Evidence map›Paper›PMID 35763362›Full record

ArticleDatabase : the journal of biological databases and curation2022

FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank.

Daniele Toti, Gabriele Macari, Enrico Barbierato, Fabio Polticelli

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 58% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Daniele TotiDepartment of Mathematics and Physics, Catholic University of the Sacred Heart, Faculty of Mathematical, Physical and Natural Sciences, via della Garzetta 48, Brescia 25133, Italy.ORCID 0000-0002-9668-6961
Gabriele MacariDepartment of Sciences, Roma Tre University, viale Marconi 446, Roma, Lazio 00146, Italy.
Enrico BarbieratoDepartment of Mathematics and Physics, Catholic University of the Sacred Heart, Faculty of Mathematical, Physical and Natural Sciences, via della Garzetta 48, Brescia 25133, Italy.
Fabio PolticelliDepartment of Sciences, Roma Tre University, viale Marconi 446, Roma, Lazio 00146, Italy.ORCID 0000-0002-7657-2019
Roma Tre University · ITUniversità Cattolica del Sacro Cuore · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work presents Fragment Graph DataBase (FGDB), a graph database of ligand fragments extracted and generated from the protein entries available in the Protein Data Bank (PDB). FGDB is meant to support and elicit campaigns of fragment-based drug design, by enabling users to query it in order to construct ad hoc, target-specific libraries. In this regard, the database features more than 17 000 fragments, typically small, highly soluble and chemically stable molecules expressed via their canonical Simplified Molecular Input Line Entry System (SMILES) representation. For these fragments, the database provides information related to their contact frequencies with the amino acids, the ligands they are contained in and the proteins the latter bind to. The graph database can be queried via standard web forms and textual searches by a number of identifiers (SMILES, ligand and protein PDB ids) as well as via graphical queries that can be performed against the graph itself, providing users with an intuitive and effective view upon the underlying biological entities. Further search mechanisms via advanced conjunctive/disjunctive/negated textual queries are also possible, in order to allow scientists to look for specific relationships and export their results for further studies. This work also presents two sample use cases where maternal embryonic leucine zipper kinase and mesotrypsin are used as a target, being proteins of high biomedical relevance for the development of cancer therapies. Database URL: http://biochimica3.bio.uniroma3.it/fragments-web/.

Indexed as

ProteinsDatabases, ProteinLigandsLigandsProteins

Identifiers

PMID35763362
PMCPMC9239314
OpenAlexW4283706276

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.