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Novel machine learning approaches revolutionize protein knowledge.

Trends in biochemical sciences | 2023

Breakthrough methods in machine learning (ML), protein structure prediction, and novel ultrafast structural aligners are revolutionizing structural biology. Obtaining accurate models of proteins and annotating their functions on a large scale is no longer limited by time and resources. The most recent method to be top ranked by the Critical Assessment of Structure Prediction (CASP) assessment, AlphaFold 2 (AF2), is capable of building structural models with an accuracy comparable to that of experimental structures. Annotations of 3D models are keeping pace with the deposition of the structures due to advancements in protein language models (pLMs) and structural aligners that help validate these transferred annotations. In this review we describe how recent developments in ML for protein science are making large-scale structural bioinformatics available to the general scientific community.

Pubmed ID: 36504138 RIS Download

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Associated grants

  • Agency: Wellcome Trust, United Kingdom
    Id: 221327/Z/20/Z
  • Agency: Biotechnology and Biological Sciences Research Council, United Kingdom
    Id: BB/T002735/1

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This is a list of tools and resources that we have found mentioned in this publication.


UniProt (tool)

RRID:SCR_002380

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

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Worldwide Protein Data Bank (wwPDB) (tool)

RRID:SCR_006555

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

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CATH: Protein Structure Classification (tool)

RRID:SCR_007583

CATH is a hierarchical classification of protein domain structures, which clusters proteins at four major levels: Class (C), Architecture (A), Topology (T) and Homologous superfamily (H). The boundaries and assignments for each protein domain are determined using a combination of automated and manual procedures which include computational techniques, empirical and statistical evidence, literature review and expert analysis Users can search CATH by ID/Sequence/text. They can also browse CATH from the top of the hierarchy, or download CATH data.

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MMseqs2 (tool)

RRID:SCR_022962

Software suite for ultra fast and sensitive sequence search and clustering. Used to search and cluster huge protein and nucleotide sequence sets. Designed to run on multiple cores and servers.

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AlphaFold Protein Structure Database (tool)

RRID:SCR_023662

Database of protein structure predictions by AlphaFold that are freely and openly available to global scientific community. Included are nearly all catalogued proteins known to science. Provides programmatic access to and interactive visualization of predicted atomic coordinates, per residue and pairwise model confidence estimates and predicted aligned errors.

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