Literature DB >> 23740740

Insights into polypharmacology from drug-domain associations.

Aurelio A Moya-García1, Juan A G Ranea.   

Abstract

MOTIVATION: Polypharmacology (the ability of a single drug to affect multiple targets) is a key feature that may explain part of the decreasing success of conventional drug discovery strategies driven by the quest for drugs to act selectively on a single target. Most drug targets are proteins that are composed of domains (their structural and functional building blocks).
RESULTS: In this work, we model drug-domain networks to explore the role of protein domains as drug targets and to explain drug polypharmacology in terms of the interactions between drugs and protein domains. We find that drugs are organized around a privileged set of druggable domains.
CONCLUSIONS: Protein domains are a good proxy for drug targets, and drug polypharmacology emerges as a consequence of the multi-domain composition of proteins. CONTACT: amoyag@uma.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mesh:

Substances:

Year:  2013        PMID: 23740740     DOI: 10.1093/bioinformatics/btt321

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


  8 in total

1.  PPDMs-a resource for mapping small molecule bioactivities from ChEMBL to Pfam-A protein domains.

Authors:  Felix A Kruger; Anna Gaulton; Michal Nowotka; John P Overington
Journal:  Bioinformatics       Date:  2014-10-27       Impact factor: 6.937

Review 2.  A survey on the computational approaches to identify drug targets in the postgenomic era.

Authors:  Yan-Fen Dai; Xing-Ming Zhao
Journal:  Biomed Res Int       Date:  2015-04-28       Impact factor: 3.411

3.  Creation of a free, Internet-accessible database: the Multiple Target Ligand Database.

Authors:  Chao Chen; Yang He; Jianhui Wu; Jinming Zhou
Journal:  J Cheminform       Date:  2015-04-15       Impact factor: 5.514

4.  Analysis of individual protein regions provides novel insights on cancer pharmacogenomics.

Authors:  Eduard Porta Pardo; Adam Godzik
Journal:  PLoS Comput Biol       Date:  2015-01-08       Impact factor: 4.475

5.  Large-scale bioactivity analysis of the small-molecule assayed proteome.

Authors:  Tyler William H Backman; Daniel S Evans; Thomas Girke
Journal:  PLoS One       Date:  2017-02-08       Impact factor: 3.240

6.  A simple mathematical approach to the analysis of polypharmacology and polyspecificity data.

Authors:  Gerry Maggiora; Vijay Gokhale
Journal:  F1000Res       Date:  2017-06-06

7.  In silico prediction of targets for anti-angiogenesis and their in vitro evaluation confirm the involvement of SOD3 in angiogenesis.

Authors:  Javier A García-Vilas; Ian Morilla; Anibal Bueno; Beatriz Martínez-Poveda; Miguel Ángel Medina; Juan A G Ranea
Journal:  Oncotarget       Date:  2018-04-03

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

北京卡尤迪生物科技股份有限公司 © 2022-2023.