ISSN 2186-7437

NII Shonan Meeting Report

No. 2016-12

Web-based Molecular Graphics
Andrea Schafferhans
Seán O’Donoghue
Haruki Nakamura
September 05–08, 2016

National Institute of Informatics
2-1-2 Hitotsubashi, Chiyoda-Ku, Tokyo, Japan

Web-based Molecular Graphics
Organizers:
Andrea Schafferhans (TUM & HSWT, Germany)Seán O’Donoghue (CSIRO & Garvan Institute, Australia)
Haruki Nakamura (Osaka University, Japan)
September 05–08, 2016

1

Overview of the meeting

1.1

Summary

Molecular graphics is a well established discipline used in many scientific fields(e.g., life sciences, biomedical research, chemistry, material sciences), including commercial research (e.g., pharmaceutical industry). A wealth of methods
and tools have been developed, and are still actively developed – however until
recently activity has focused on stand-alone software. This meeting will explore an emerging new frontier for molecular graphics, namely deployment ina server-client environment, which promises to make molecular structural information much more easily accessible to scientists. In addition, the recent
hybrid approaches have revealed structures, functions and dynamics of verylarge molecules and cellular machineries, which are displayed as both atomic
structures and molecular/cellular images, greatly extending the roles of molecular graphics. This meeting has brought together key players in this emerging
field to explore the challenges and opportunities raised by web-based moleculargraphics and new applications.

1.2

Background

There is a rapidly growing wealth of molecular structure data that has been
derived from experimental methods (e.g., X-ray crystallography, NMR spectroscopy, electron microscopy) and are freely provided from the international
database PDB, Protein Data Bank, as well as computational methods, such as
molecular dynamics. These data provide scientists today with unprecedented
insight into a wide range of molecular phenomena, for example protein function,
biological membrane transport, or material properties. The amount of data is
steadily growing in size as well as in complexity: more protein structures, larger
protein structures (big complexes) and time-resolved data, such as molecular
dynamics trajectories. In the near future, these data may increase in scale toinclude, for example, complex cellular machineries and whole living cells. A
key challenge is to make all of these data accessible to scientists, in ways thatenable interpretation and the generation of new research insights. Fortunately,
nowadays almost all scientists – even students – have easy access to computer1

graphics capabilities powerful enough to show a wide variety of molecular structures. With modern bandwidth speeds, it is even feasible to stream complex,
interactive molecular graphics into simple devices such as an iPad or iPhone, via
GPU-rendering on a remote server. Thus, it is now possible to depict and explore 3D models in regular browsers, such as Mozilla Firefox, Internet Explorer
or Google Chrome. This allows to bring 3D molecular visualisation tools to
non-expert end users without the need to install specialised software. However,in times of a steadily growing amount of data, improved visualization methods
and tools are urgently needed, which can make the more complex data accessible
and interpretable.

1.3

Aims of the meeting

We believe that web molecular graphics is likely to soon become very widelyadopted. Therefore, we feel it was very timely to host a Shonan meeting on
this topic. Overall, the seminar aimed to help give this emerging field direction
and clarity, by bringing together global efforts in making molecular structure
information available to scientists via the web. We discussed strategies for effectively managing very large molecular structures (e.g., millions of atoms ormore). Most current browsers fail to visualize these larger molecular structuresfor various reasons. In some cases (e.g., whole organelles, entire genomes, ormaterials, such as metal-organic frameworks), the molecular assembly becomesso large that it requires the use of multi-scale, often hierarchical representations
that change automatically at different scales, somewhat analogously to Google
Maps. Similar strategies can also be needed for large molecular dynamic simulations. All of these cases are a particular challenge for web molecular graphics,
which is limited by network bandwidth. In addition, many of the scientific problems being investigated cannot be solved with molecular graphics alone. Instead,data on molecular structures needs to be exchanged with other resources, forexample resources that integrate data derived from structures with other information, and display the result using network graphs, or using other visualization
paradigms. Therefore, an approach is required which is compatible to different
modeling environments. Nowadays, the most widely used scripting language is
JavaScript which is moreover used by all recent web browsers. This language
seems best suited to be used to interactively combine the website’s content withthe molecular 3D visualization via WebGL. The seminar will discussed pros
and cons of this architecture and defined desirable interaction paradigms andcommunication methods.

22

Meeting Schedule

Check-in Day: September 4th (Sun)• Welcome Banquet
Day1: September 5th (Mon)• Lightning talks• Keynote: Peter Rose
• Agreement on breakout topics• Group photo shooting• Breakout sessions• Keynote: Mike Goodstadt, Jim Zheng• Breakout check-in and round up
Day2: September 6th (Tue)• Keynote: Haruki Nakamura• Keynote: Sameer Velankar• Tech talk: Sean O’Donoghue, Bosco Ho• Breakout session• Breakout summary• Agreement on further breakout topics• Breakout session
Day3: September 7th (Wed)• Remote Keynote: Graham Johnson• Tech talk: Ian Silitoe• Breakout session• Excursion and Main Banquet
Day4: September 8th (Thu)• Breakout session• Breakout summary• Wrap up

3

3

Keynote and Technical Talks

Compressive Structural Bioinformatics: High Efficiency 3D
Structure Compression
Peter Rose, Peter Rose, RCSB Protein Data Bank, San Diego Supercomputer
Center, University of California, San Diego, USA
Technologies in structural biology continue to improve and help determine
ever-larger 3D macromolecular complexes. Interactive visualization of large
complex structures and large scale queries or structural comparisons across theentire Protein Data Bank (PDB) archive are becoming a bottleneck in termsof network bandwidth, I/O, parsing, and memory consumption. We have developed a compact and extensible file format (MacroMolecular Transmission
Format, MMTF, http://mmtf.rcsb.org) for 3D molecules to overcome these challenges. This compact representation enables efficient data transfer and parsing
for interactive visualization on the web that is one to two orders of magnitudes fast than using standard PDB or mmCIF file formats. MMTF files also
contain bonds and bond orders and consistently calculated secondary structure
information (DSSP). Both the MMTF specification and encoders and decoders
are available open source in GitHub (https://github.com/rcsb/mmtf). MMTF
Decoders are available in Java, JavaScript, Python, and a C/C++ version is under development. Early adopters of MMTF include NGL Viewer, Jmol/JSmol,
3Dmol.js, iCn3D, ICM-Browser, PyMol, BioJava, and Biopython.

Visualizing Human Genome in Time and Space
Jim Zheng, University of Texas Health Science Center at Houston, USA
The high order nuclear organization of mammalian genome plays significant
roles in important cellular functions such as gene regulation and cell state determination. The influx of new details about the higher-level structure anddynamics of the genome from Hi-C and CHIA-PET technology requires newtechniques to model, visualize and analyze the full extent of genomic information in three dimensions. While existing genome browsers have been provenas successful genome information management and visualization tools, thesebrowsers are based on two-dimensional visual interface with limited capacity torepresent structural hierarchies and long-range chromosome interactions, particularly across non-contiguous genomic segments.
We created the first model-view framework of eukaryotic genomes, Genome3D(http://genome3d.org), to enable integration and visualization of genomic andepigenomic data in a three-dimensional space. Our physical genome model
implicitly contains all levels of structure and hierarchy, and provides an underlying platform for integrating multi-scale genomic information within three
dimensions. Our viewer uses a hierarchical model of the relative positions of all
nucleotide atoms in the cell nucleus.
We further developed a game engine based Genome3D browser that has better performance, is platform independent and can be configured to allow users
to access and visualize 3D genome models on a remote server. In this works,
we integrated various genomic databases with Genome3D software, providing

4

a multi-scale genome information visualization system to explore and navigate
eukaryotic genome in 3-dimension.
The new system, iGenome3D, provides a wide spectrum of tools, ranging
from model construction to spatial analysis, to decipher the relationships between 3D conformation of the genome and its functional implication. The incorporation of literature allows users to quickly identify key features from PubMed
abstracts for genes in the displayed 3D genome structure. The seamless integration of UCSC Genome Browser allows genetic and epigenetic features from the2D browser to be visualized in 3D genome structure. iGenome3D can also output 3D genome model in various forms, including one that allows these models
to be explored in modern virtual reality environments such as Oculus. Eukaryotic genomes can be analyzed from a completely new angle in iGenome3D thatenables researchers to make new discoveries from a truly multi-scale exploration

Visualizing Genomes in Three Dimensions
Mike Goodstadt, CNAG (Centro Nacional de Anàlisis Genòmica), Spain
Genomic data is encoded and represented in linear sequence. Yet whencontained within nucleus this 2m long strand is not merely efficiently packed
but it is organized in a non-random structure. This spatial conformation has
been shown to serve as a key part of gene expression and regulation of cellfunction. Recent research also reveals that this is dynamic in nature.
This structure has been resolved by modeling at a molecular level and by
microscopy at cellular scale. However it has yet to be determined at an intermediate resolution. To fill this gap in knowledge, researchers combine distinct
techniques (light microscopy (FISH) and 3C-based experiments) to detect interactions across the genome which indicate proximity. The resulting contact
matrices can be computationally analyzed to build ensembles of probable conformations.
However there are still significant challenges given the increasing scale ofcomputational demands (calculation, storage, manipulation), the need for cohesive and coordinated research, and the aim for an integrated and reproduciblemodel of the whole genome. Web-based molecular graphics can assist in tackling
key aspects of these. The multiple scales of structure, organization and functionneed discrete visual description and inter-connection.
Yet diverse sources and types of data from which the graphics are derived
need to be typified and standard methods of integration agreed. Therefore identification of shared properties is important, and development of a new grammar
will help optimize visualization of structure and dynamics. There are also more
complex unresolved requirements, for example the display and navigation ofmultiple genomes, networks, data confidence, or phylogenetics.
These new representations must be developed inline with expertise and bestpractice in visualization and with awareness of the obfuscation inherent in 3D
images (see Tamara Munzner. Visualization Analysis and Design. A K Peters
Visualization Series, CRC Press, 2014). Existing popular genome browsers do
not comfortably integrate interaction or 3D data if at all. However there are anumber of new browsers based on these types of data which demonstrate various form of achieving such an comprehensive genomics tool: Juicebox, 3DBG,
Foldsynth, Genome3D, and our own TADkit.
5

Activities of wwPDB and PDBj towards multiscale structural biology
Haruki Nakamura & Gert-Jan Bekker, Osaka University, Japan
In recent years, the structures of very large macromolecular machines in cells
have been determined by combining observations from multiple, complementary experimental methods, such as X-ray crystallography, NMR spectroscopy,
cryo-EM, small-angle scattering (SAS), FRET, crosslinking, and many others.
Thus, so called ”Hybrid method” is going to provide us the biological systems
in the multiscale manner. Currently, many large structures (421 entries on
31 August 2016) determined by such hybrid methods appear in high-impactfactor journals, and are being deposited in the PDB (Protein Data Bank),
which is managed by an international organization, the wwPDB (worldwide
PDB: http://wwpdb.org/)). We will introduce the activities of the wwPDB and
PDBj to view those large structures, in particular using the web-based moleculargraphics, Molmil (Bekker et al. J Cheminform 8:42, 2016 DOI 10.1186/s13321016-0155-1), and will discuss several issues to be overcome.

From data to knowledge – exploiting macromolecular structure data
Sameer Velankar, EMBL-EBI, UK
The recent advances in structure determination technology have led to researchers being able to tackle large and complex problems at cellular and molecular level. As a result the Protein Data Bank (PDB) and Electron Microscopy
Data Bank (EMDB) have increasing number of depositions of large macromolecular complexes and it is expected that this trend will continue in the
future. The data archives and structural bioinformatics community, as a result, has the challenging task of delivering these large data sets to the user
community for data mining, data integration efforts and/or to the browser
based user interfaces for interactive visualisation. Providing seamless accessto datasets at cellular level and being able to investigate the molecules represented in those data sets at atomic resolution is a difficult task both interms of user interface design and delivery of data for interactive visualisation. At PDBe we have addressed the data delivery challenge by implementing
a server (https://www.ebi.ac.uk/pdbe/coordinates/) that allows users to dynamically select the subset of data they are interested in to ensure fast andinteractive delivery of molecular structure information. A prototype wherein addition to dynamic selection, compression of data to reduce the size ofdata packet is also developed and is undergoing testing. The coordinate server
makes these data available in mmCIF format, a stadard developed for representation of macromolecular structure data. Additionally we have developed REST API (http://www.ebi.ac.uk/pdbe/api/doc/) and web components(http://www.ebi.ac.uk/pdbe/pdb-component-library/) to display the biologicalcontext for the macromolecular structures. We have also developed LiteMol a WebGL based, interactive 3D viewer which is available of the PDBe pages(e.g. pdbe.org/1cbs) and is able to show both macromolecular structure data

6

and associated experimental results (Electron density maps for both diffraction
experiments and Electron microscopy structures).

Aquaria – Insight from protein structuresSeán O’Donoghue, CSIRO & Garvan Institute, Australia
Aquaria (http://aquaria.ws; O’Donoghue et al., Nature Methods 2015) is a
new web resource that streamlines and simplifies the generation of insight fromprotein structures. It has been designed to make structural information moreaccessible to life scientists who find existing resources too time-consuming to use.
The Aquaria interface is organized primarily by protein sequence, not structure.
For any protein of interest, Aquaria generates a concise visual summary of
all related PDB structures. Aquaria also allows mapping of domains, singlenucleotide polymorphisms, post-translational modifications and other sequence
features onto 3D structures. Users can also define and map their own sequence
features. Aquaria uses a minimal set of mouse-based controls that are intuitive
yet powerful. Aquaria can also be controlled via hand gestures using the Leap
Motion. Currently, Aquaria contains over 100 million pre-calculated sequenceto-structure alignments, resulting in at least one matching structure for 87% of
SwissProt proteins and a median of 35 structures per protein; this provides a
depth of sequence-to-structure information currently not available from otherresources. Recently, we used this database of structural alignments to map the’dark proteome’, i.e., the regions of proteins where molecular conformation iscompletely unknown (Perdigao et al., PNAS 2015).

Jolecule – protein viewer in the cloud
Bosco Ho, Monash University, Australia
Introduction to Jolecule (http://jolecule.com), a web-based viewer that focuses on annotations. It focuses on user interactions for structural biology, suchas a arrow embellishment to indicate chain direction, and depiction of the backbone peptide bond plane. There are several ways to find residues, and it’s easy
to add atom labels and distance measurements. The most distinguishing aspectof Jolecule is the ability to store annotations: specific views of a protein structure with explanatory text and labels. This is stored on a central server and iseasily available on any device.

Using CATH to predict the function of novel protein structures
Ian Silitoe, UCL, UK
CATH is a classification of protein structures: it groups together protein
structural domains that are related by evolution. This body of work (built over
20 years) has been used to predict the location of structural domains on over 50
million known protein sequences. When combined with functional annotations(such as UniProtKB, Gene Ontology, Enzyme Commission, etc), this information can be used to recognise sequence patterns (HMMs) observed during protein
7

evolution. In turn, these evolutionary ’fingerprints’ can be used to provide predictions of the structure and even function for new protein sequences. Allowing
scientists to interrogate these sequence, structure and functional annotations
in a clear and meaningful way provides a number of interesting visualisation
challenges.

SSBD: a database of quantitative data of spatiotemporal
dynamics of biological phenomena
Shuichi Onami, RIKEN, Japan
Recent advances in live-cell imaging analysis and mathematical modeling
have produced a large amount of quantitative data on spatiotemporal dynamics
of biological objects ranging from molecules to organisms. In this talk, Shuichi
discussed how these data are revolutionizing biological researches by showing
his group’s works on a large collection of quantitative data on nuclear division dynamics in early C. elegans embryos. Computational phenotype analysis
and inference of causal relationship of phenotype expressions were discussed inaddition to the power of interactive 3D visualization. Shuichi then gave an
overview of the SSBD database, which his group launched for storing and sharing quantitative biological dynamics data. Current technologies and problems
of web-based visualization of biological objects ranging from single molecules toorganisms were discussed Finally, Shuichi discussed future plans of the SSBD
database and possible collaborations with the web-based molecular graphics
research activities.

4

Breakout group discussions

4.1

Augmented Reality and Virtual Reality

This session investigated the current state of augmented reality (AR) and virtual
reality (VR) in web molecular graphics. We considered challenges, opportunities, use cases, and perspectives of these technologies for education, outreach,and research.
Recent capabilities and advancements in AR/VR hardware and experiences
have significantly revolutionized gaming and entertainment industries. Within
the past year, we believe this technology has reached several ’tipping points’, evident in the worldwide craze in applications such as Pokemon Go and Snapchat.
Although AR/VR technologies have been available for decades, the technology has often been labelled as ’gimmicky’, or one-off experiences with highwow-factor. With the introduction of affordable and effective low-end (Google
Cardboard, mobile AR) and high-end hardware (Oculus, HTV Vive, Hololens),
we discussed the importance of experience creation, delivery, and the powerof content-driven adoption. Authoring and designing experiences for molecular data include use cases in remote collaboration, education, outreach, andresearch.
In an effort to accelerate the ’tipping point’ for web molecular graphics, we
present a review of available web AR/VR authoring tools, successful content to8date, and available hardware1 .

4.2

Building Mash-Ups – Interoperability Requirements

While a plethora of excellent web-based molecule viewers exist, it is still achallenge to allow a user to dynamically annotate the viewer with additionalannotations that are relevant to the molecule viewing task at hand and to theuser’s field of expertise. The Web Molecular Graphics 2016 Shonan meeting”mash-up” subgroup has proposed a preliminary conceptual outline and logicalflow for establishment of a standard by which web-based molecular viewers candynamically enrich a molecule display with relevant annotations.
We considered the following motivation example: Next-generation sequencing (NGS) technology has matured to a stage in which it will be mass deployed
in clinics and hospitals around the world. Two common NGS results are genotyping for genetic variants in DNA (DNAseq) and expression of genes under aspecific physiological condition (RNAseq). A clinician, researcher, or patient
could benefit from a web-based experience in which the variants detected arepresented from several views:• A view of variants as mapped onto a view of the collection of chromosomes(chromosome global view).
• A highlighted view of the chromosome and gene region containing a specificvariant (chromosome global-local view).
• A view of which organs in the body express the gene (organism view).
• A view of drugs available that specifically target the variant gene being
viewed (pharmacogenomic action view).
• A gene subset view of patient gene expression in tissue samples analyzed(expression view) and comparison to case/control tissue (expression comparison view).
• An alignment of standard gene protein/nucleotide sequence versus patient
sequence (sequence comparison view).
A key challenge is how to present this information to a clinician in a format thatis compact enough that a clinical treatment decision can be made in minutes, aswell as how to allow interaction with one view to update the remaining views.
Using this example, we discussed the required technical building blocks tobuild such a mash-up. We envisaged a three-tier architecture:
1. The Data layer uses REST services to provide the required dat
2. The Mashup layer retrieves data from the data layer through the respective APIs and provides components for coordinate mapping and communication (e.g. about events) between different components. Coordinate
systems to be mapped are genomic, protein and structure coordinates.
1 https://docs.google.com/document/d/1Zf0kB4amYvnSkEAo2bTBSpMKjpvgcYXrqMkNtky
MKq09

3. The Visualization layer uses BioJS or specialised Custom Widgets to display the information and communicates with the Mashup layer throughan Event API.
In order to encourage cooperation between different components we recommend the establishment of a registry for the Mashup layer. Such a registry
should not only give a detailed (ontology-enhanced) description of the service,
but also provide means to ensure that the component is valid and responsive at
the time of query.

4.3

Mesoscale and Intermediate Representations

This group looked into the challenge of representing mesoscopic biological structures. Mesoscopic structures are biological objects which are too large to beresolved by methods used to determine protein structures, but also too small tobe resolved by standard microscopy techniques. These can include large protein
complexes and small organelles. Objects in this range present a general problem for visualisation because there are few datasets available, and there is alsoa lack of visualisation paradigms and solutions. Examples of mesoscopic structures can include viruses, nuclear pores, ribosomes, focal adhesion complexes,
etc.
Mesoscopic visualisation was of interest to the group for a variety of reasons.
This includes • Whole cell visualisation• Combining structure views with pathways• Combining mesoscopic and molecular visualizations/Viewing protein interactions in biological contexts• Drug development• Representations for audiences using storytelling• Moving beyond molecular views• Maximising use from electron microscopy data
This group discussed the current state of mesoscopic structure visualisation
paradigms, and addressed the challenges for visualising these objects. The main
challenges we addressed can be summarised as follows:
1. Mesoscopic structures can occupy a vast range of physical sizes - this canpresent a significant computational challenge since mesoscopic assemblies
could require very large numbers of data points to be represented, which
may place computational constraints on the possibilities for visualisation.
2. Mesoscopic data can be very heterogeneous - coming from a variety ofexperiment types and representing a range of structure types. This may
present technical challenges for visualisation.
3. Interactive, real time visualisation are highly desirable for mesoscopic visualisation, to allow exploration of complex datasets. This interactivity
also presents specific challenges.
10The discussions investigated strategies to tackle these challenges. The primary focus was on data formats that could accommodate interactive visualisations of large scale biological data sets. Some key themes emerged from these
discussions:• Lossy data formats are probably acceptable for mesoscopic visualization,
as they prioritize scale, interactivity and dynamic range over accuracy.
• Formats which contain a range of representations for different zoom levels are desirable, as they provide on demand detail when zoomed in on
small structures, but should allow rapid transitions to zoomed out views
containing large numbers of objects.
Some basic file reduction procedures are of interest to make mesoscopic visualisation more practical.
1. Representations which feature only backbone trace or 1 or 2 point residue
use can still represent overall protein structures while reducing file sizes,
but sacrificing some molecular detail
2. Gaussian mixture models may be particularly interesting to vastly reducethe complexity of displayed objects, while still representing the overall
shapes of objects2 .
3. Creating surfaces and then reducing the surface count using decimation
procedures may be necessary for surface style representations Volumetrics
could be interesting, but may be more computationally expensive. Perhaps
looking at representations of astronomical datasets could help inform thissort of practice.

4.4

3D Rendering and Representation of Molecular Structures

In our breakout group about rendering and representing molecular structures
we identified a set of challenges common to most molecular graphics tools.
Related to providing interactive rendering are: perception of smooth interaction; leveraging increased parallelism of modern computers; providing scalable
performance given highly variable resources on desktop and mobile machines.
Scalability becomes an issue with a growing number of objects to be rendered
and when data is dynamic in nature. In terms of visual quality, transparency,
anti-aliasing, shadows, and ambient occlusion are important factors. The web
lacks reusable (standard) implementations for many common algorithms usedin molecular graphics, including electron density handling, structure/sequencealignment and generally calculation of derived features such as molecular surfaces and volumes. Apart from those more technical challenges, there are many
open question regarding representing variability and ambiguity: how to show
comparisons, highlight differences; how make the user aware of incomplete data
and uncertainty therein; how to make alternative ensemble and dynamic data
accessible. Another question is how to efficiently annotate 3D structures withdata from other sources to show spatial relationships.
2 See http://www.sciencedirect.com/science/article/pii/S0006349508786041

11

We discussed potential solutions or at least approaches to/for some of thosechallenges. If data gets too large to download or render all at once one canmove to a client-server architecture. This can for instance allow access to large
molecular dynamics trajectories by only loading and rendering parts the user
wants see at the same time. With respect to representing data in appropriate
ways we found that there are a number of non-standard representations that arevery useful but not widely available. Those include Bendix, Hyperballs, Molecular Surface Maps, 2D Maps of Channels, Abstractions for Sugars and Lipids,
Volume Rendering, Directional Arrows on Backbone Atoms (e.g., showing thedirection of the amino acid chain).
We find that there is a large gap between computer graphics research andits application in life sciences. This is especially true with respect to the technical rendering challenges, but also innovative representations. In the worldof desktop applications it took 10 years and more for techniques developed incomputer graphics research to find their way into tools used by life scientist.
For the web, we don’t want to wait that long. Therefore we are proposing tocreate Modular Molecular Graphics (MMG.js), a low level library for modular
molecular graphics. The idea for that library is that it would provide a common
platform for joint development and collaborations between computer graphics
researchers and application developers from life sciences to bring state of theart rendering to the user. Such a project could evolve around a github projectand raise awareness through a homepage, mentioning in articles and posters aswell as through personal invitations of potential collaborators from both fields.

4.5

User Experience Best Practise

Over the past decades, molecular graphics systems have been developed to address a wide variety of user scenarios, and using a diversity of languages, operating systems, and user interface paradigms. The emerging web moleculargraphics systems are likely to be used for an even more diverse range of applications, many not possible previously (e.g., multiscale interactive navigation frommolecular to cellular or even tissue scales).
However, in contrast to previous work, web molecular graphics will havea common language (JavaScript) and platform (browser) – and are therefore
more likely to share commonalities in the user experience (UX) than previous.
There is therefore an opportunity for de facto standards in user experience toemerge, blending existing web standards and the best of breed pre-existing conventions from existing stand-alone browsers. That will enable users unfamiliar
with molecular graphics to be more easily ’onboarded’, and to learn to use andgain insight from 3D structural information. For expert users, good de facto
standards will enable them to more quickly learn new applications, thus broadening the scope of analysis tools in their arsenal. Our goal in this breakout was
to explore these possibilities, with the aim of articulating a set of user experience
best practises.
As a preliminary step towards a planned publication that articulates key
elements of such a de facto graphical user interface, we discussed that it could
include:• A default ’minimal’ mode with only the most essential GUI elements.

12• Specialized modes for specific types of exploration, e.g., dynamics trajectories, or small molecule interactions.
• Enhancing orientation awareness using graphical metaphors such as, forexample, the ’View Cube’ from 3D Studio Max.
• Easy access to sets of pre-calculated canonical orientations.
• Use 3D controls familiar to 3D gamers, e.g., via keyboard ’numpad’ controls.
• Enhancing perception of depth cues, e.g., by y-axis rocking.
• Intuitive yet sophisticated selections using familiar GUI conventions.
• Color conventions that account for color blindness, as well as for limitations in normal color perception.
Another key element of molecular graphics tools is the selection and scripting language; as a preliminary step towards a Common Molecular Modeling
Scripting and Selection Language’, we identified key goals and features such alanguage would have, including:• Compact• Expressive• Easily parsable• Encodable (URLs, filenames, etc.)• Human readable• Extensible to large, multi-scale• Efficient• Hierarchical• Supports boolean combinations - e.g., A and (B or not C)• Pre-defined keywords (e.g., ’protein’, ’ligand’, etc.) built from primitives.
• Operators• Wildcards.
Finally, we anticipate that web molecular graphics systems will often bepart of an ecosystem of ’mash-ups’; this will greatly facilitated by defining arich set common of inter-application communication. The challenge of defining
and communicating this context can be broken down:• defining a set of predefined common scientific contexts (e.g. ”small molecule
chemistry”)• deciding on a common ontology

13• defining a data structure that describes context (minimum amount of information, optional extras)• allowing this context to be easily integrated with existing tools.
A number of factors need to be taking into account when communicating
information about the scientific context in which a particular user is interested:• privacy• user may be interested in more than one context• user may not want suggested views imposed upon them (always allow”default settings”)• the definition of ”context” would need to grow (without breaking existing
tools).
Expecting developers to implement and maintain all these different views
into their individual resources would represent an unrealistic amount of work.
However, rather than developing their own pages, we would encourage resource
developers to reuse existing web components to provide views such as 3D rendering of protein structure. This way the task of understanding and communicating
scientific context would be left to a small number of developers on an opt-in basis. This would represent an entirely tractable problem and could provide an
extremely useful tool for the community.

4.6

Chemoinformatics

The ”Chemoinformatics” breakout group discussed visualisation challenges specific to interactions between proteins and small molecules – which range fromobtaining an overview of large dataset of protein-ligand interactions over visualising specific physico-chemical interactions within the protein structure tocomparing different ligand poses, but also include the challenge of displaying
and building chemical compounds in a 2D sketch as well as a probable 3D conformation.
As a unifying scenario that includes many of the above challenges, we proposed to build a framework that can create an interesting, educational, andinteractive experience for students to understand the basic concept of a ligand
successfully docking into a receptor. Students interested in clinical medicine
and medical science would benefit from understanding the biophyiscal, pharmacological, and other related aspects of a small molecule binding into a large
receptor. An interactive experience should allow a student to design a ligand
interactively and test its spatial and electrostatic compatibility.
As a result of the discussions we developed an outline for how to build sucha system as well as a plan how to fund this joint project.
We also produced a wish-list of features molecular viewers should implement
in order to enhance the usability for more detailed analyses of chemical interactions. For some of these features we were able to cases we suggest possible
solutions (based on Bob Hanson’s implementations in Jmol), others would benefit from suggestions of visualisation experts on how to achieve the intended
aim:

14

• Visualisation of surfaces:– show iso-surfaces for energy maps
– simultaneously visualise multiple surfaces with quick on/off switch– see pockets and surfaces without obscuring chemical detail – suggestion: use separate slab for surfaces• Visualisation of clashes – suggestion: colour the molecular surface by theamount of the van-der-Waals overlap• Visualise H-bonds so they are distinguishable from covalent bonds – suggestion: show H-bonds as disks or small surfaces in the areas of the vander-Waals overlap• Visualisation of electrostatic interactions: difficult because that would require displaying electrostatic fields of the interaction partners – suggestion:
coordinate with a 2D view (in a mash-up display) that shows electrostatics

4.7

Review of the State of the Art

Participants: Mike Goodstadt, Shuichi Onami, Björn Sommer, Jenny Vuong,
Merry Wang, W. Jim Zheng
Visualization in molecular biology has played an essential role in revealingmechanisms of biological function. Our ability to visualize molecular interactions at the atomic level is astonishing. For many cases, 2D visualization
will suffice, but there remain many biological systems where 3D visualization
is essential: the exploration of 3D genomes, proteins, membrane patches andsimulations, vesicles, metabolic reactions on the atomic scale, etc.
In the past, the dissemination and exploration of three-dimensional models
was limited, as visualizations of models were prepared on specialist equipment,
and then distilled into publication figures. For complex operations, specialized
tools were required for the visualization of these models.
Today, we are poised to enter an era of unprecedented access to 3D visualizations of biological molecular systems. This is due to the maturation of a numberof technologies: 1) commodity graphics cards, 2) JavaScript in web browsers, 3)
the WebGL standard and 4) distributed data delivery. In this breakout session,
the initial manuscript was discussed which focuses at the web representationof molecular graphics in the browser. The initial idea for this manuscript goesback to an initiative starting at the VizBi 2016 with Seán O’Donoghue andBjorn Sommer, and later extended by Bosco Ho and Xavier Ho.
With the break out session group, the structure of the paper was discussed
and improved. Whereas the initial manuscript was focusing only on web tools
visualized with WebGL and JavaScript, it was decided to discuss also relevant
tools that are still based on older technologies, such as Java applets. A good
example is Jmol, which was used in the past as a Java applet, but nowadays isalso available for the web as the web version JSmol. Still, tools like Aquaria are
not fully implemented in WebGL.
The basic chapters for the manuscript were fixed as follows:• Introduction (with history, from Java Applets to WebGL)

15

• Methods (Technical Background: OpenGL, JavaScript, WebGL)• Frameworks (such as ThreeJS and Unity3D; with table)• Applications (Jmol, JSmol, Aquaria, Jolecule, etc.; with table)• Data Formats• Conclusion• Outlook
A big advantage of the workshop was the fact that many developers of thedifferent tools were available on site, so we decided to prepare the tables required for the final publications by directly confronting the developers with
our questions. The result is an initial table that will be later revised by all
co-authors.
The actual plan is to involve all attendees of the workshop to use the paper
as a global outcome of the workshop, with a future outlook based on the workof the other breakout sessions.
One basic outcome will be the idea that there should be a basic framework,
such as three.js, which is optimized for molecular graphics and which can beused by all other programmers as a base, which is then extended by their custom
functionalities.
The initial manuscript should be finished by middle of October, and the idea
is to submit the full manuscript until the end of this year.

16

5

List of Participants• Marc Baaden, CNRS, France• Gert-Jan Bekker, Osaka University, Japan• Spencer Bliven, National Center for Biotechnology Information, USA• J.B. Brown, Kyoto University, Japan• Matthieu Chavent, University of Oxford, UK• Mike Goodstadt, Centre Nacional d’Anàlisi Genòmica - Centre de Regulació Genòmica (CNAG-CRG) , Spain• Christopher Hammang, Garvan Institute, Australia, Australia• Bob Hanson, St. Olaf College Chemistry, USA• Bosco Ho, Burnet Institute, Australia• Michael Krone, VISUS, University of Stuttgart, Germany• Haruki Nakamura, Osaka University, Japan• Shuichi Onami, Riken Quantitative Biology Center, Japan• Seán O’Donoghue, CSIRO & Garvan Institute, Australia• Alexander Rose, UC San Diego/ RCSB Protein Data Bank, USA• Peter Rose, UC San Diego/ RCSB Protein Data Bank, USA• Andrea Schafferhans, Technische Universität München, Germany• Ian Silitoe, University College London, UK• Bjorn Sommer, University of Konstanz, Germany• Christian Stolte, New York Genome Center, USA• Baichuan Sun, CSIRO, Australia• Hirofumi Suzuki , IPR, Osaka University, Japan• Sandhya Tiwari, Riken, Japan• Sameer Velanker, PDBe, EBI, UK• Jenny Vuong, CSIRO Australia, Australia• Merry Wang, Autodesk Research, Canada• Jon Wedell, BMRB, Wisconsin-Madison, USA• Philippe Youkharibache, National Institute of Health, USA, USA• Jim Zheng, University of Texas Health Science Center at Houston, USA

17