Towards the routine use of in silico screenings for drug discovery using metabolic modelling
Author(s) -
Tamara Bintener,
Maria Pires Pacheco,
Thomas Sauter
Publication year - 2020
Publication title -
biochemical society transactions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.562
H-Index - 144
eISSN - 1470-8752
pISSN - 0300-5127
DOI - 10.1042/bst20190867
Subject(s) - drug repositioning , in silico , cancer drugs , drug , computational biology , drug discovery , cancer , drug development , computer science , bioinformatics , biology , gene , pharmacology , genetics
Currently, the development of new effective drugs for cancer therapy is not only hindered by development costs, drug efficacy, and drug safety but also by the rapid occurrence of drug resistance in cancer. Hence, new tools are needed to study the underlying mechanisms in cancer. Here, we discuss the current use of metabolic modelling approaches to identify cancer-specific metabolism and find possible new drug targets and drugs for repurposing. Furthermore, we list valuable resources that are needed for the reconstruction of cancer-specific models by integrating various available datasets with genome-scale metabolic reconstructions using model-building algorithms. We also discuss how new drug targets can be determined by using gene essentiality analysis, an in silico method to predict essential genes in a given condition such as cancer and how synthetic lethality studies could greatly benefit cancer patients by suggesting drug combinations with reduced side effects.
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