24BBR: Enabling efficient basic and translational research through sustainable expansion of PDBe Knowledge Base Using Integrative Resource Framework
Lead Research Organisation:
Science and Technology Facilities Council
Abstract
Macromolecular structure data provides valuable insights into the functional mechanisms of biological processes. Recent advances in experimental structure determination techniques and structure prediction have accumulated an abundance of structure models, revolutionising life-science research. Over the past 50 years, the Protein Data Bank (PDB) and, in the past 24 years, the Electron Microscopy Data Bank (EMDB) have delivered experimentally determined macromolecular structure data. The structure data can only benefit the broader scientific community if it is enriched by adding structural and functional annotations to provide biological context through analysis using various scientific software.
PDBe Knowledge Base (PDBe-KB; pdbe-kb.org) is an open, collaborative consortium that supports the use of 3D-structure data by facilitating integrated access to structural and functional annotations for PDB data from 34 partner resources worldwide, complementing the minimal annotations available in the PDB. PDBe-KB provides a unified access mechanism for 3D structure models from multiple data resources through its 3D-beacons network (3d-beacons.org). Over the past five years after its establishment, PDBe-KB and 3D-Beacons have successfully supported basic and translational research in life sciences, as evident by the more than 300K unique users each year with over 110 citations.
The challenge is establishing a sustainable infrastructure to enrich the over 800 million structure models available in many other data resources (e.g., AFDB, ESM atlas, EMDB, etc.) and accommodate the expected advances in experimental techniques to study conformational changes or studying macromolecules in their natural context inside cells to predicting large multi-component complexes and their conformations. A sustainable extension of the PDBe-KB infrastructure is essential to support easy access to the increasing number and complexity of structure data and associated annotations generated using various tools, including new-generation AI/ML tools for structural and functional annotations for the vast number of structure models.
In this project, we will develop a sustainable infrastructure to enrich structure models by:
Developing distributed workflows that integrate structure analysis tools, including the next-generation AI/ML tools, and making these accessible via an easy-to-use web-based interface.
Extending current PDBe-KB infrastructure for structure models from large-scale prediction and new experimental modalities.
Significantly expanding the PDBe-KB annotations using the combination of newly developed workflow infrastructure and extended infrastructure.
Develop advanced training material for using new workflow infrastructure and expanded PDBe-KB annotations.
The use of workflows for updating PDBe-KB provides a highly efficient use of available resources and a scalable way to consolidate enriched annotations for the large number of models in the multiple structure resources. Access to workflows via easy-to-use web-based interfaces and their compatibility with different workflow engines (CCP4 cloud, NextFlow or Galaxy) will expedite their use in academic or corporate environments. Adopting the new infrastructure by the PDBe-KB partners will maximise the use of their structure analysis tools, such as comparing structure models across different resources and maximising impact. A standardised way of accessing new tools will ensure a scalable and efficient mechanism for integrating new annotations into PDBe-KB. The new workflow infrastructure and large-scale expansion of PDBe-KB will realise the promise of structural biology by driving hypothesis generation and experiment design to study macromolecular function and facilitate basic and translational research, e.g., in drug and protein design, supporting the design of better therapeutics and the green economy, for example, by aiding in the design of more effective enzymes for breaking down plastic pollution.
PDBe Knowledge Base (PDBe-KB; pdbe-kb.org) is an open, collaborative consortium that supports the use of 3D-structure data by facilitating integrated access to structural and functional annotations for PDB data from 34 partner resources worldwide, complementing the minimal annotations available in the PDB. PDBe-KB provides a unified access mechanism for 3D structure models from multiple data resources through its 3D-beacons network (3d-beacons.org). Over the past five years after its establishment, PDBe-KB and 3D-Beacons have successfully supported basic and translational research in life sciences, as evident by the more than 300K unique users each year with over 110 citations.
The challenge is establishing a sustainable infrastructure to enrich the over 800 million structure models available in many other data resources (e.g., AFDB, ESM atlas, EMDB, etc.) and accommodate the expected advances in experimental techniques to study conformational changes or studying macromolecules in their natural context inside cells to predicting large multi-component complexes and their conformations. A sustainable extension of the PDBe-KB infrastructure is essential to support easy access to the increasing number and complexity of structure data and associated annotations generated using various tools, including new-generation AI/ML tools for structural and functional annotations for the vast number of structure models.
In this project, we will develop a sustainable infrastructure to enrich structure models by:
Developing distributed workflows that integrate structure analysis tools, including the next-generation AI/ML tools, and making these accessible via an easy-to-use web-based interface.
Extending current PDBe-KB infrastructure for structure models from large-scale prediction and new experimental modalities.
Significantly expanding the PDBe-KB annotations using the combination of newly developed workflow infrastructure and extended infrastructure.
Develop advanced training material for using new workflow infrastructure and expanded PDBe-KB annotations.
The use of workflows for updating PDBe-KB provides a highly efficient use of available resources and a scalable way to consolidate enriched annotations for the large number of models in the multiple structure resources. Access to workflows via easy-to-use web-based interfaces and their compatibility with different workflow engines (CCP4 cloud, NextFlow or Galaxy) will expedite their use in academic or corporate environments. Adopting the new infrastructure by the PDBe-KB partners will maximise the use of their structure analysis tools, such as comparing structure models across different resources and maximising impact. A standardised way of accessing new tools will ensure a scalable and efficient mechanism for integrating new annotations into PDBe-KB. The new workflow infrastructure and large-scale expansion of PDBe-KB will realise the promise of structural biology by driving hypothesis generation and experiment design to study macromolecular function and facilitate basic and translational research, e.g., in drug and protein design, supporting the design of better therapeutics and the green economy, for example, by aiding in the design of more effective enzymes for breaking down plastic pollution.