A community proposal to integrate structural bioinformatics activities in ELIXIR (3D-Bioinfo Community)

3D-Bioinfo Executive and Steering Committees

The 3D-Bioinfo Community includes leading figures in the field of structural bioinformatics across Europe. It was initiated in March 2018 with the formation of a Steering Committee and an Executive Committee comprising representatives from 16 ELIXIR nodes. These members actively sought further participants from within their nodes, covering a wide spectrum of skills and needs (see European groups participating in 3D-Bioinfo). They are responsible for the development and sustainable operation of complex tools ranging from databases to infrastructures promoting interoperability between multiple areas of research that rely on the reusability of structural data provided by the structural biology community (e.g. as represented by Instruct-ERIC).

Description of the launch meeting

3D-BioInfo was launched at a meeting in Basel, September 2018, with 70 participants from 15 European countries providing their input. In addition to presentations from committee members on the proposed 3D-Bioinfo Activities, representatives of the five ELIXIR platforms on data, tools, interoperability, compute and training, described their activities. John Hancock also gave a presentation as Coordinator of ELIXIR Communities and representative of the ELIXIR hub. Additionally, 19 ‘flash talks’ were given by European research groups interested in contributing to one or more of the proposed 3D-Bioinfo activities and/or to joint activities with the ELIXIR platforms. Organisers of related ELIXIR communities (proteomics, intrinsically disordered proteins and human copy number variation) gave presentations indicating possible areas of future collaboration. There were also oral contributions from representatives of other European ESFRI initiatives like Instruct-ERIC and BioExcel, again highlighting synergies and possible collaborations. Posters from many research groups, keen to participate in 3D-Bioinfo, were presented at the meeting highlighting their possible contributions and an interactive session was held allowing participants to discuss the proposed Activities and suggest future Activities. Participants also discussed ideas for interaction with the ELIXIR platforms.

Activity I: Infrastructure for FAIR structural and functional annotations

Coordinator: Sameer Velankar. The Protein Data Bank (PDB) and the Electron Microscopy Data Bank (EMDB) both follow the FAIR principles, thus enabling many niche data resources to derive added value annotations from the archived structural data, such as structure domain classifications, information on ligand- and macromolecule binding sites and effects of mutations on structure and function. However, a lack of coordination between these specialist data resources has prevented the creation of data standards and uniform data access mechanisms, consequently reducing the impact of these valuable data.

The proposed Activity will address these omissions by further developing the PDBe Knowledge Base (PDBe-KB) – a community-driven data resource for structural and functional annotations that places structural data in its biological context. PDBe-KB increases the visibility and interoperability of niche data resources by collating minimally required common structure-based annotation data in a standardized data exchange format and by enabling comparisons between specific types of annotations obtained from different software tools.

The initial focus of this Activity will include three major goals: i) continue to expand the scope of integrating known and predicted functional site annotations with PDBe-KB; ii) integration of annotations concerning the impacts of disease-associated variants on structure and function in PDBe-KB; and iii) integration of predicted protein structure data via existing model archives by establishing a federated infrastructure for access (3D-Beacons).

Identifying additional predicted or manually curated annotations that could further enrich the integrated data of PDBe-KB: The lack of data standards and fragmented nature of specialist data resources is a barrier to the FAIR principle. We will bring together the community experts to define data standards for different types of annotations and integration of these annotations using a community-driven data exchange format will facilitate finding, accessing and reusing sparse annotations in an interoperable manner. Activity I will ensure that PDBe-KB will be an effective platform for the collaborating partners to share and compare their value-added, structure-derived annotations. Furthermore, we will continue to identify gaps in coverage of the various types of annotations in PDBe-KB and bring together community experts to fill in those gaps. The workshops will also facilitate the development and testing of new methods by providing valuable, standardized benchmarking data sets.

Integration of annotations related to the impacts of disease-associated variants on structure and function: By bringing together developers of specialist data resources and scientific software tools that can provide information on the effects of amino-acid variation on structure and function, we will establish data standards to represent these data. The data standards will support integration of these annotations in PDBe-KB with particular emphasis on the effect of disease-related mutations on conformational stability. Compiling and integrating these annotations will be highly beneficial when investigating naturally occurring variations, and when used together with all the other types of integrated annotations it may facilitate development of better tools ultimately benefiting the wider biomedical research community.

Integrating predicted protein structure models (3D-Beacons): Taking advantage of the highly interconnected data of PDBe-KB will allow the transfer of valuable annotations to structural models based on sequence- or structural similarity when experimentally determined structural data is unavailable. Development of 3D-Beacons infrastructure by incorporating structural models from existing European archives (e.g. SWISS-MODEL³¹, Genome3D⁴⁰) and other international resources (e.g. MODBASE⁴¹ and Gremlin⁴²) will facilitate an increase in the coverage of structure data in the sequence space. The PDBe-KB data alongside the predicted structure models will potentially allow the scientific community to gain valuable insights regarding the biological context.

The focused activities will take advantage of the existing PDBe-KB infrastructure, and will include developing community-driven data standards and a uniform data access mechanism in addition to novel, portable and distributed web-based visualisation components. Activity I will build on existing collaborations involving five ELIXIR nodes (UK, Italy, Spain, Czech Republic, Belgium).

Activity II: Open resources for sharing, integrating and benchmarking software tools for modelling the proteome in 3D

Coordinator: Shoshana Wodak. Activity II is about empowering the scientific community to extend the current information on protein 3D structures, protein interactions and assemblies, and extract knowledge from this information by using computational and bioinformatics methods, and integrating biological data from different sources. Its initial focus will be on software tools and benchmark datasets for modeling the 3D structures and conformational flexibility of proteins and protein assemblies, and on community-wide benchmarking activities that advance the field. This focus will subsequently be broadened to include other areas where 3D modelling of proteins and their interactions is most impactful. The following specific aims will be pursued.

Extend the content of OpenEBench by adding a knowledge base integrating software tools for modeling the 3D structure of proteins, protein complexes and assemblies. A variety of software tools are available for modeling protein structures and protein complexes by exploiting available protein sequence data and information on known structures in the Protein Data Bank (PDB). Exploiting these data successfully involves integrating the appropriate set of tools for the problem at hand. The Community will tap into OpenEBench a knowledge portal fostering benchmarking in the life sciences domain and an important component of the ELIXIR Tools Platform, with exemplary datasets of CAMEO and CAPRI already present. The extension will include workflows and guidelines to software tools and servers for modeling protein structures and complexes, based on known structures (templates) in the PDB. More specifically tools for template-based modeling of protein assemblies, and for Integration of template-based modeling of individual subunits, with protein-protein and protein-peptide docking servers developed by members of the CAPRI community. For a more in-depth understanding of the resources please refer to the CAPRI and CAMEO websites. 3D-Bioinfo will build on these efforts and take them to the next level.

Develop a set of standard freely available tools for evaluating the quality of 3D models of proteins and protein complexes. Evaluating the quality and accuracy of 3D models of proteins and protein complexes plays a crucial role in evaluating the performance of molecular modeling methods, and helping methods developers to optimize their procedures. Furthermore, to effectively compare the performance across methods, agreed upon standard quality measures and evaluation protocols are necessary, as implemented for single protein models by CAMEO modeling (3D), the CAMEO Quality Estimation (QE) category and for protein – protein complexes by the CAPRI community. Major goals will include:

1) Full automation of the CAPRI quality assessment procedures for models of protein-protein and protein-peptide complexes, and larger assemblies and making them widely accessible online and for download,

2) Integration of the CAPRI and CAMEO model quality assessment tools,

3) Making the integrated tools available as open software through a community repository (e.g. on GitHub, building on the GitHub established by the CAPRI community).

Develop a one-stop-shop of benchmark datasets for testing and evaluating methods for generating scoring, and ranking models of protein complexes. The availability of appropriate benchmark datasets has been crucial for the development of protein modeling procedures at all levels. Protein docking benchmarks, which assemble high resolution 3D structures of selected sets of known protein complexes and their components^43,44,45 as well as their experimentally measured affinities^46,47, have been widely used for benchmarking methods for protein-protein docking, and for predicting and scoring protein interaction interfaces. The OpenEBench project within ELIXIR-EXCELERATE (OpenEBench.bsc.es⁴⁸) has established a transparent data model that allows not only the sharing of benchmarking datasets, but also analyzing and comparing the performance of different prediction algorithms on these datasets.

OpenEBench will thus foster a collection of benchmark datasets relevant to the field of modeling the 3D structure of monomeric, homo-oligomeric and heteromeric protein complexes, extending to proteins - peptide and protein - nucleic acid interactions. It will include: 1) protein docking and affinity benchmark datasets developed by members of the CAPRI community, 2) datasets comprising all the predicted models of protein assemblies submitted to CAPRI and CASP blind prediction challenges, following the examples of the Score-Set⁴⁹ derived from predicted models submitted to CAPRI, 3) a dynamic benchmark for protein complexes beyond binary interactions, considering different difficulty levels (See DynBench3D;⁵⁰). In addition a mechanism will be developed for users to contribute datasets⁵¹, following well-defined community-approved standards such as the mmCIF based modeling extension developed in collaboration with the RCSB within the macromolecular ModelArchive.org project.

Develop the infrastructure to manage the CAPRI challenge, in coordination with CAMEO. For CAPRI: Develop automated registration and submission procedures (including automated validation of compliance with standard format), as well as tools for accessing and navigating target information, predicted models and prediction results on the CAPRI website. Work on these tasks is currently underway at CAPRI-EBI, but further support is needed to complete it. For CAMEO: CAMEO is currently adding a new category for heteromeric complex modeling. We propose a close collaboration with CAPRI concerning the prediction and scoring applied during fully automated evaluations.

Develop a knowledge portal to user-friendly bioinformatics and computational tools for modeling conformational flexibility of proteins. Adequate modeling of conformational changes is currently a major bottleneck in protein assembly modeling. To foster progress an important first step would be to develop a knowledge portal offering the modeling community at large, workflows and guidelines to various available computational and bioinformatics tools for modeling conformational flexibility. We will use the bio.tools registry established by the ELIXIR Tools Platform as infrastructure for this. bio.tools has tags, one of which is structure prediction, but it should be possible to add more customized tags. With such tools playing an important role in modeling intrinsically unstructured proteins, collaborations with the ELIXIR Community on protein intrinsic disorder on topics of common interest will be undertaken.

Activity III: Protein-ligand interactions

Coordinator: Vincent Zoete. The biological activity of biomacromolecules is often linked to the three-dimensional recognition and binding of small molecules such as substrates, activators or inhibitors. Indeed, a large fraction of drugs are ligands targeting macromolecules like enzymes, receptors, transporters or ion channels. Consequently, important efforts have been dedicated to develop computer-aided drug design (CADD) and notably structure-based drug design (SBDD) approaches over the last decades, contributing significantly to the design of small molecules of therapeutic interest.

The field of drug discovery and development will face several challenges in the future. The on-going needs in medicinal chemistry prompts a dramatic demand for new molecular entities and the exploitation of chemical spaces that are yet unexplored. Despite important progress over the last few decades, toxicity issues remain a problem for small compounds. This has to be addressed through increased specificity, but also via a better characterization of the possible targets and the anticipation of multiple off-target effects. Toxicogenomics, pharmacogenomics, and phenotypic screening data should be collected, organized and disseminated to get a clearer overview of biomacromolecule-ligand interactions, and to ultimately predict in silico the poly-pharmacology of the compounds. New target classes are also emerging, beyond the usual well-defined binding pockets, including among others the interaction of proteins with other proteins, nucleic acids, lipids or sugars. These additions in the target classes are mirrored by the use of new classes of ligands, including peptides and macrocyclic compounds. These new types of target-ligand interactions will foster the development of novel in silico approaches, which will require new algorithms and thorough evaluations of their descriptive and predictive capacities.

Among other in silico technologies, structure based drug design (SBDD) methods remain in great need of comprehensive evaluations of their performance and domain of applicability. In particular, there is a need for improved docking and scoring methods. Although protein-ligand complexes can be predicted for small ligands and almost rigid proteins, large, flexible molecules like peptides or macrocycles and proteins with flexible binding regions are still very difficult to handle. The reliable prediction of the binding free energy of a protein-ligand complex also remains a major challenge. Better methods making use of precise chemical models, modern optimization techniques and innovative scoring approaches are still much needed but must be accompanied by comprehensive and rigorous evaluations of their performance and domain of applicability. This should go hand in hand with the creation of processing pipelines for the proper use of structural data, and of standardizing tools for IO.

The efficiency of SBDD tools often depends on molecular/physicochemical properties such as the charge, polarity or size of the protein binding site and ligand, as well as on the target class of the biomacromolecule or the chemical class of the ligand. To address this, benchmark sets should clearly list and quantify these different properties for each complex with suitable descriptors, transparent for the user community. For Activity III, we plan the following goals:

Creation of benchmark datasets to assess structure-based drug design tools. Benchmarking studies performed so far, including those carried out in the CSAR⁵² or D3R Grand Challenge⁵³ which focus on compound series consistently measured within one lab/institute - rely on datasets of limited size and diversity, precluding large-scale, FAIR comparisons of their performance, especially as a function of ligand and binding site properties. Activity III will therefore involve:

1) Building benchmark datasets, extracted from the PDB and curated, for assessing SBDD tools on a large-scale, under well-defined FAIR conditions, thereby complementing efforts such as the D3R grand challenges. A particular effort will be devoted to collecting complexes involving peptides and macromolecules.

2) Quantifying different properties (e.g. charge, polarity, size, flexibility of the binding site and ligand etc.) for each entry in the benchmark, to enable evaluation of SBDD tools as a function of these properties.

3) Developing links to other databases and standardizing the retrieved data to complement the information provided for each protein-ligand complex in the benchmark sets; notably, collecting information on ligands in collaboration with PDBe-KB, and associating complexes with reliable binding affinity data using databases like ChEMBL⁵⁴ and Pubchem⁵⁵.

4) Adding information on the non-bioactive conformations of ligands to standardize the comparison of docking calculations starting from such geometries.

5) Adding information on experimentally determined non-active compounds (taken e.g. from ChEMBL⁵⁴) to be used as negative examples for testing virtual screening procedures.

Dissemination and promotion of the benchmark datasets and results. Benchmark datasets will be made publicly available by following Open Access and FAIR principles via a collaboration with the OpenEBench project within ELIXIR EXCELERATE. The latter will also allow the sharing of benchmarking results, and comparing the performance of different prediction algorithms under FAIR conditions. Preferred standardized benchmark workflows and protocols will be published, to guarantee an objective comparison of different tools. Researchers will be encouraged to evaluate their preferred sets of SBDD approaches using the above-mentioned standardized benchmarking workflows and protocols, and to report their results. We will collect the latter and provide them to the community. This activity will be of major value to Pharma and Biotech researchers, who acknowledge the importance of standard benchmarking protocols.

Biomacromolecule-ligand interactions for every scientist, educational aspects. Despite significant interest in using modelling approaches among life scientists, the use of biomacromolecules structures in molecular design largely remains a domain for experts. However, complex data preparation and association could be largely automated resulting in easier-to-use software and substantially lowering the usage barrier for life scientists. By encouraging the development of tutorials guiding the application of modelling and the interpretation of the achieved results, we will endeavour to open the world of structure-based modelling to the broader life science community.

Activity IV: Tools to describe, analyse, annotate, and predict nucleic acid structures

Coordinator: Bohdan Schneider. The ultimate goal and vision of Activity IV is to encourage development and use of software tools to describe, analyse, annotate, and predict nucleic acid (NA) structures. The availability and sophistication of tools dealing with various hierarchies of the nucleic acid structure lag behind the tools used to explore protein structures and this situation must be remedied. In particular, standards are needed for initial model building and refinement of nucleic acid molecular structures. This task has become urgent as new techniques, including, but not limited to cryo-EM, are generating experimental data on 3D structures containing RNA and DNA molecules, such as ribosomes, spliceosomes, polymerase assemblies, and histone complexes, faster than ever before. The modelling of large nucleic acid molecules into low-resolution electron densities is particularly challenging. The RNA structural bioinformatics community has provided prototype tools, with which to model RNA and RNA-protein complexes based on experimental data, but these tools are currently not compatible with community-wide standards describing RNA and DNA conformational space and geometry at the local (nucleotide or dinucleotide) levels.

Therefore, efforts need to be directed towards formulating community-accepted benchmarks that integrate the different levels of nucleic acid structure descriptions, and more generally to improving software tools that describe, analyse, annotate, and model nucleic acid structures. To enable these developments, Activity IV will focus on the following specific goals:

1) Cataloguing software tools for building nucleic acid models based on their sequences alone as well as for modelling their 3D structures using experimental data, and facilitate integration of these tools.

2) Coordinating the unification of the existing NA geometry standards and formulate specifications for missing standards.

3) Developing benchmarks dataset for evaluating the quality of predicted or experimentally determined NA structures.

To limit the redundancy and increase the synergy between the methods, databases, web services, and other tools, we plan to continuously update the catalogue of software tools developed by the RNA tools and software consortium, extend these tools to DNA structures and enable integration of emerging tools. These efforts will build on existing ontologies while preserving consistency with new extensions.

This integration effort will require a significant level of interoperability between data exchange protocols and software, which will be implemented following FAIR principles. Dealing with software to solve, model, and refine NA structures based on the experimental data will require a close collaboration with experimentalists. Hence joining forces with Instruct-ERIC will be essential, for reaching all the stated goals, including the development of benchmarking tools and standards.

We list a few examples of steps, which could assist useful integration of the existing tools:

1) Adding links from existing servers to other tools, especially those linking 2D and 3D structure prediction. The RNA Tools and Software Consortium have already recapitulated methods for RNA secondary structure prediction and to some extent RNA 3D tools. The RNA Puzzles community of RNA structural bioinformaticians^16,17,18 has developed a set of tools for linking 2D and 3D structures, software for RNA 3D structure model evaluation also exists, e.g. RASP⁵⁶ or MacroMoleculeBuilder, MMB⁵⁷.

2) Unifying the libraries of RNA/DNA dinucleotide fragments based on the analysis of experimental structures^58,59 and trinucleotide fragments⁶⁰. Ultimately, the community should reach a consensus on what is the meaning of “preferred”, “allowed” and “wrong” conformers in analogy with the use of these terms in the Ramachandran plot.

3) Integrating and benchmarking methods dealing with RNA structures, e.g. SimRNA⁶¹, RNAComposer⁶² MMB⁵⁷, FARNA/FARFAR⁶³, Web-Beagle⁶⁴.

4) Strengthening the collaboration with developers of the main experimental nucleic acid structure determination software tools (e.g. REFMAC⁶⁵, COOT⁶⁶, Phenix⁶⁷, PDB-REDO⁶⁸) to encourage consistent handling of NAs.

The goals of Activity IV are quite ambitious, and their implementation will require close and friendly collaboration of all research teams willing to participate; including the teams involved in this Activity, and other teams active in the field. The teams not involved in Activity IV will be encouraged to join. Successful completion of the stated goals will also depend on the close collaboration of scientists grouped under other infrastructure projects in Europe and beyond. New tools, standards and benchmarks developed for NA validation will be communicated to the experimental structural biology community, mainly Instruct-ERIC but also EuroBioImaging, to ensure consistency across the different research communities.

As a part of the 3D-Bioinfo Community, we plan to hold regular meetings and workshops and web conferences, to informally discuss progress and help identify problems that can be addressed collectively. Unlike other 3D-Bioinfo Activities, Activity IV involves a relatively new community that is less well established and will require organising workshops to encourage collaboration and to enable updating of tool catalogues and ontologies. As with the other 3D-Bioinfo Activities, we will coordinate organisation of the workshops with the ELIXIR’s training portal TeSS where appropriate. The first workshop of the Activity IV is going to take place in May 2020.

Future 3D-Bioinfo activities

The above mentioned themes will not only form the initial focus for 3D-Bioinfo but the steering committee will actively monitor the emergence of new technologies and/or new research fields relevant for bioinformatics approaches, which then can be fostered further as new activities. For example, in the field of protein design the overarching aim is to enable completely rational design of proteins with customized biological functions e.g. novel biocatalysts for Green Chemistry to meet sustainability and environmental challenges. In order to foster new developments focused courses/workshops will be organised on such topics. For example, a course or workshop on using biocomputing to understand and engineer biocatalysis is being planned. 3D-Bioinfo will continuously seek to integrate biocomputational efforts with experimental studies in order to systematically generate, test and critically assess new hypotheses on the fundamental properties of highly active enzymes and binding proteins. This would very much increase our quantitative understanding and enhance the capabilities for the rapid generation of binders, inhibitors and biocatalysts for a range of applications in research, technology and medicine.

Alignment with the ELIXIR platforms

All the above 3D-Bioinfo Activities will engage with the ELIXIR platforms as described below.

Interoperability platform – The outcomes of our projects must be easy to discover, to access and to integrate into users’ pipelines. This necessitates the use of standardised file formats, metadata, vocabularies and identifiers. We plan to include our resources in FAIRshairing and Identifiers.org. For all Activities we will organise community workshops to develop data exchange and retrieval standards to improve compliance with FAIR principles. Participating teams will also adopt BioSchemas⁶⁹, a European led initiative. For example, different community-wide standards for evaluating predicted models of proteins and protein complexes would be integrated to promote community-wide use. FAIR-ification of benchmark datasets will be undertaken. To implement the 3D-Beacons infrastructure, we will implement a common API specification for macromolecular structure data from both experimentally determined and predicted models. Where possible, the services and tools will also be linked via workflows using common workflow language to help with interoperable workflow software development.

Data platform – We will link key structural bioinformatics data resources to drive the use and re-use of data. For example, data from five UK based structure prediction resources have already been integrated via Genome3D, and ELIXIR implementation studies are already supporting further integration of the data in Genome3D with data from SWISS-MODEL, developed by the Swiss node. In addition, Activity I will be responsible for the integration of data on known and predicted functional sites, from a large number of participating European groups, in PDBe-KB. Information on the structural impacts of genetic variations predicted by multiple groups will also be integrated and novel visualization strategies for presenting this integrated data will be developed. These will need to clearly distinguish between experimentally known and predicted data. Activity II will be responsible for integrating various benchmark datasets on predicted protein complexes and assemblies, and on experimentally determined complexes annotated with data from other sources (in close coordination with Activity I). Activity III will also integrate benchmark datasets. For example, we will establish Open Access benchmarks sets under FAIR principles, for assessing structure-based drug design applications. This must be done in a robust, sustainable and scalable data ecosystem, allowing the use and re-use of the data, in line with the ELIXIR Data Platform goals.

Tools platform – The participating tools and resources will be registered in BioTools to make them discoverable and sustainable. Currently, there are several hundred tools relating to structural bioinformatics registered in BioTools covering a range of themes. Extending the repertoire of structural bioinformatics tools in BioTools will a) ensure reproducibility, b) allow scaling up by working in cloud environments, e.g. EOSC c) make tools widely available and sustainable for non-expert users. Containerization of these tools in BioContainers will support development of complex workflows. We will use the benchmarking infrastructure OpenEBench to assess tools and help methods development. For example, all tools related to Activity I will be registered in BioTools and the developers will have the opportunity to access expertise on containerization; for Activity II, these will incorporate exemplary datasets from CAMEO and CAPRI. Workflows for modeling protein conformational flexibility and for modelling protein assemblies in the context of Cryo-EM structure determination will be designed in collaboration with respectively, BioExcel and Instruct-ERIC. The development of improved tools for validation of nucleic acid models in Activity IV feeds directly into this platform and all new methods will be registered with BioTools.

Compute platform – The ELIXIR Authentication & Authorisation Infrastructure (ELIXIR-AAI) which connects to other European AAI initiatives like EGI-CheckIn, INSTRACT ARIA, will be adopted to support depositions. We will link with the compute platform activities to address scalability of the underlying infrastructure for data transfer as well as data access. For example, access to the ELIXIR compute infrastructure and to the European Open Science Cloud resources (EOSC-Hub) will be explored, to enable large-scale assessment of predicted models of protein assemblies in CAPRI prediction rounds, and to disseminate software tools and web-services. Similarly, groups providing large-scale protein structure predictions and variant impacts will seek to benefit from access to the ELIXIR compute infrastructure. We will adopt ELIXIR Authentication & Authorisation Infrastructure (ELIXIR-AAI) to support deposition of ligand-protein complexes or benchmark results into our future infrastructure. We also need to provide an easy way to store and synchronise our datasets and users’ benchmarks results across ELIXIR and other e-Infrastructures.

Training platform – PDBe-KB and participating data resources will work to add training workflows to the TeSS portal. As mentioned already, ELIXIR-UK funding has already supported preliminary work on these workflows involving collaborations between multiple partners. Proteopedia, which is being developed in collaboration between the Israeli node and PDBe at the hub, will also be a valuable mechanism for training and outreach (see Figure 4). Connections with existing initiatives such as the BioExcel Knowledge Resource Center will be established. The BioExcel knowledge resource center is a repository for computational biomolecular training resources. The resources are primarily online based, such as tutorials, online courses and videos but also include face-to-face events.

Figure 4. The tRNA page from Proteopedia [http://proteopedia.org/w/TRNA].

tRNA plays a key role in translation, the process of synthesizing proteins from amino acids. The two arms of the "L" shaped molecule (cartoon) are formed by the stacking of the acceptor and TΨC-stem.

With regards to protein ligand interactions, we will train researchers on the best way to retrieve and use our benchmark datasets, and promote the usage of preferred benchmark conditions. The Molecular Modeling Group of the SIB Swiss Institute of Bioinformatics will enhance the Drug Design Workshop. This is a web-based educational tool⁷⁰ to introduce structure-based computer-aided drug design to the general public. This online workshop constitutes a helpful tool to introduce the concepts of structure-based drug design to young students (15−19 years old) and to the general public. It can also be used as an introductory tool for more advanced students. Several routes of enhancements will be followed, including a better visualization and analysis of the ligand-protein complex, or the selection of new protein targets.

Building on the experience of the CAPRI community in organizing the well-attended EMBO courses on Integrative of Biomolecular Complexes (3 editions so far), Activity II will coordinate various training activities and workshops on teaching non-experts how to use protein structure and assembly prediction tools and how to benchmark new prediction methods using various datasets assembled in Activity II. Training workflows will be derived and added to the TeSS portal. Activity II will also help coordinate training tasks related to protein structure prediction in the Meet-U initiative. This is an innovative pedagogical initiative created in 2016 that teaches MSc students by involving them in real world research projects, with results evaluated by experts in the field during a final scientific symposium. Meet-U is currently implemented as a collaborative course between three universities of Paris/France area: Sorbonne Université (SU/UPMC), Universités Paris-Sud/Paris-Saclay, and Université Paris-Diderot. It is proposed to implement an international version of Meet-U, involving universities linked to ELIXIR nodes across Europe.

There has also been some support from the ELIXIR UK node to develop training workflows in protein structure prediction and variant impact analysis. This has enabled pilot work and the establishment of small-scale training workflows in the ELIXIR TESS registry. For all activities, we will organise training workshops for trainers and users, and add workflows to TeSS where appropriate.

Connection to other communities and European infrastructure initiatives

3D-Bioinfo community users: The 3D-Bioinfo community bridges several infrastructures and their providers as well as users, namely people and tools of structural biology (Instruct-ERIC, iNEXT), cheminformatics (OpenScreen), system biology (ISBE), molecular simulations (BioExcel) and the proposed community for intrinsically disordered proteins (IDP). In addition, the value of structural data in providing insights into the impacts of genetic variations has led to involvement of some of the 3D-BioInfo participating groups with the ELIXIR Rare Disease Community. Similarly, work in all Activities on structural impacts of residue mutations and other research fields of protein engineering and nucleic acid analogues would clearly enable links with the newly emerging ELIXIR Community on Synthetic Biology. The action plan of this community includes the development of new strains with designed metabolic pathways and expression systems. The synergy of the expertise in the 3D-Bioinfo and Synthetic Biology communities will therefore be very important to implement the new biotech applications that can be expected to be generated through the acquired knowledge and expertise generated by the 3D-Bioinfo ELIXIR community.

The tools and services offered by the proposed 3D-Bioinfo Community already have many millions of users per year and the new Activities, described above, will undoubtedly broaden this scope.

As regards potential overlap with Instruct-ERIC, the 3D-Bioinfo community develops tools that go beyond the scope of structural biology and are not covered by the Instruct-ERIC initiatives and efforts. We will work closely with Instruct-ERIC on common areas of interest (e.g. methods for validating experimental protein and nucleic acid structures) and seek support for joint implementations studies.

Connection with industry

Industry and SME involvement – As mentioned already, Activity III (linked to structure-based drug design) is of particular relevance for the pharmaceutical and biotechnology industries, particularly those using computer-aided structure-based drug design programs. Companies involved in the development of scientific software as well as novel bioactive compounds acknowledge the importance of developing benchmarking protocols, and participate in the D3R Grand Challenges by providing undisclosed data. Furthermore, as regards Activity I, PDBe-KB has interactions with OpenTargets platform and provides annotations to major data resources (UniProt, InterPro and Pfam). Development of data standards and distributable infrastructure would further improve accessibility of the added value annotation data for industry users where all four Activities will contribute. We also expect to build up links to the pharmaceutical Industry via the collaborations with BioExcel, and Instruct-ERIC. Future 3D-Bioinfo Activities around protein and enzyme engineering are expected to provide strong links with the industry and it is anticipated that these links will very much strengthen the competitiveness of the developing European biotechnology SMEs.

Integration at a global level

Clearly the ontologies and data exchange formats established and endorsed through 3D-Bioinfo enabled collaborations will be valuable in a global context as well as across Europe. In fact many of the initiatives we will foster such as PDBe-KB, CAPRI and CAMEO already involve other international partners outside Europe. Furthermore, 3D-Bioinfo groups are involved in organising the international community-wide CASP benchmarking of protein structure prediction. We will support and where possible engage in initiatives for global health, for example the Global Alliance for Genomics and Health (GA4GH). We plan to present activities and output from 3D-Bioinfo in special sessions or technology tracks at the European ECCB and international ISMB conferences, the latter of which is held in Europe on alternate years. This will publicise our activities to the wider bioinformatics community, enable us to recruit additional European participants and promote links with other international initiatives.

Underlying data

No data are associated with this article.