FunPDBe: Community-driven enrichment of PDB data

Table of Contents
  1. Introduction
  2. Data deposition
  3. Participating resources
  4. Project reports

Introduction


What is FunPDBe?

FunPDBe is a project of the Protein Data Bank in Europe - Knowledge Base (PDBe-KB) with the goal to create an integrated and accessible resource of structural and functional annotations for macromolecular structure data in the Protein Data Bank (PDB). It is a collaboration between the PDBe-KB and world-leading providers of structural bioinformatics data.

What is the goal of FunPDBe?

The project promotes interoperability, comparative analysis and exchange of structural and functional annotations by implementing common data standards and infrastructure to collect these enhanced annotations. PDBe-KB, of which FunPDBe is a flagship project, aims to significantly increase the impact of structural data globally by implementing a central sustainable data resource and a uniform data access mechanism (via FTP and REST API) for distribution of these valuable functional and structural annotations, developed by researchers. The data is to be made accessible via web interface by developing re-usable web components.

Data deposition


Who can contribute annotations?

PDBe-KB is open to deposition of annotations from potential collaborating data resource or scientific software developers. This document describes the process of contributing annotations as a member of the PDBe-KB consortium.

A separate Consortium Guideline document with information on the agreed terms of collaborations is available at https://www.ebi.ac.uk/pdbe/pdbe-kb/guidelines

Please contact PDBe-KB for more details.

How to deposit data?

Download as PDF
Data Exchange Schema

Collaborating partners contribute annotations by converting their data to JSON (https://json.org) formatted files based on the agreed JSON specification schema. This schema and an example JSON can be found at https://gitlab.ebi.ac.uk/pdbe-kb/funpdbe/funpdbe-schema

Format Validation Tools

The JSON files can be validated using a Python package available at https://gitlab.ebi.ac.uk/pdbe-kb/funpdbe/funpdbe-validator. This lightweight Python package performs every check performed during deposition:

  • Checks against the schema
  • Data sanity checks
  • Cross-matching the residue indices in JSON to those available in the PDB

Note for the last point: The residue numbering in the JSON files is required to be the same as the author residue numbering in PDB (i.e. auth_seq_id).

File Transfer

Each partner resource is provided with a private FTP area by the PDBe-KB team. The partner resources transfer the validated JSON files to the assigned private FTP areas provided by EMBL-EBI. The folder structure should follow the PDB FTP convention, i.e. the JSON file for the PDB entries ‘1a00’ and ‘1a0n’ should both be in the sub-folder ‘a0’ as shown on the example below:

The transferred files are then processed, validated and integrated with the core PDB data in the PDBe graph database ( https://pdbe.org/graph-schema).

Please note: The PDBe will request this FTP account once the data format is finalised and reviewed.

Downstream Processes

The integrated annotations are exposed via the PDBe graph API endpoint (https://pdbe.org/graph-api). These API endpoints power the PDBe-KB aggregated views, such as the Aggregated Views for Proteins ( https://pdbe-kb.org/proteins).

Importantly, the annotations are always displayed together with links that use the URLs provided by the partner resource so that the users can directly reach the original data resource.

Please note: Not every annotation is displayed on all the PDBe and PDBe-KB pages, i.e. some annotations may only be displayed on specific pages.

Participating resources

14-3-3-Pred Geoff Barton group http://www.compbio.dundee.ac.uk/1433pred
3D Complex Emmanuel Levy group https://shmoo.weizmann.ac.il/elevy/3dcomplexV6/Home.cgi
3DLigandSite Mark Wass group http://www.sbg.bio.ic.ac.uk/~3dligandsite/
AKID Manuela Helmer Citterich group http://akid.bio.uniroma2.it/
Arpeggio Tom Blundell group http://biosig.unimelb.edu.au/arpeggioweb/
CamKinet Toby Gibson group http://camkinet.embl.de/v2/home/
canSAR Bissan Al-Lazikani group https://cansar.icr.ac.uk/
CATH-FunSites Christine Orengo group http://www.cathdb.info/
ChannelsDB Jaroslav Koca group http://ncbr.muni.cz/ChannelsDB/
COSPI-Depth M.S. Madhusudhan group http://cospi.iiserpune.ac.in/depth
DynaMine Wim Vranken group http://dynamine.ibsquare.be/
FoldX Luis Serrano group http://foldxsuite.crg.eu/
M-CSA Janet Thornton group https://www.ebi.ac.uk/thornton-srv/m-csa/
MetalPDB Claudia Andreini, Antonio Rosato group http://metalweb.cerm.unifi.it/
Missense3D Michael Sternberg group http://www.sbg.bio.ic.ac.uk/~missense3d/
P2Rank David Hoksza group http://prankweb.cz/
POPSCOMP Franca Fraternali group http://popscomp.org:3838/
ProKinO Natarajan Kannan group http://vulcan.cs.uga.edu/prokino/about/prokino
SKEMPI Iain H Moal group https://life.bsc.es/pid/skempi2/

FunPDBe Project Reports

The FunPDBe project is divided into 3 work packages:

  1. Predicted functional annotations (Oct 2017 - Sep 2018)
  2. Curated/evidence-based funcitonal annotations (Oct 2018 - Sep 2019)
  3. Mutations and variations (Oct 2019 - Sep 2020) (In Progress)

Report on Work Package 1

Predicted functional annotations

Click here to download in PDF format

Table of Contents
  1. Executive Summary
  2. WP1 Deliverables
  3. Outcomes
    1. Consortium terms of reference
    2. Data exchange format and schema
    3. Deposition system
    4. Accessing and visualising data
  4. Networking
  5. Recommendations, next steps
  6. Appendices
Executive Summary

FunPDBe is one of the flagship projects of the Protein Data Bank in Europe - Knowledge Base (PDBe-KB), a community-driven integrated and accessible resource of structural and functional annotations for macromolecular structure data in the Protein Data Bank (PDB). It is a collaboration between PDBe-KB and world-leading providers of structural bioinformatics data. The project promotes interoperability, comparative analysis and exchange of structural and functional annotations by implementing common data standards and infrastructure to collect these enhanced annotations. The project aims to significantly increase the impact of structural data globally by implementing a central sustainable data resource and a uniform data access mechanism (via FTP and REST API) for distribution of these valuable functional and structural annotations. The data is made accessible programmatically and via web interface by developing reusable web components.

It is a 3 year long project that has been running since October 2017, divided into three main Work Packages (WPs), with an additional, concurrent work package focused on training and dissemination. This current report covers the first WP.

Work packages Focus Co-PIs
WP1 (Oct 2017-2018) Predicted functional sites Christine Orengo
WP2 (Oct 2018-2019) Known functional sites Janet Thornton
WP3 (Oct 2019-2020) Genetic variation Mike Sternberg
WP1 Deliverables

Work Package 1 can be divided into 3 main deliverables (Figure 1). All three deliverables have been achieved as envisaged during this first year. These are described in detail below:

  1. Designing a data exchange format that captures the commonalities between the annotations provided by various specialist data resources, who may have very diverse types of data.
  2. Designing and implementing a data deposition system that allows the collaborating partners to deposit their annotations in the agreed data exchange format.
  3. Designing and implementing programmatic access to the deposited data, and displaying the data using various visualisation tools.

Figure 1 - Overview of the FunPDBe deliverables

The first and second deliverables are the data format and the deposition system (blue boxes), while the third deliverable is exposing the annotations using web components (yellow boxes)

Outcomes
Consortium terms of reference

During the first year of FunPDBe, there were three workshops (October and November 2017 and May 2018) where collaborating partners and other interested parties discussed the goals, progress, next steps of the project and collaboration guidelines. The guidelines (Appendix A) were circulated in August 2018 to project PIs and to all participating teams, and have been made available on the PDBe-KB web page: https://www.ebi.ac.uk/pdbe/pdbe-kb/guidelines

Data exchange format and schema

The initial recommendation presented in the inaugural workshop in October 2018 was to design a JSON (JavaScript Object Notation) schema that can capture residue-level functional annotations keyed on PDB entries. After a number of iterations, the schema was finalised during the 2nd workshop in Nov 2017. The key data items are the residue-level predictions scores (raw scores), the confidence scores and their classification into simplified levels (null, low, medium, high), and evidence and conclusion ontology (ECO) codes and terms. Importantly, the JSON schema allows for storing URLs linking back to the original data contributor. This allows access to more comprehensive data that cannot be captured by the unified data exchange format, while also giving credit to the collaborating partners for the data they provide.

The JSON schema is available publicly, hosted on EMBL-EBI’s GitLab: https://gitlab.ebi.ac.uk/pdbe-kb/funpdbe/funpdbe-schema

Partner resources agreed on using this format when depositing functional annotations.

Deposition system

In order to allow the collaborating partners to deposit their data, we have designed and implemented a deposition system. This deposition system consists of 3 units:

  • FunPDBe Deposition Client
  • FunPDBe Deposition API
  • FunPDBe Deposition Database

The FunPDBe Deposition Client is a lightweight Python package that can be used to validate data against the FunPDBe JSON schema specifications, and for communicating with the FunPDBe Deposition API, creating, reading, updating and deleting data. The client is hosted on GitLab and is publicly available: https://gitlab.ebi.ac.uk/pdbe-kb/funpdbe/funpdbe-client

Collaborating partners have agreed to download and use this client for depositing their JSON files.

The FunPDBe Deposition API is providing programmatic access to the deposition database. It listens to requests sent by the FunPDBe client, performs final data checks, and loads the data into the deposition database. It is hosted on virtual machines internal to EBI.

The FunPDBe Deposition Database is a MySQL database that serves as a staging database for the data deposited by the contributing partner resources. Access to this database is provided only via the deposition API.

Accessing and visualising data

Annotations deposited to the FunPDBe Deposition Database are periodically exported, and integrated with annotations from other projects and core PDBe data in a Neo4j Graph Database. Using the graph approach is especially well-suited for this type of highly interconnected data, and allows performing complex queries, effectively rendering the database into a scientific research tool. Each annotation is linked to the corresponding PDB residues, and these residues are also linked to their UniProtKB counterparts, provided by the SIFTS infrastructure. This enables the transfer of structure-based functional annotations onto UniProtKB sequences, allowing queries based on UniProtKB accessions, sequences and residues.

The Neo4j database itself (currently at 250GB) will be made publicly available, allowing the scientific community to perform complex queries, and to integrate this rich data resource with their own data and/or perform extensive data mining.

We are developing an API that allows programmatic access to this database, exposing functional annotations in the context of PDB entries. Current API endpoints answer the following questions, related to the FunPDBe project:

  1. Which data resources have annotations for a specific PDB entry?
  2. What are the annotations for every residue within a specific PDB entry from a specific resource?
  3. What annotations are there for a specific PDB residue?

These API endpoints are available on our development server, with production release scheduled in early 2019: https://wwwdev.ebi.ac.uk/pdbe/graph-api/pdbe_doc/

In order to visualise the functional annotations, our initial goals are to integrate the API endpoints with ProtVista and LiteMol. ProtVista is a sequence feature viewer developed by UniProt ( http://ebi-uniprot.github.io/ProtVista/ ) and used by UniProt, InterPro and PDBe. It is well suited for displaying and comparing residue-level annotation. An example of the FunPDBe implementation is shown below (Figure 2). Integration of FunPDBe data with the reusable and portable ProtVista widget means that the annotations can be plugged in and displayed on any web service in a straightforward manner, facilitating access and providing visibility to the data of the contributing resources.

Figure 2 - FunPDBe annotations rendered in ProtVista

ProtVista is a sequence feature viewer developed by UniProt. We have integrated the new API calls with ProtVista so that FunPDBe data can be accessed, consumed and rendered by ProtVista tracks.

LiteMol is a 3D molecular viewer already used on the PDBe pages. We are currently working on establishing direct two-way communication between ProtVista and LiteMol, so that selecting a residue/annotation in ProtVista will highlight that residue on the 3D structure, and vice versa.

Networking

The original group of contributors in Work Package 1 consisted of six labs (see Appendix B). Over the course of the first year, additional groups have expressed an interest in collaborating in the FunPDBe project. To date, four more resources provided residue-level annotations, and there are discussions with six further groups.

Recommendations, next steps

Once the integration of FunPDBe annotations with the 3D molecular viewer, LiteMol, is completed, the data will be available for displaying on PDBe pages, and other web services. Moving forward to Work Package 2 (Oct 2018 - 2019), there are planned changes to the deposition system, enabling higher throughput depositions using FTP (file transfer protocol) and local, parallelised data validation and loading, in addition to the deposition API and client that are already in place.

Appendices
  • A - Consortium Guidelines
  • B - Participating Partner Resources and Statistics
Appendix A - Consortium Guidelines
Terms of collaboration
PDBe-KB
  • The infrastructure for data deposition and retrieval will be maintained by PDBe-KB
  • Data exchange format schema(s) will be maintained by PDBe-KB
  • The schema will evolve in consultation with collaborating partners
  • PDBe-KB will provide programmatic access to expose contributed annotations
  • PDBe-KB will link back to the original collaborating partners resource, attributing credit for their contributions
  • PDBe-KB will maintain an open-access library of reusable data visualisation components
Collaborating partners
  • The data contributed to PDBe-KB by collaborating partners will be free from any restrictions on distribution and re-use
  • The partners are responsible for the quality of the data they contribute
  • Protocols for data generation must be published in peer-reviewed publications
  • In case of predicted/calculated annotations, the contributing partner makes a commitment of depositing data at least once a year: e.g., to provide annotations for newer PDB entries and/or update the existing annotations when the underlying algorithms change significantly.
  • Manually curated annotations may be exempt from this condition on a case-by-case basis
  • Depositors can change/update/delete their entries at any time
General Data Protection Regulation (GDPR) notice

Collaborating partners have to agree to the PDBe-KB GDPR notice before registering a data deposition account. The privacy notice is available here

Appendix B - Participating Partner Resources and Statistics
Resource name Owner Data type Entries contributed
CATH-FunSites Christine Orengo Conserved sites 23,975
canSAR Bissan al-Lazikani Druggable pockets 17,804
3DLigandSite Mark Wass Binding sites 975
NoD Geoff Barton Binding sites 1
14-3-3-Pred Geoff Barton Binding sites 1
POPSCOMP Franca Fraternali Solvent accessibility 0
CREDO Tom Blundell Binding pockets 0
COSPI-Depth M. Madhusudhan Residue depth 141,097
DynaMine Wim Vranken Dynamics 139,049
AKID Manuela Citterich-Helmer PTM sites 39,763
ProKinO Natarajan Kannan PTM sites 3,671

Report on Work Package 2

Curated/evidence-based funcitonal annotations

Click here to download in PDF format

Table of Contents
  1. Executive Summary
  2. WP2 Deliverables
  3. Outcomes
    1. Consortium terms of reference
    2. Data exchange format and schema
    3. Deposition system
    4. Accessing and visualising data
    5. Aggregated Views for Proteins
  4. Networking
  5. Publications
  6. Recommendations, next steps
  7. Appendices
Executive Summary

FunPDBe is a flagship project that contributes data to the Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://pdbe-kb.org), a community-driven integrated and accessible resource of structural and functional annotations for macromolecular structure data in the Protein Data Bank (PDB). It is a collaboration between the PDBe team and world-leading providers of structural bioinformatics data. The project promotes interoperability, comparative analysis and exchange of structural and functional annotations by implementing common data standards and infrastructure to collect these enhanced annotations. The project aims to significantly increase the impact of structural data globally by implementing a central, sustainable data resource and a uniform data access mechanism (via FTP and REST API) for distribution of these valuable functional and structural annotations. The data is made accessible programmatically and via a web interface by developing reusable web components.

Over the course of the first two years of the project, the consortium members agreed on the collaboration guidelines (https://pdbe-kb.org/guidelines) and established a common data exchange format for functional site annotations and biophysical parameters. By the end of WP2, the contributing resources transferred over 828,000 entries using the deposition infrastructure designed and implemented over the duration of the FunPDBe project, and this data is being exposed using novel aggregated views keyed on UniProt identifiers in addition to PDB identifiers (https://pdbe-kb.org/proteins).

In addition to the original collaborating partners listed in the grant proposal, several new resources joined the consortium, in part through the ELIXIR 3DBioInfo community, where PDBe-KB is designated as a recommended activity

FunPDBe project is described in the PDBe-KB publication in the 2020 Database Issue of Nucleic Acids Research [REF].

It is a 3 year long project that has been running since October 2017, divided into three main Work Packages (WPs), with an additional, concurrent work package focused on training and dissemination. This current report covers the second work package.

Work packages Focus Co-PIs
WP1 (Oct 2017-2018) Predicted functional sites Christine Orengo
WP2 (Oct 2018-2019) Known functional sites Janet Thornton
WP3 (Oct 2019-2020) Genetic variation Mike Sternberg
WP2 Deliverables

Work Package 2 builds upon the previous work, focusing on the deliverables described below. The overall workflow is depicted in Figure 1.

  1. Evaluate the suitability of the data exchange format developed in WP1 and extend it if required to accommodate annotations that are evidence-based and curated.
  2. Maintain, improve and further develop the data deposition system to allow the partners from both WP1 and WP2 to deposit their annotations using the agreed data exchange format.
  3. Design and implement additional RESTful API endpoints to expose the new annotations and ensure that the developed visualisation components support the new data.

Figure 1 - Overview of the FunPDBe deliverables

The deposition system validates and processes the contributed annotations (left-side of the figure), while the data is exposed from the PDBe Neo4j graph database (middle of the figure) using web components that are reused on PDBe and PDBe-KB pages (right-side of the figure). The deposition API and MySQL deposition database is being retired as the FTP and local validation pipeline is more efficient for high-throughput depositions.

Outcomes
Consortium terms of reference

Over the second year of FunPDBe, the collaboration guidelines were presented both to the Scientific Advisory Board and to new potential PDBe-KB partners during the annual PDBe-KB meeting in June 2019. The guidelines (Appendix A) remained unchanged except for the technical appendix, where the changes to the infrastructure were included, and are available at https://www.ebi.ac.uk/pdbe/pdbe-kb/guidelines .

Data exchange format and schema

During WP1 it was agreed that the data exchange format should be defined as JSON (JavaScript Object Notation) schema that can capture residue-level functional and biophysical annotations keyed on PDB entries. The schema is available at https://gitlab.ebi.ac.uk/pdbe-kb/funpdbe/funpdbe-schema.

Over the course of the second year of FunPDBe (Oct 2018 - Sep 2019) there have been changes to this schema in order to support the annotations of the new partner resources, while ensuring backward compatibility for existing contributors. The changes are recorded in the “changelog” file of the repository and can be found below, in chronological order:

  • 24/10/2018 - "confidence_score" can be greater than 1.0, if the calculation method justifies it
  • 15/01/2019
    • "confidence_score" is optional - curated annotations don't have confidence score
    • "raw_score" is optional - curated annotations don't have raw scores
    • "curated" added to "confidence_classification" enumeration list
    • allow additional annotations fields
  • 22/03/2019 - "aa_variant" is an optional field in "site_data" for mutations/variants
  • 10/09/2019 - "site_url" is an optional field in "sites" for linking directly to site information
  • 16/09/2019 - "source_version" is an optional field for the version of data which was used to derive annotations
Deposition system

The PDBe-KB deposition system changed extensively over WP2 of FunPDBe in order to improve its scalability and efficiency. This was necessary as some of the partner resources started to provide residue-level annotations for each residue in the PDB, making the deposition via the deposition API cumbersome, often taking several days to complete the data transfer

In order to address this issue, the following major changes were carried out:

  1. The FunPDBe client is retired except for its “JSON validation” functionality. This functionality was moved to a new “FunPDBe Validator” tool, available at https://gitlab.ebi.ac.uk/pdbe-kb/funpdbe/funpdbe-validator and performs significantly more validation than the original client. In particular, it executes all the data “sanity checks”, ensures compliance with the data exchange format JSON schema, and performs residue-level checking against PDBe data to ensure the residue numbering is correct and that only non-obsoleted entries are processed.
  2. The FunPDBe deposition API is also retired, and its data validation and processing functionality was moved to the “FunPDBe Validator” described above.
  3. The FunPDBe SQL database will be retired, once all the partner resources move their annotations to the new deposition system that will be described below.

The new deposition system consists of private FTP (File Transfer Protocol) areas specific to each collaborating resource where they can transfer their annotations. The transferred JSON files are then validated and processed locally at EBI rather than performing the checks at the resource sites using the client and via the deposition API. The process can provide log files to the contributing partners with detailed errors descriptions if an entry failed.

The processed JSON files are then converted directly to the CSV format which is expected by the PDBe graph database loader pipeline. Previously, the CSV files were generated by exporting the data from the deposition SQL database, but this new pipeline can go straight from JSON to CSV.

The CSV files are used by the graph database loader pipeline which runs weekly, and regenerates the complete PDBe graph database.

Accessing and visualising data

Annotations deposited to PDBe-KB are provided to the PDBe archive weekly process so these can be integrated with annotations from other PDBe archive projects and core PDBe data in a Neo4j Graph Database. Using the graph approach is especially well-suited for this type of highly interconnected data, and allows performing complex queries, effectively rendering the database into a scientific research tool. Each annotation is linked to the corresponding PDB residues, and these residues are also linked to their UniProtKB counterparts, provided by the SIFTS infrastructure. This enables the transfer of structure-based functional annotations onto UniProtKB sequences, allowing queries based on UniProtKB accessions, sequences and residues. In future, this can be extended to proteins that are within the same UniRef90 cluster as the directly mapped UniProtKB sequence, i.e. protein sequences with 90% or higher sequence identities where the structural coverage of the referred UniProtKB sequence is 70% or higher.

The Neo4j database itself (currently at 500GB) was made publicly available by the PDBe team during WP2, allowing the scientific community to perform complex queries, and to integrate this rich data resource with their own data and/or perform extensive data mining. The database is available over FTP at ftp://ftp.ebi.ac.uk/pub/databases/msd/graphdb/ and the underlying data schema is made available at https://www.ebi.ac.uk/pdbe/pdbe-kb/schema

Over the course of WP2, 70+ programmatic access endpoints were added to the PDBe graph API, exposing functional annotations in the context of PDB entries and UniProtKB proteins. The API and its documentation is available at https://www.ebi.ac.uk/pdbe/graph-api/pdbe_doc/

Aggregated Views for Proteins

In March 2019 PDBe-KB launched a new type of web pages which are keyed on UniProt accession identifiers instead of PDB entry identifiers and provide an overview of all the available structural information and FunPDBe annotations for a protein of interest. These pages aggregate data using the PDBe graph API described above, and use the web components developed as part of the FunPDBe project. In particular, the sequence feature viewer ProtVista is playing a prominent role in displaying the structural information.

One of the sections of these aggregated views is focused on the residue-level (FunPDBe) annotations provided by the PDBe-KB partners.

The aggregated views for proteins are available at https://www.ebi.ac.uk/pdbe/pdbe-kb/protein using either UniProt or PDB identifiers. For example: UniProt Q14676, PDB 2ETX

Networking

The original group of contributors in Work Package 2 consisted of 3 labs. Over the course of the first year, additional groups have expressed an interest in collaborating in the FunPDBe project and yet more resources joined during the second year of FunPDBe. As of October 2019, 14 resources provided residue-level annotations, with 4 more preparing to contribute their data (see Appendix B).

Publications

PDBe-KB is published in the 2020 Database Issue of Nucleic Acids Research: PDBe-KB: a community-driven resource for structural and functional annotations.

Recommendations, next steps

The final year of FunPDBe (WP3) will focus on mutation and variation data from collaborating partner resources. Initial discussions have already been started with these groups, and the first step will be to ensure the schema of the data exchange format is suitable for supporting their new type of data.

Additionally, more aggregated views are planned for PDBe-KB which will serve as further platforms to display annotations collected as part of the FunPDBe project.

Appendices
  • A - Consortium Guidelines
  • B - Participating Partner Resources and Statistics
Appendix A - Consortium Guidelines
Terms of collaboration
PDBe-KB
  • The infrastructure for data deposition and retrieval will be maintained by PDBe-KB
  • Data exchange format schema(s) will be maintained by PDBe-KB
  • The schema will evolve in consultation with collaborating partners
  • PDBe-KB will provide programmatic access to expose contributed annotations
  • PDBe-KB will link back to the original collaborating partners resource, attributing credit for their contributions
  • PDBe-KB will maintain an open-access library of reusable data visualisation components
Collaborating partners
  • The data contributed to PDBe-KB by collaborating partners will be free from any restrictions on distribution and re-use
  • The partners are responsible for the quality of the data they contribute
  • Protocols for data generation must be published in peer-reviewed publications
  • In case of predicted/calculated annotations, the contributing partner makes a commitment of depositing data at least once a year: e.g., to provide annotations for newer PDB entries and/or update the existing annotations when the underlying algorithms change significantly.
  • Manually curated annotations may be exempt from this condition on a case-by-case basis
  • Depositors can change/update/delete their entries at any time
General Data Protection Regulation (GDPR) notice

Collaborating partners have to agree to the PDBe-KB GDPR notice before registering a data deposition account. The privacy notice is available here

Appendix B - Participating Partner Resources and Statistics
Category Resource name Owner Data type Entries contributed
WP1 participants Arpeggio T. Blundell Ligand interactions 117,023
POPSCOMP F. Fraternali Solvent accessibility 77,578
3DLigandSite M. Wass Predicted binding sites 901
CATH-FunSites C. Orengo Conserved sites 23,975
14-3-3-Pred G. Barton Predicted binding sites 1,887
canSAR B. al-Lazikani Druggable pockets 17,804
WP2 participants M-CSA J. Thornton Curated catalytic sites 919
3DComplex E.D. Levy Interaction interfaces 106,100
Additional partners COSPI-Depth M.S. Madhusudhan Residue depth 139,509
AKID M. Helmer-Citterich Predicted kinase-targets 41,251
P2rank D. Hoksza Predicted binding sites 138,544
ChannelsDB R. Svobodova Molecular channels 22,305
CamKinet T. Gibson Curated PTM sites 1,076
FoldX L. Serrano Predicted effects of mutations 6,804
ProKinO N. Kannan Curated PTM sites 5,035
DynaMine W. Vranken Predicted backbone flexibility 130,552