ArticleNucleic acids research2019
AlloDriver: a method for the identification and analysis of cancer driver targets.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 42 citations in OpenAlex.
- AI accelerate the identification of druggable targets by 3D structures of proteins and compounds.NPJ precision oncology · 2026Review
- Bioinformatics-based screening and prediction of compounds and antigen epitopes for immune targets with point mutations in colitis-associated colorectal cancer.Discover oncology · 2025Article
- Article
- CancerHubs: a systematic data mining and elaboration approach for identifying novel cancer-related protein interaction hubs.Briefings in bioinformatics · 2024Article
- The value of protein allostery in rational anticancer drug design: an update.Expert opinion on drug discovery · 2024Review
- ImmRNA: a database of RNAs associated with tumor immunity.Database : the journal of biological databases and curation · 2024Article
- Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.Briefings in bioinformatics · 2024Review
- CDMPred: a tool for predicting cancer driver missense mutations with high-quality passenger mutations.PeerJ · 2024Article
- AlloReverse: multiscale understanding among hierarchical allosteric regulations.Nucleic acids research · 2023Article
- DeepAlloDriver: a deep learning-based strategy to predict cancer driver mutations.Nucleic acids research · 2023Article
- A Structure-Based Allosteric Modulator Design Paradigm.Health data science · 2023Review
- Allostery: Allosteric Cancer Drivers and Innovative Allosteric Drugs.Journal of molecular biology · 2022Review
- Mechanism of activation and the rewired network: New drug design concepts.Medicinal research reviews · 2022Review
- Targeting RAS phosphorylation in cancer therapy: Mechanisms and modulators.Acta pharmaceutica Sinica. B · 2021Review
- Untangling Dual-Targeting Therapeutic Mechanism of Epidermal Growth Factor Receptor (EGFR) Based on Reversed Allosteric Communication.Pharmaceutics · 2021Article
- Computational methods for cancer driver discovery: A survey.Theranostics · 2021Review
- AI-Driver: an ensemble method for identifying driver mutations in personal cancer genomes.NAR genomics and bioinformatics · 2020Article
- Untangling a complex web: Computational analyses of tumor molecular profiles to decode driver mechanisms.Journal of genetics and genomics = Yi chuan xue bao · 2020Review
- PI3K inhibitors: review and new strategies.Chemical science · 2020Review
- Integrated Computational Approaches and Tools forAllosteric Drug Discovery.International journal of molecular sciences · 2020Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying the variants that alter protein function is a promising strategy for deciphering the biological consequences of somatic mutations during tumorigenesis, which could provide novel targets for the development of cancer therapies. Here, based on our previously developed method, we present a strategy called AlloDriver that identifies cancer driver genes/proteins as possible targets from mutations. AlloDriver utilizes structural and dynamic features to prioritize potentially functional genes/proteins in individual cancers via mapping mutations generated from clinical cancer samples to allosteric/orthosteric sites derived from three-dimensional protein structures. This strategy exhibits desirable performance in the reemergence of known cancer driver mutations and genes/proteins from clinical samples. Significantly, the practicability of AlloDriver to discover novel cancer driver proteins in head and neck squamous cell carcinoma (HNSC) was tested in a real case of human protein tyrosine phosphatase, receptor type K (PTPRK) through a L1143F driver mutation located at the allosteric site of PTPRK, which was experimentally validated by cell proliferation assay. AlloDriver is expected to help to uncover innovative molecular mechanisms of tumorigenesis by perturbing proteins and to discover novel targets based on cancer driver mutations. The AlloDriver is freely available to all users at http://mdl.shsmu.edu.cn/ALD.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.