Finding enzyme cofactors in Protein Data Bank

Mukhopadhyay, Abhik; Borkakoti, Neera; Pravda, Lukáš; Tyzack, Jonathan D.; Thornton, Janet M.; Velankar, Sameer

doi:10.1093/bioinformatics/btz115

Cited by 25 publications

(15 citation statements)

References 9 publications

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“…Most of the annotations provided by the PDBe-KB partner resources focus on amino acid residues and their functions or biophysical characteristics, yet PDBe-KB has information also on molecular entities such as small molecules or macromolecular interaction partners (Figure 6 ). For example, using a previously developed semi-automated annotation process, we can now flag small molecules as enzyme cofactors and cofactor-like molecules ( 50 ). We display this information on the sequence feature viewer, ProtVista and ligand gallery.…”

Section: Methodsmentioning

confidence: 99%

PDBe-KB: collaboratively defining the biological context of structural data

Váradi¹,

Anyango²,

Armstrong³

et al. 2021

Nucleic Acids Research

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The Protein Data Bank in Europe – Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive.

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Section: Methodsmentioning

confidence: 99%

PDBe-KB: collaboratively defining the biological context of structural data

Váradi¹,

Anyango²,

Armstrong³

et al. 2021

Nucleic Acids Research

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“…The latest version of the aggregated views of proteins display functional annotations for ligands, such as whether an observed ligand is a reactant‐like (similar to product or substrate), a cofactor‐like, or a drug‐like molecule. 38 We use internal data pipelines to create these annotations weekly, using the latest PDB data. These pipelines are available as part of our open‐source PDBe CCDutils package ( https://github.com/PDBeurope/ccdutils ).…”

Section: Protein Data Bank Knowledge Base Web Servicesmentioning

confidence: 99%

PDBe and PDBe‐KB: Providing high‐quality, up‐to‐date and integrated resources of macromolecular structures to support basic and applied research and education

et al. 2022

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The archiving and dissemination of protein and nucleic acid structures as well as their structural, functional and biophysical annotations is an essential task that enables the broader scientific community to conduct impactful research in multiple fields of the life sciences. The Protein Data Bank in Europe (PDBe; pdbe.org) team develops and maintains several databases and web services to address this fundamental need. From data archiving as a member of the Worldwide PDB consortium (wwPDB; wwpdb.org), to the PDBe Knowledge Base (PDBe-KB; pdbekb. org), we provide data, data-access mechanisms, and visualizations that facilitate basic and applied research and education across the life sciences. Here, we provide an overview of the structural data and annotations that we integrate and make freely available. We describe the web services and data visualization tools we offer, and provide information on how to effectively use or even further develop them. Finally, we discuss the direction of our data services, and how we aim to tackle new challenges that arise from the recent, unprecedented advances in the field of structure determination and protein structure modeling.

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“…Elucidation of protein function remains a difficult and important task, with many millions of proteins present in UniProt ( 1 ) and only a small fraction of them functionally annotated ( 2 , 3 ), making automated sequence annotation tools essential. Small molecules that bind to proteins are intimately related to protein function; they can be substrates or products of an enzyme reaction, cofactors ( 4 ) that play an essential role in catalysis or have important structural or regulatory roles ( 5 ).…”

Section: Introductionmentioning

confidence: 99%

3DLigandSite: structure-based prediction of protein–ligand binding sites

McGreig

Uri

Antczak

et al. 2022

Nucleic Acids Research

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3DLigandSite is a web tool for the prediction of ligand-binding sites in proteins. Here, we report a significant update since the first release of 3DLigandSite in 2010. The overall methodology remains the same, with candidate binding sites in proteins inferred using known binding sites in related protein structures as templates. However, the initial structural modelling step now uses the newly available structures from the AlphaFold database or alternatively Phyre2 when AlphaFold structures are not available. Further, a sequence-based search using HHSearch has been introduced to identify template structures with bound ligands that are used to infer the ligand-binding residues in the query protein. Finally, we introduced a machine learning element as the final prediction step, which improves the accuracy of predictions and provides a confidence score for each residue predicted to be part of a binding site. Validation of 3DLigandSite on a set of 6416 binding sites obtained 92% recall at 75% precision for non-metal binding sites and 52% recall at 75% precision for metal binding sites. 3DLigandSite is available at https://www.wass-michaelislab.org/3dligandsite. Users submit either a protein sequence or structure. Results are displayed in multiple formats including an interactive Mol* molecular visualization of the protein and the predicted binding sites.

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Finding enzyme cofactors in Protein Data Bank

Cited by 25 publications

References 9 publications

PDBe-KB: collaboratively defining the biological context of structural data

PDBe-KB: collaboratively defining the biological context of structural data

PDBe and PDBe‐KB: Providing high‐quality, up‐to‐date and integrated resources of macromolecular structures to support basic and applied research and education

3DLigandSite: structure-based prediction of protein–ligand binding sites

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