TargetDB: A target information aggregation tool and tractability predictor.
PLoS One
; 15(9): e0232644, 2020.
Article
en En
| MEDLINE
| ID: mdl-32877430
ABSTRACT
When trying to identify new potential therapeutic protein targets, access to data and knowledge is increasingly important. In a field where new resources and data sources become available every day, it is crucial to be able to take a step back and look at the wider picture in order to identify potential drug targets. While this task is routinely performed by bespoke literature searches, it is often time-consuming and lacks uniformity when comparing multiple targets at one time. To address this challenge, we developed TargetDB, a tool that aggregates public information available on given target(s) (links to disease, safety, 3D structures, ligandability, novelty, etc.) and assembles it in an easy to read output ready for the researcher to analyze. In addition, we developed a target scoring system based on the desirable attributes of good therapeutic targets and machine learning classification system to categorize novel targets as having promising or challenging tractrability. In this manuscript, we present the methodology used to develop TargetDB as well as test cases.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Bases de Datos como Asunto
/
Minería de Datos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Animals
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Humans
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2020
Tipo del documento:
Article