Design and application of a knowledge network for automatic prioritization of drug mechanisms.

ABSTRACT:

Motivation

Drug repositioning is an attractive alternative to de novo drug discovery due to reduced time and costs to bring drugs to market. Computational repositioning methods, particularly non-black-box methods that can account for and predict a drug's mechanism, may provide great benefit for directing future development. By tuning both data and algorithm to utilize relationships important to drug mechanisms, a computational repositioning algorithm can be trained to both predict and explain mechanistically novel indications.

Results

In this work, we examined the 123 curated drug mechanism paths found in the drug mechanism database (DrugMechDB) and after identifying the most important relationships, we integrated 18 data sources to produce a heterogeneous knowledge graph, M

SUBMITTER: Mayers M 

PROVIDER: S-EPMC9113361 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature