Zebrafish as a model to evaluate peptide-related cancer therapies

Austin Y. Shull, Chien An A. Hu, Yong Teng

Research output: Contribution to journalReview article

2 Citations (Scopus)

Abstract

Peptide-derived drug discovery has experienced a remarkable resurgence in the past decade since the failure of small-molecule modulators to effectively access the large binding surfaces of intracellular protein–protein interactions as well as “undruggable” residues of certain disease-driving proteins. However, the effectiveness of peptide-based cancer therapies is being questioned in light of declines in pharmaceutical R&D efficiency. As a model of whole organism, zebrafish provide a means to develop promising peptide and protein anticancer agents in an informative, cost-effective and time-efficient manner, which also allows for surveying mechanisms of drug action and optimization of drug delivery system. This review highlights the achievements and potential of zebrafish for modelling human cancer and for peptide-based drug discovery and development. Specific challenges, possible strategies and future prospects are also discussed.

Original languageEnglish (US)
Pages (from-to)1907-1913
Number of pages7
JournalAmino Acids
Volume49
Issue number12
DOIs
StatePublished - Dec 1 2017

Fingerprint

Second Primary Neoplasms
Zebrafish
Peptides
Drug Discovery
Surveying
Drug Delivery Systems
Pharmaceutical Preparations
Antineoplastic Agents
Modulators
Neoplasms
Proteins
Efficiency
Costs and Cost Analysis
Molecules
Costs
Therapeutics

Keywords

  • Anti-cancer
  • Cancer models
  • Drugs
  • Peptides
  • Strategy and therapy
  • Zebrafish

ASJC Scopus subject areas

  • Biochemistry
  • Clinical Biochemistry
  • Organic Chemistry

Cite this

Zebrafish as a model to evaluate peptide-related cancer therapies. / Shull, Austin Y.; Hu, Chien An A.; Teng, Yong.

In: Amino Acids, Vol. 49, No. 12, 01.12.2017, p. 1907-1913.

Research output: Contribution to journalReview article

Shull, Austin Y. ; Hu, Chien An A. ; Teng, Yong. / Zebrafish as a model to evaluate peptide-related cancer therapies. In: Amino Acids. 2017 ; Vol. 49, No. 12. pp. 1907-1913.
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