BioLiP2: an updated structure database for biologically relevant ligand–protein interactions

Author:

Zhang Chengxin1ORCID,Zhang Xi2,Freddolino Peter L12ORCID,Zhang Yang12345ORCID

Affiliation:

1. Department of Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor , MI 48109, USA

2. Department of Biological Chemistry, University of Michigan , Ann Arbor , MI 48109, USA

3. Department of Computer Science, School of Computing, National University of Singapore , 117417, Singapore

4. Cancer Science Institute of Singapore, National University of Singapore ,117599, Singapore

5. Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore , 117596, Singapore

Abstract

Abstract With the progress of structural biology, the Protein Data Bank (PDB) has witnessed rapid accumulation of experimentally solved protein structures. Since many structures are determined with purification and crystallization additives that are unrelated to a protein's in vivo function, it is nontrivial to identify the subset of protein–ligand interactions that are biologically relevant. We developed the BioLiP2 database (https://zhanggroup.org/BioLiP) to extract biologically relevant protein–ligand interactions from the PDB database. BioLiP2 assesses the functional relevance of the ligands by geometric rules and experimental literature validations. The ligand binding information is further enriched with other function annotations, including Enzyme Commission numbers, Gene Ontology terms, catalytic sites, and binding affinities collected from other databases and a manual literature survey. Compared to its predecessor BioLiP, BioLiP2 offers significantly greater coverage of nucleic acid-protein interactions, and interactions involving large complexes that are unavailable in PDB format. BioLiP2 also integrates cutting-edge structural alignment algorithms with state-of-the-art structure prediction techniques, which for the first time enables composite protein structure and sequence-based searching and significantly enhances the usefulness of the database in structure-based function annotations. With these new developments, BioLiP2 will continue to be an important and comprehensive database for docking, virtual screening, and structure-based protein function analyses.

Funder

National Institute of General Medical Sciences

National Institute of Allergy and Infectious Diseases

National Science Foundation

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Genetics

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