Computational Discovery and Characterization of Cancer-associated Variants in DNA Transaction Enzymes: Impact of a Glioma–associated mutation on Thymine-DNA Glycosylase
4 affiliations
- 1Department of Physics
- 2University of Texas at Dallas
- 3Department of Chemistry and Biochemistry
- 4Department of Biology
Abstract
DNA transaction pathways play a fundamental role in maintaining genome integrity through the regulation of DNA replication, repair, recombination, and epigenetic modification. When these pathways are disrupted, it can lead to genomic instability and contribute to disease initiation and progression. Genome-wide association studies and follow–up analysis from data generated by these studies continue to identify numerous disease-associated variants, although functional characterization of missense mutations arising from these variants remains a challenge. In this study, we employed a hypothesis-driven computational framework to identify statistically significant cancer-associated variants in DNA transaction genes across four different cancer phenotypes using genome-wide association study databases. Bioinformatics analyses were used to prioritize missense variants based on their statistical significance. Among the identified variants, the thymine DNA glycosylase (TDG) missense variant rs4135113 was selected for detailed structural characterization because of the critical role of TDG in base excision repair and active DNA methylation. Classical molecular dynamics simulations were performed to investigate the impact of the resulting TDG variant on its structure and dynamics. In addition, the impact of biologically relevant post-translational modifications on both wild-type TDG and variant proteins were investigated. Our results uncover 74 previously unreported cancer–associated SNPS for the four tested phenotypes, including 7 pleiotropic variants. Additionally, our atomistic analysis of a glioma–associated TDG variant provides a detailed insights into how a cancer-associated variant in TDG may impact its function and highlight the importance of combining bioinformatics with molecular simulations to connect genetic data with underlying biological mechanisms.
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BibTeX
@misc{dissanayake2026computational,
title = {{Computational Discovery and Characterization of Cancer-associated Variants in DNA Transaction Enzymes: Impact of a Glioma–associated mutation on Thymine-DNA Glycosylase}},
author = {Upeksha C. Dissanayake and Architha Cunnapakkam and Ramya Konduru and G. Andrés Cisneros},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008985/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008985/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Computational Discovery and Characterization of Cancer-associated Variants in DNA Transaction Enzymes: Impact of a Glioma–associated mutation on Thymine-DNA Glycosylase
AU - Upeksha C. Dissanayake
AU - Architha Cunnapakkam
AU - Ramya Konduru
AU - G. Andrés Cisneros
PY - 2026
DA - 2026/09/17
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008985/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008985/v1
AB - DNA transaction pathways play a fundamental role in maintaining genome integrity through the regulation of DNA replication, repair, recombination, and epigenetic modification. When these pathways are disrupted, it can lead to genomic instability and contribute to disease initiation and progression. Genome-wide association studies and follow–up analysis from data generated by these studies continue to identify numerous disease-associated variants, although functional characterization of missense mutations arising from these variants remains a challenge. In this study, we employed a hypothesis-driven computational framework to identify statistically significant cancer-associated variants in DNA transaction genes across four different cancer phenotypes using genome-wide association study databases. Bioinformatics analyses were used to prioritize missense variants based on their statistical significance. Among the identified variants, the thymine DNA glycosylase (TDG) missense variant rs4135113 was selected for detailed structural characterization because of the critical role of TDG in base excision repair and active DNA methylation. Classical molecular dynamics simulations were performed to investigate the impact of the resulting TDG variant on its structure and dynamics. In addition, the impact of biologically relevant post-translational modifications on both wild-type TDG and variant proteins were investigated. Our results uncover 74 previously unreported cancer–associated SNPS for the four tested phenotypes, including 7 pleiotropic variants. Additionally, our atomistic analysis of a glioma–associated TDG variant provides a detailed insights into how a cancer-associated variant in TDG may impact its function and highlight the importance of combining bioinformatics with molecular simulations to connect genetic data with underlying biological mechanisms.
ER -