Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2015:2015:239654.
doi: 10.1155/2015/239654. Epub 2015 Apr 28.

A survey on the computational approaches to identify drug targets in the postgenomic era

Yan-Fen Dai  1 , Xing-Ming Zhao  2
Affiliations
Review

A survey on the computational approaches to identify drug targets in the postgenomic era

Yan-Fen Dai et al. Biomed Res Int. 2015.

Abstract

Identifying drug targets plays essential roles in designing new drugs and combating diseases. Unfortunately, our current knowledge about drug targets is far from comprehensive. Screening drug targets in the lab is an expensive and time-consuming procedure. In the past decade, the accumulation of various types of omics data makes it possible to develop computational approaches to predict drug targets. In this paper, we make a survey on the recent progress being made on computational methodologies that have been developed to predict drug targets based on different kinds of omics data and drug property data.

PubMed Disclaimer

Figures

Figure 1
Figure 1
A schematic view of identifying drug-target interactions based on drug-induced gene expression profiles. (a) The drug-induced gene expression profiles across cell lines. (b) Define a gene signature for each compound and calculate the MOA similarity between each pair of drugs. (c) Predict targets for novel drugs with the assumption that drugs with similar MOAs are likely to target same proteins.
Figure 2
Figure 2
A schematic view of identifying drug-target interaction from molecular networks. (a) Identify drug targets from PPIN supposing that proteins in close proximity of the PPIN are more likely targeted by the same drug(s). (b) Predict drug targets based on metabolic networks assuming that the targets are able to interrupt the pathological procedure so that the disease status can be reversed to normal status.
Figure 3
Figure 3
A schematic view of identifying drug-target interactions based on drug effect profiles. (a) Identify drug-target interaction based on therapy information by assuming that drugs with similar therapy may target same protein(s). (b) Predict drug targets based on side effects supposing that drugs with similar side effect have common target(s).
Figure 4
Figure 4
Functional distribution of human proteins (a), drug targets (b), neighbor proteins of drug targets (c) in the PPIN, and drug therapeutic targets (d).
See this image and copyright information in PMC

References

    1. DiMasi J. A., Hansen R. W., Grabowski H. G. The price of innovation: new estimates of drug development costs. Journal of Health Economics. 2003;22(2):151–185. doi: 10.1016/S0167-6296(02)00126-1. - DOI - PubMed
    1. Wan X., Zhang W., Li L., Xie Y., Li W., Huang N. A new target for an old drug: Identifying mitoxantrone as a nanomolar inhibitor of PIM1 kinase via kinome-wide selectivity modeling. Journal of Medicinal Chemistry. 2013;56(6):2619–2629. doi: 10.1021/jm400045y. - DOI - PubMed
    1. Andrews W. J., Panova T., Normand C., Gadal O., Tikhonova I. G., Panov K. I. Old drug, new target: ellipticines selectively inhibit RNA polymerase I transcription. Journal of Biological Chemistry. 2013;288(7):4567–4582. doi: 10.1074/jbc.M112.411611. - DOI - PMC - PubMed
    1. Kuhn M., Szklarczyk D., Pletscher-Frankild S., et al. STITCH 4: integration of protein-chemical interactions with user data. Nucleic Acids Research. 2014;42(1):D401–D407. doi: 10.1093/nar/gkt1207. - DOI - PMC - PubMed
    1. Knox C., Law V., Jewison T., et al. DrugBank 3.0: a comprehensive resource for “Omics” research on drugs. Nucleic Acids Research. 2011;39(1):D1035–D1041. doi: 10.1093/nar/gkq1126. - DOI - PMC - PubMed

Publication types

LinkOut - more resources