Literature DB >> 26360911

Large-Scale Predictive Drug Safety: From Structural Alerts to Biological Mechanisms.

Ricard Garcia-Serna1, David Vidal1, Nikita Remez1,2, Jordi Mestres1,2.   

Abstract

The recent explosion of data linking drugs, proteins, and pathways with safety events has promoted the development of integrative systems approaches to large-scale predictive drug safety. The added value of such approaches is that, beyond the traditional identification of potentially labile chemical fragments for selected toxicity end points, they have the potential to provide mechanistic insights for a much larger and diverse set of safety events in a statistically sound nonsupervised manner, based on the similarity to drug classes, the interaction with secondary targets, and the interference with biological pathways. The combined identification of chemical and biological hazards enhances our ability to assess the safety risk of bioactive small molecules with higher confidence than that using structural alerts only. We are still a very long way from reliably predicting drug safety, but advances toward gaining a better understanding of the mechanisms leading to adverse outcomes represent a step forward in this direction.

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Year:  2015        PMID: 26360911     DOI: 10.1021/acs.chemrestox.5b00260

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  15 in total

1.  Synthesis, pharmacological evaluation and molecular docking of pyranopyrazole-linked 1,4-dihydropyridines as potent positive inotropes.

Authors:  Rakesh Kumar; Neha Yadav; Rodolfo Lavilla; Daniel Blasi; Jordi Quintana; José Manuel Brea; María Isabel Loza; Jordi Mestres; Mamta Bhandari; Ritu Arora; Rita Kakkar; Ashok K Prasad
Journal:  Mol Divers       Date:  2017-04-25       Impact factor: 2.943

2.  Application of the hard and soft, acids and bases (HSAB) theory as a method to predict cumulative neurotoxicity.

Authors:  Fjodor Melnikov; Brian C Geohagen; Terrence Gavin; Richard M LoPachin; Paul T Anastas; Phillip Coish; David W Herr
Journal:  Neurotoxicology       Date:  2020-05-05       Impact factor: 4.294

3.  In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs.

Authors:  Raymond R Tice; Arianna Bassan; Alexander Amberg; Lennart T Anger; Marc A Beal; Phillip Bellion; Romualdo Benigni; Jeffrey Birmingham; Alessandro Brigo; Frank Bringezu; Lidia Ceriani; Ian Crooks; Kevin Cross; Rosalie Elespuru; David M Faulkner; Marie C Fortin; Paul Fowler; Markus Frericks; Helga H J Gerets; Gloria D Jahnke; David R Jones; Naomi L Kruhlak; Elena Lo Piparo; Juan Lopez-Belmonte; Amarjit Luniwal; Alice Luu; Federica Madia; Serena Manganelli; Balasubramanian Manickam; Jordi Mestres; Amy L Mihalchik-Burhans; Louise Neilson; Arun Pandiri; Manuela Pavan; Cynthia V Rider; John P Rooney; Alejandra Trejo-Martin; Karen H Watanabe-Sailor; Angela T White; David Woolley; Glenn J Myatt
Journal:  Comput Toxicol       Date:  2021-09-23

Review 4.  In silico toxicology: From structure-activity relationships towards deep learning and adverse outcome pathways.

Authors:  Jennifer Hemmerich; Gerhard F Ecker
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2020-03-31

Review 5.  Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions.

Authors:  Shadia Zaman; Sirarat Sarntivijai; Darrell R Abernethy
Journal:  Gene Regul Syst Bio       Date:  2017-03-15

6.  Systems Toxicology: Real World Applications and Opportunities.

Authors:  Thomas Hartung; Rex E FitzGerald; Paul Jennings; Gary R Mirams; Manuel C Peitsch; Amin Rostami-Hodjegan; Imran Shah; Martin F Wilks; Shana J Sturla
Journal:  Chem Res Toxicol       Date:  2017-03-31       Impact factor: 3.739

Review 7.  Polypharmacology in Precision Oncology: Current Applications and Future Prospects.

Authors:  Albert A Antolin; Paul Workman; Jordi Mestres; Bissan Al-Lazikani
Journal:  Curr Pharm Des       Date:  2016       Impact factor: 3.116

8.  How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology.

Authors:  Clemens Wittwehr; Hristo Aladjov; Gerald Ankley; Hugh J Byrne; Joop de Knecht; Elmar Heinzle; Günter Klambauer; Brigitte Landesmann; Mirjam Luijten; Cameron MacKay; Gavin Maxwell; M E Bette Meek; Alicia Paini; Edward Perkins; Tomasz Sobanski; Dan Villeneuve; Katrina M Waters; Maurice Whelan
Journal:  Toxicol Sci       Date:  2016-12-19       Impact factor: 4.849

9.  Expanding biological space coverage enhances the prediction of drug adverse effects in human using in vitro activity profiles.

Authors:  Ruili Huang; Menghang Xia; Srilatha Sakamuru; Jinghua Zhao; Caitlin Lynch; Tongan Zhao; Hu Zhu; Christopher P Austin; Anton Simeonov
Journal:  Sci Rep       Date:  2018-02-28       Impact factor: 4.379

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

Authors:  Matthew J O'Meara; Sara Ballouz; Brian K Shoichet; Jesse Gillis
Journal:  PLoS One       Date:  2016-07-28       Impact factor: 3.240

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