FireDB: a compendium of biological and pharmacologically relevant ligands

Maietta, Paolo; Lopez, Gonzalo; Carro, Ángel; Pingilley, Benjamin J.; León, Leticia G.; Valencia, Alfonso; Tress, Michael L.

doi:10.1093/nar/gkt1127

Cited by 23 publications

(20 citation statements)

References 30 publications

(28 reference statements)

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“…These problems prevent the PDB from being a reliable resource for precise structure-based function analyses. Efforts have been made to address these issues to build biologically-relevant ligand–protein binding databases, such as FireDB ( 30 ).…”

Section: Methodsmentioning

confidence: 99%

I-TASSER server: new development for protein structure and function predictions

2015

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The I-TASSER server (http://zhanglab.ccmb.med.umich.edu/I-TASSER) is an online resource for automated protein structure prediction and structure-based function annotation. In I-TASSER, structural templates are first recognized from the PDB using multiple threading alignment approaches. Full-length structure models are then constructed by iterative fragment assembly simulations. The functional insights are finally derived by matching the predicted structure models with known proteins in the function databases. Although the server has been widely used for various biological and biomedical investigations, numerous comments and suggestions have been reported from the user community. In this article, we summarize recent developments on the I-TASSER server, which were designed to address the requirements from the user community and to increase the accuracy of modeling predictions. Focuses have been made on the introduction of new methods for atomic-level structure refinement, local structure quality estimation and biological function annotations. We expect that these new developments will improve the quality of the I-TASSER server and further facilitate its use by the community for high-resolution structure and function prediction.

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Section: Methodsmentioning

confidence: 99%

I-TASSER server: new development for protein structure and function predictions

2015

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“…For example, clustering the sc-PDB sites of adenylosuccinate synthetase yields three clusters; two of them that have similar structures and compositions except guanosine diphosphate (GDP) and Mg 2+ cofactors; the third one is localized in a different region in the protein (Supplementary Figure S3). Other high quality databases derived from the PDB also facilitate the comparison of the binding sites across a protein family ( 21 – 23 ). The sc-PDB database is, however, the only meta-database enabling to search the PDB using user-defined queries mixing protein, ligand, binding site and binding mode properties.…”

Section: New Features Of the Sc-pdb Databasementioning

confidence: 99%

sc-PDB: a 3D-database of ligandable binding sites—10 years on

Desaphy

Bret

Rognan

et al. 2014

Nucleic Acids Research

206

199

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The sc-PDB database (available at http://bioinfo-pharma.u-strasbg.fr/scPDB/) is a comprehensive and up-to-date selection of ligandable binding sites of the Protein Data Bank. Sites are defined from complexes between a protein and a pharmacological ligand. The database provides the all-atom description of the protein, its ligand, their binding site and their binding mode. Currently, the sc-PDB archive registers 9283 binding sites from 3678 unique proteins and 5608 unique ligands. The sc-PDB database was publicly launched in 2004 with the aim of providing structure files suitable for computational approaches to drug design, such as docking. During the last 10 years we have improved and standardized the processes for (i) identifying binding sites, (ii) correcting structures, (iii) annotating protein function and ligand properties and (iv) characterizing their binding mode. This paper presents the latest enhancements in the database, specifically pertaining to the representation of molecular interaction and to the similarity between ligand/protein binding patterns. The new website puts emphasis in pictorial analysis of data.

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“…53 groups used some form of sequence similarity, 20 used physical protein interaction data, and 12 used gene expression. While the SIAM/FireDB method uses protein-ligand co-crystal structures [ 39 ], as far as we are aware, no team used data from ChEMBL or other large protein-ligand database to construct their predictors. This absence is conspicuous since evaluating diverse data sources should have larger impact than a varying inference algorithms [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

et al. 2016

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The expansion of protein-ligand annotation databases has enabled large-scale networking of proteins by ligand similarity. These ligand-based protein networks, which implicitly predict the ability of neighboring proteins to bind related ligands, may complement biologically-oriented gene networks, which are used to predict functional or disease relevance. To quantify the degree to which such ligand-based protein associations might complement functional genomic associations, including sequence similarity, physical protein-protein interactions, co-expression, and disease gene annotations, we calculated a network based on the Similarity Ensemble Approach (SEA: sea.docking.org), where protein neighbors reflect the similarity of their ligands. We also measured the similarity with functional genomic networks over a common set of 1,131 genes, and found that the networks had only small overlaps, which were significant only due to the large scale of the data. Consistent with the view that the networks contain different information, combining them substantially improved Molecular Function prediction within GO (from AUROC~0.63–0.75 for the individual data modalities to AUROC~0.8 in the aggregate). We investigated the boost in guilt-by-association gene function prediction when the networks are combined and describe underlying properties that can be further exploited.

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FireDB: a compendium of biological and pharmacologically relevant ligands

Cited by 23 publications

References 30 publications

I-TASSER server: new development for protein structure and function predictions

I-TASSER server: new development for protein structure and function predictions

sc-PDB: a 3D-database of ligandable binding sites—10 years on

Ligand Similarity Complements Sequence, Physical Interaction, and Co-Expression for Gene Function Prediction

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