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Oxford University Press, Database, (2023), 2023

DOI: 10.1093/database/baad046

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APDB: a database on air pollutant characterization and similarity prediction

Journal article published in 2023 by Eva Viesi ORCID, Davide Stefano Sardina ORCID, Ugo Perricone ORCID, Rosalba Giugno ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract The World Health Organization estimates that 9 out of 10 people worldwide breathe air containing high levels of pollutants. Long-term and chronic exposure to high concentrations of air pollutants is associated with deleterious effects on vital organs, including increased inflammation in the lungs, oxidative stress in the heart and disruption of the blood–brain barrier. For this reason, in an effort to find an association between exposure to pollutants and the toxicological effects observable on human health, an online resource collecting and characterizing in detail pollutant molecules could be helpful to investigate their properties and mechanisms of action. We developed a database, APDB, collecting air-pollutant-related data from different online resources, in particular, molecules from the US Environmental Protection Agency, their associated targets and bioassays found in the PubChem chemical repository and their computed molecular descriptors and quantum mechanics properties. A web interface allows (i) to browse data by category, (ii) to navigate the database by querying molecules and targets and (iii) to visualize and download molecule and target structures as well as computed descriptors and similarities. The desired data can be freely exported in textual/tabular format and the whole database in SQL format. Database URL http://apdb.di.univr.it