Literature DB >> 25380960

IntSide: a web server for the chemical and biological examination of drug side effects.

Teresa Juan-Blanco1, Miquel Duran-Frigola1, Patrick Aloy2.   

Abstract

SUMMARY: Drug side effects are one of the main health threats worldwide, and an important obstacle in drug development. Understanding how adverse reactions occur requires knowledge on drug mechanisms at the molecular level. Despite recent advances, the need for tools and methods that facilitate side effect anticipation still remains. Here, we present IntSide, a web server that integrates chemical and biological information to elucidate the molecular mechanisms underlying drug side effects. IntSide currently catalogs 1175 side effects caused by 996 drugs, associated with drug features divided into eight categories, belonging to either biology or chemistry. On the biological side, IntSide reports drug targets and off-targets, pathways, molecular functions and biological processes. From a chemical viewpoint, it includes molecular fingerprints, scaffolds and chemical entities. Finally, we also integrate additional biological data, such as protein interactions and disease-related genes, to facilitate mechanistic interpretations.
AVAILABILITY AND IMPLEMENTATION: Our data and web resource are available online (http://intside.irbbarcelona.org/). CONTACT: patrick.aloy@irbbarcelona.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2014        PMID: 25380960     DOI: 10.1093/bioinformatics/btu688

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  PDID: database of molecular-level putative protein-drug interactions in the structural human proteome.

Authors:  Chen Wang; Gang Hu; Kui Wang; Michal Brylinski; Lei Xie; Lukasz Kurgan
Journal:  Bioinformatics       Date:  2015-10-26       Impact factor: 6.937

2.  Development of a Controlled Vocabulary-Based Adverse Drug Reaction Signal Dictionary for Multicenter Electronic Health Record-Based Pharmacovigilance.

Authors:  Suehyun Lee; Jongsoo Han; Rae Woong Park; Grace Juyun Kim; John Hoon Rim; Jooyoung Cho; Kye Hwa Lee; Jisan Lee; Sujeong Kim; Ju Han Kim
Journal:  Drug Saf       Date:  2019-05       Impact factor: 5.606

3.  The SIDER database of drugs and side effects.

Authors:  Michael Kuhn; Ivica Letunic; Lars Juhl Jensen; Peer Bork
Journal:  Nucleic Acids Res       Date:  2015-10-19       Impact factor: 16.971

4.  Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

Authors:  Callie Federer; Minjae Yoo; Aik Choon Tan
Journal:  Assay Drug Dev Technol       Date:  2016-09-15       Impact factor: 1.738

5.  Systematic Analyses and Prediction of Human Drug Side Effect Associated Proteins from the Perspective of Protein Evolution.

Authors:  Tina Begum; Tapash Chandra Ghosh; Surajit Basak
Journal:  Genome Biol Evol       Date:  2017-02-01       Impact factor: 3.416

6.  Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects.

Authors:  Phuong A Nguyen; David A Born; Aimee M Deaton; Paul Nioi; Lucas D Ward
Journal:  Nat Commun       Date:  2019-04-05       Impact factor: 14.919

7.  An Explainable Supervised Machine Learning Model for Predicting Respiratory Toxicity of Chemicals Using Optimal Molecular Descriptors.

Authors:  Keerthana Jaganathan; Hilal Tayara; Kil To Chong
Journal:  Pharmaceutics       Date:  2022-04-11       Impact factor: 6.525

8.  Structural and Functional View of Polypharmacology.

Authors:  Aurelio Moya-García; Tolulope Adeyelu; Felix A Kruger; Natalie L Dawson; Jon G Lees; John P Overington; Christine Orengo; Juan A G Ranea
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

  8 in total

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