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Integrate Omics Data and Molecular Dynamics Simulations toward Better Understanding of Human 14-3-3 Interactomes and
JoAnne J Babula1, Jing-Yuan Liu2
1Department of Pharmacology and Toxicology, Indiana University School of Medicine, 980 W. Walnut Street, Indianapolis, IN 46202, USA.
Abstract:
The 14-3-3 protein family is among the most extensively studied, yet still largely mysterious protein families in mammals to date. As they are well recognized for their roles in apoptosis, cell cycle regulation, and proliferation in healthy cells, aberrant 14-3-3 expression has unsurprisingly emerged as instrumental in the development of many cancers and in prognosis. Interestingly, while the seven known 14-3-3 isoforms in humans have many similar functions across cell types, evidence of isoform-specific functions and localization has been observed in both healthy and diseased cells. The strikingly high similarity among 14-3-3 isoforms has made it difficult to delineate isoform-specific functions and for isoform-specific targeting. Here, we review our knowledge of 14-3-3 interactome(s) generated by high-throughput techniques, bioinformatics, structural genomics and chemical genomics and point out that integrating the information with molecular dynamics (MD) simulations may bring us new opportunity to the design of isoform-specific inhibitors, which can not only be used as powerful research tools for delineating distinct interactomes of individual 14-3-3 isoforms, but also can serve as potential new anti-cancer drugs that selectively target aberrant 14-3-3 isoform.
Insights
The 14-3-3 protein family plays roles in cell regulation and cancer. Integrating interactome data with molecular dynamics may enable the development of isoform-specific inhibitors for cancer therapy.
Area of Science:
- Molecular Biology
- Biochemistry
- Cancer Research
Background:
- The 14-3-3 protein family is crucial for cellular processes like apoptosis and proliferation.
- Aberrant 14-3-3 expression is linked to cancer development and prognosis.
- Despite high similarity, distinct isoform-specific functions and localizations exist.
Purpose of the Study:
- To review current knowledge of 14-3-3 interactomes.
- To explore the potential of integrating diverse data for isoform-specific targeting.
- To identify opportunities for developing novel anti-cancer therapeutics.
Main Methods:
- Review of high-throughput techniques, bioinformatics, structural genomics, and chemical genomics data.
- Analysis of 14-3-3 protein interactomes.
- Integration with molecular dynamics (MD) simulations.
Main Results:
- High-throughput and omics approaches have generated extensive 14-3-3 interactome data.
- Molecular dynamics simulations offer a promising avenue for understanding isoform-specific interactions.
- The high similarity among 14-3-3 isoforms presents a challenge for targeted drug development.
Conclusions:
- Integrating interactome data with MD simulations can facilitate the design of isoform-specific inhibitors.
- These inhibitors can serve as research tools to delineate distinct isoform functions.
- Targeting specific 14-3-3 isoforms holds potential for developing novel anti-cancer drugs.
