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
. 2023 Jul 5;51(W1):W129-W133.
doi: 10.1093/nar/gkad295.

DeepAlloDriver: a deep learning-based strategy to predict cancer driver mutations

Qianqian Song  1   2 , Mingyu Li  1 , Qian Li  2 , Xun Lu  1   2 , Kun Song  3 , Ziliang Zhang  2 , Jiale Wei  2   4 , Liang Zhang  5 , Jiacheng Wei  2   4 , Youqiong Ye  1 , Jinyin Zha  2 , Qiufen Zhang  2 , Qiang Gao  6 , Jiang Long  7 , Xinyi Liu  2 , Xuefeng Lu  4 , Jian Zhang  1   2   8
Affiliations

DeepAlloDriver: a deep learning-based strategy to predict cancer driver mutations

Qianqian Song et al. Nucleic Acids Res. .

Abstract

Driver mutations can contribute to the initial processes of cancer, and their identification is crucial for understanding tumorigenesis as well as for molecular drug discovery and development. Allostery regulates protein function away from the functional regions at an allosteric site. In addition to the known effects of mutations around functional sites, mutations at allosteric sites have been associated with protein structure, dynamics, and energy communication. As a result, identifying driver mutations at allosteric sites will be beneficial for deciphering the mechanisms of cancer and developing allosteric drugs. In this study, we provided a platform called DeepAlloDriver to predict driver mutations using a deep learning method that exhibited >93% accuracy and precision. Using this server, we found that a missense mutation in RRAS2 (Gln72 to Leu) might serve as an allosteric driver of tumorigenesis, revealing the mechanism of the mutation in knock-in mice and cancer patients. Overall, DeepAlloDriver would facilitate the elucidation of the mechanisms underlying cancer progression and help prioritize cancer therapeutic targets. The web server is freely available at: https://mdl.shsmu.edu.cn/DeepAlloDriver.

PubMed Disclaimer

Figures

Graphical Abstract
Graphical Abstract
Identification of allosteric driver mutations in cancers.
Figure 1.
Figure 1.
The Workflow of DeepAlloDriver.
Figure 2.
Figure 2.
The examples of DeepAlloDriver. (A) The driver mutation R507C is found at the NTRK1 allosteric site (PDB ID: 6D20). The protein structure is exhibited in both cartoon and transparent surface modes with allosteric site coloured in chartreuse and orthosteric site in deepsalmon. Residue R507C is highlighted in stick mode. (B) The driver mutation Q72L is found at the RRAS2 potential allosteric site (PDB ID: 2ERY). Allosteric and orthosteric sites are highlighted in skyblue and deepsalmon, respectively. Residue Q72L and ligand GDP are shown in stick mode.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Merlo L.M.F., Pepper J.W., Reid B.J., Maley C.C.. Cancer as an evolutionary and ecological process. Nat. Rev. Cancer. 2006; 6:924–935. - PubMed
    1. Pon J.R., Marra M.A.. Driver and passenger mutations in cancer. Annu. Rev. Pathol. Mech. Dis. 2015; 10:25–50. - PubMed
    1. Haber D.A., Settleman J.. Drivers and passengers. Nature. 2007; 446:145–146. - PubMed
    1. Bozic I., Antal T., Ohtsuki H., Carter H., Kim D., Chen S., Karchin R., Kinzler K.W., Vogelstein B., Nowak M.A.. Accumulation of driver and passenger mutations during tumor progression. Proc. Natl. Acad. Sci. U.S.A. 2010; 107:18545–18550. - PMC - PubMed
    1. Bokhari Y., Alhareeri A., Arodz T.. QuaDMutNetEx: a method for detecting cancer driver genes with low mutation frequency. BMC Bioinf. 2020; 21:122. - PMC - PubMed

Publication types