Title |
Probing the chemical–biological relationship space with the Drug Target Explorer
|
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Published in |
Journal of Cheminformatics, August 2018
|
DOI | 10.1186/s13321-018-0297-4 |
Pubmed ID | |
Authors |
Robert J. Allaway, Salvatore La Rosa, Justin Guinney, Sara J. C. Gosline |
Abstract |
Modern phenotypic high-throughput screens (HTS) present several challenges including identifying the target(s) that mediate the effect seen in the screen, characterizing 'hits' with a polypharmacologic target profile, and contextualizing screen data within the large space of drugs and screening models. To address these challenges, we developed the Drug-Target Explorer. This tool allows users to query molecules within a database of experimentally-derived and curated compound-target interactions to identify structurally similar molecules and their targets. It enables network-based visualizations of the compound-target interaction space, and incorporates comparisons to publicly-available in vitro HTS datasets. Furthermore, users can identify molecules using a query target or set of targets. The Drug Target Explorer is a multifunctional platform for exploring chemical space as it relates to biological targets, and may be useful at several steps along the drug development pipeline including target discovery, structure-activity relationship, and lead compound identification studies. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 38% |
Comoros | 1 | 6% |
Spain | 1 | 6% |
Sweden | 1 | 6% |
Japan | 1 | 6% |
Unknown | 6 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 8 | 50% |
Members of the public | 7 | 44% |
Science communicators (journalists, bloggers, editors) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 35 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 26% |
Researcher | 5 | 14% |
Student > Master | 4 | 11% |
Other | 3 | 9% |
Lecturer | 3 | 9% |
Other | 6 | 17% |
Unknown | 5 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 10 | 29% |
Biochemistry, Genetics and Molecular Biology | 7 | 20% |
Agricultural and Biological Sciences | 3 | 9% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
Computer Science | 2 | 6% |
Other | 3 | 9% |
Unknown | 8 | 23% |