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Updated: Nov 24, 2025
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Molecular dynamics approach to identification of new OGG1 cancer-associated somatic variants with impaired activity
Aleksandr V Popov1, Anton V Endutkin1, Darya D Yatsenko2
1Laboratory of Genome and Protein Engineering, SB RAS Institute of Chemical Biology and Fundamental Medicine, Novosibirsk, Russia.
Abstract:
DNA of living cells is always exposed to damaging factors. To counteract the consequences of DNA lesions, cells have evolved several DNA repair systems, among which base excision repair is one of the most important systems. Many currently used antitumor drugs act by damaging DNA, and DNA repair often interferes with chemotherapy and radiotherapy in cancer cells. Tumors are usually extremely genetically heterogeneous, often bearing mutations in DNA repair genes. Thus, knowledge of the functionality of cancer-related variants of proteins involved in DNA damage response and repair is of great interest for personalization of cancer therapy. Although computational methods to predict the variant functionality have attracted much attention, at present, they are mostly based on sequence conservation and make little use of modern capabilities in computational analysis of 3D protein structures. We have used molecular dynamics (MD) to model the structures of 20 clinically observed variants of a DNA repair enzyme, 8-oxoguanine DNA glycosylase. In parallel, we have experimentally characterized the activity, thermostability, and DNA binding in a subset of these mutant proteins. Among the analyzed variants of 8-oxoguanine DNA glycosylase, three (I145M, G202C, and V267M) were significantly functionally impaired and were successfully predicted by MD. Alone or in combination with sequence-based methods, MD may be an important functional prediction tool for cancer-related protein variants of unknown significance.
Insights
Molecular dynamics accurately predicted functional impairments in DNA repair enzyme variants. This advance aids in understanding cancer mutations and personalizing cancer therapies by assessing protein variant significance.
Area of Science:
- Biochemistry
- Molecular Biology
- Genetics
Background:
- DNA repair mechanisms are crucial for cellular integrity and counteract DNA damage from endogenous and exogenous factors.
- Base excision repair is a vital DNA repair pathway, and its enzymes are often implicated in cancer due to tumor genetic heterogeneity.
- Understanding the functional impact of DNA repair gene variants is essential for developing personalized cancer therapies that overcome treatment resistance.
Purpose of the Study:
- To investigate the functional consequences of clinically observed variants in the DNA repair enzyme 8-oxoguanine DNA glycosylase.
- To evaluate the utility of molecular dynamics (MD) simulations in predicting the functional impact of these variants.
- To correlate computational predictions with experimental characterization of variant functionality.
Main Methods:
- Utilized molecular dynamics (MD) simulations to model the 3D structures of 20 variants of 8-oxoguanine DNA glycosylase.
- Experimentally assessed the activity, thermostability, and DNA binding capabilities of a subset of these mutant proteins.
- Compared MD-predicted structural and dynamic changes with experimental functional data.
Main Results:
- MD simulations successfully predicted functional impairments in specific 8-oxoguanine DNA glycosylase variants.
- Three variants (I145M, G202C, and V267M) demonstrated significantly impaired function and were accurately identified by MD.
- Experimental data corroborated the functional deficits predicted by MD simulations for these variants.
Conclusions:
- Molecular dynamics (MD) is a powerful tool for predicting the functional significance of protein variants involved in DNA repair.
- MD, potentially combined with sequence-based methods, can aid in the functional assessment of cancer-related protein variants of unknown significance.
- This approach holds promise for advancing personalized cancer therapy by informing treatment strategies based on individual tumor genetic profiles.
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