user to change theAmbisonic decoder used and the volume of the sonification. The“Wave settings” part relates to the Data Sonogram-like travellingwave interaction. The radius determines how many elements thewave reaches and the speed determines the wait time between elements. “Staggering” refers to not simultaneously playing parts of
the wave that would be played simultaneous otherwise.

4.2. Sonification for molecular docking
The first task we looked at is the docking of small molecular drug
compounds to their cognate protein receptors, in order to design
tight-binding (potent) and selective inhibitors (a process called iterative lead optimisation). The same task is routinely performedby medicinal chemists in order to select the best binder from alist of small molecular compounds, a process known as structurebased virtual screening. In this application, the chemists needto understand the structure and intrinsic dynamics of the bindingsite of the protein to draw conclusions about factors governing thebinding potency, specificity, and selectivity.
This information allows for the rational design of drug-candidates
with the optimal pharmacological profile in order to minimise thenumber of adverse effects. As some parts of the binding sites canbe very tightly embedded in the structure they can be challenging to visualise in a way that is required for the task. Also, thedynamics of the binding site, which are notoriously difficult to inspect visually, may sometimes play a pivotal role in governing theligand-protein associations (e.g., HIV-1 protease inhibitors, hERG
potassium channel and cytochrome P450 binders).
We designed an auditory display to illustrate the electrostaticand van der Waals’ interactions influencing the enthalpic contribution to the free energy of protein-ligand association, and the atomic
positional fluctuations (APFs), which are the measure of the conformational flexibility of the protein target and ligand molecules

4. IMPLEMENTATION
4.1. Framework
We chose UCSF Chimera as the target platform as it is widelyused, open source, free for academic use, and relatively straightforward to extend. It provides support for all data formats (PDB
and mol2) and applications (visualisation of molecules and docking tasks) we targeted.
The plugin is written in the Python programming language.
Chimera takes care of translating the source files in PDB or otherformats into hierarchical data structures representing models, madeup of residues, atoms, and bonds, etc. It provides triggers forchanges in these data structures which we use to detect loading
and deleting of molecules, updating the sonification accordingly.
All other data processing is done in Python with the help of
the open-source scientific computing library Numpy [11].
SuperCollider is used as the synthesis engine, as it has good
support for all major operating systems, supports 3D sound withAmbisonics, and has good sound synthesis plugins [12].
The plugin communicates with SuperCollider over UDP using
the Open Sound Control (OSC) protocol. As all data processing is

1 See https://github.com/mortuosplango/chison.

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Table 1: Simple sound object OSC protocol. Sound objects correspond to synthesis processes on the synthesis engine and data structureson the client.
OSC command
Explanation/obj/new id sound type [attr name attr value]* Add new object with id and sound type/obj/modify id [attr name attr value]*
Modify existing object by id/obj/delete id
Delete object by id/resetReset everything (delete all sound objects and samples)/sample/new id path
Load sample at path to this id/decoder/set name
Switch Ambisonic decoder/volume/set volume
Set global volume between 0 and 1.0
4.3. B-factor sonification(entropic contribution to the free binding energy), in order to navigate the user in the processes of virtual screening and iterative
optimisation of the lead molecule.
We used auditory icons and interactive parameter mapping
sonification (PMSon) to give interactive feedback.
Auditory icons represent the H-bonds present between the ligand and the protein.
PMSon is used for the display of the ligand atoms. The constant sound of the ligand is represented using phase modulation
synthesis. It is mapped linearly to the modulation frequency, whereas
the grid van der Waals’ score is mapped exponentially to the carrier frequency. Therefore each sound object in a ligand has thesame carrier frequency, while the modulation frequency depends
on the individual atoms’ charge. This provides a unique overview
sound for each ligand depending on the van der Waals’ score whileproviding feedback on the charge of the object on click. Throughthe addition of vibrato we livened up the sound by adding a bit ofrandomness to the pitch and wanted to improve source separationaccording to the principle of common fate [14].
Inspired by science fiction film soundscapes we chose to gowith a space ship docking metaphor, with the H-bonds closing represented with a sound modelled after a magnetic seal docking on
an air conduit.
The protein’s residues are sonified only on interaction, where
the B-factors (also known as DebyeWaller factors, a measure of
the intrinsic flexibility of parts of a protein) are mapped to the pitchof the sound objects. We used interactive PMSon to show which
components are more flexible than others. We mapped the B-factor
values exponentially to the pitch of a slightly distorted sine wave
(see Figure 3) produced by f (x) = tanh(sin(x) ⇤ 2.8). This
provides a relatively small spectral and CPU-footprint while still
having some timbral qualities of a square wave, making it easier
to localise than a pure sine tone.
By clicking on a residue or atom, the user can play the corresponding pitch of that region and of the neighbouring residues oratoms according to the wave settings.

The second task is the sonification of DebyeWaller factors, also
known as B-factors, and/or atomic positional fluctuations (APFs)
of atoms or amino acid residues, related to their intrinsic flexibility. Combined with a simple animation of the sonified parts thiswill help the researchers understand the dynamic behaviour of theprotein of interest better.
We used the same interactive PMSon for displaying the Bfactors as in the previous paragraph. Additionally, we continuously displayed the 20% of residues with the highest values. They
are displayed as sequence of sound events with a percussive envelope. The wait time between events is inversely proportional to theB-factor value. We added vibrato as in the other task. Additionally, the vibrato gets more pronounced in higher pitch ranges (ifthe MIDI note number is bigger than 80) to create a threshold asused in [15].
By clicking on a residue, the user can play the corresponding
pitch of that region and of the neighbouring residues according to
the wave settings.
4.4. General-purpose sonification GUI
In addition to these tasks, the plugin comes with a GUI that enables
the user to specify which data they want to sonify. We extended
a widely used Chimera tool that enables the mapping of attributes
to rendering parameters (e.g., colour or radius) to also give an option to render in pitch. This general-purpose sonification option
will hopefully in future versions of Chimera be integrated into thecurrent user experience.
The current version can be seen in Figure 4. After choosing
a structural element level (atom, residue, or molecule) and an attribute, users can define markers in the histogram view and which
MIDI pitch they represent. Values in between these markers are
mapped with linear interpolation to the chosen pitches. They canspecify a sound, as well as if a pitch and which pitch is played incase there is no value associated with the element. The user thencan interact with the molecule by clicking certain parts of it andconfigure the resulting wave front in the sonification settings (seeFigure 2).

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In an informal evaluation, we asked 8 participants to evaluate ourprototype for displaying molecular dynamics. 7 out of 8 participants are working in the field of structural biology or computational chemistry at least on a PhD candidate level. One participant
is an electroacoustic composer. Each was shown a MD-Movie, a-1,5Figure 3: Sine wave (black) vs. distorted sine wave produced by
f (x) = tanh(sin(x) ⇤ 2.8) (red, striped).
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Figure 5: Coloured representation of B-factors in human NIK protein. Red parts represent high, white middle, blue low B-factors.
Figure 4: Sonify by attribute GUI. In this case, mapping the average B-factor of the residues to pitch. There are 3 markers definedin the histogram, each setting a pitch. The pitch values in between
markers are linearly interpolated.

Comparing it to the visual modality, this researcher was quick topoint out that it was much easier to see than to probe the protein forsonic information, and that this endeavour therefore is a waste oftime. The less senior participants were more open to our work ingeneral and its possibilities. 3 participants remarked that although
the visual modality was quicker to present the information, the different interaction type and the relatively lower speed of interaction
lead to a more contemplative exploration.
In general, no participant had problems using the sonification
to fulfil the task. 7 out of 8 found the most flexible region using
the sonification.
Rating their experience on a 5 point Lickert scale, 5 out of
7 participants agreed with or strongly agreed with the sonification
being “beneficial”, 4 being “musical”, 0 being “annoying”, 5 being“helpful”, 0 being “fatiguing”, 1 being “transparent”.
On the other hand, 3 participants agreed with or strongly agreed
with the mapping between data and sound being “transparent”.
5 participants reported they were interested in using this sonification in their work, 4 participants were interested in using it inresearch, 4 in teaching, and 2 in an art context. One participant
remarked that it “would be good to use if teaching students or individuals who do not have a lot of experience in using chimera
or other applications”. 4 reported they would be interested to use
sonification in general in their work.
In conclusion, there seems to be at least some general interest
in sonification in the field. The general work environment noiselevel appears to be sufficiently quiet to use sonification. As mostparticipants listen to music at work, the hardware for sound reproduction is already there. The interaction in our mapping turned
out to be intuitively understandable even for participants which

coloured representation of B-factors and our sonification displaying the same protein (see Figure 5). The participants were asked to
identify the most flexible region of the protein in each representation. By monitoring the response and asking the participants to fillout questionnaires before and after the study, we aimed to determine: how the system could be integrated into their workflow; if
the software system with sonification could have a positive influence on drug design tasks; and how the system could be improved.
We gave minimal instruction on how to use the sonification, justexplaining the mapping and the interaction possibilities.
Before using the software, we asked the participants to fillin a short questionnaire about their listening habits, their working habits and their work place. We also asked them what they
imagined proteins would sound like.
7 out of 8 participants filled out our questionnaires. 4 reported
working in a quiet environment. 5 use Chimera daily. 5 participants had some level of musical training. None of the participants
reported associating any sound with proteins. Besides the composer, nobody reported using sonification or sound in their work.
6 participants listen to music while working at least once a day.
Participants were audio- and video-recorded while using thesystem. After using the sonification, the participants were asked tofill in a questionnaire about their experience using the software.
Our questionnaires and informal chats with the participants
showed a wide range of responses. One experienced researcher
entirely dismissed the whole idea of sonification and our setup.

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do not regularly use Chimera. The difference between participants perceiving the mapping as transparent and the sonification
as transparent points to a problem in sound design of the overallsonification, showing an imbalance between the volume levels of
permanent and interaction-triggered sounds.

counterions (0.1M concentration). Prior to MD simulations, thesystems undergone 25000 steps of molecular mechanical energy
minimisation. This was followed by 100 ps MD simulations, during which positional constraints were used on all duplex atoms.
After the following unrestrained equilibration phase (10 ns) the
production runs were carried for 100 ns, with an integration time
step of 2 fs. The cutoff for non-bonded interactions was 0.1 nm.
The coordinates were saved every 10 ps.
The temperature was kept constant at T= 298 K by using velocity rescaling with a coupling time of 0.1 ps. The pressure was
kept constant at 1bar using an isotropic coupling to ParrinelloRahman barostat with a coupling time of 0.1ps [19]. A cutoff of
1nm was used for all nonbonded interactions. Long-range electrostatic interactions were treated with the particle-mesh Ewald [20]method using a grid spacing of 0.1nm with cubic interpolation. Allbonds between hydrogens and heavy atoms were constrained using
the LINCS algorithm [21].
The intrinsic flexibility of the protein chain, hydrogen-bondnetwork, and conformational changes were computed and analysed using tools implemented in the Gromacs package [17]. The
intrinsic flexibility was quantified by root-mean-square fluctuations (RMSF) of atomic positions and calculated B-factors. For
the visual inspection of the results prior to the choice of the sonification strategy we used xmgrace and UCSF Chimera [22, 23]
packages.

6. DISCUSSION
We presented our work-in-progress sonification plugin for the molecular visualisation application UCSF Chimera. We developed two
initial sonifications for important tasks in computational chemistry
and a general-purpose sonification GUI.
In presenting our work to potential users we received valuable, mostly positive feedback. Using a travelling-wave paradigm
related to Data Sonogram scheme for interaction with the molecular structures proved intuitive for novel users. The backgrounding
via low-pass filtering for permanent sounds seemed to be valuable,
but the filtering needs to be adjusted to account for the feedback.
Although no direct improvement on task performance could
be measured, participants were interested in using sonification in
their research and teaching, and our current approach to interaction
was intuitively comprehensible.
7. VIDEO EXAMPLE
We illustrated the described tasks and the general purpose sonification GUI with a video example2 . It shows first the docking task,
then the B-factor sonification, and last the general purpose GUI.

10. REFERENCES[1] Eric F Pettersen, Thomas D Goddard, Conrad C Huang, Gregory S Couch, Daniel M Greenblatt, Elaine C Meng, andThomas E Ferrin, “UCSF Chimera – a visualization systemfor exploratory research and analysis,” Journal of Computational Chemistry, vol. 25, no. 13, pp. 1605–1612, 2004.

8. FUTURE WORK
We plan to conduct an extensive user study on master’s students inchemistry soon. We are currently working on improving the sonifications described here and on the design of the study, constructing
a concrete task related to molecular docking that is manageable forbeginners and provides quantifiable data.
Additionally, we want to evaluate our general sonification plugin with experienced Chimera users to come up with some mapping presets as well as other useful features, e.g., mapping to rhythm
or other sound attributes.
We released the source code online already but plan to package
it in a form that is easier to install. If the concept of sound objects
and spatial sonification proves valuable in other sonification tasks,
we will decouple general components from the Chimera plugin toprovide another Python sonification framework or integrate it into
Sonipy [16].

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Muller, and Thomas Ertl, “Enhancing visualization of

2 Available at https://uiae.de/ison-2016.

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