There is compelling evidence that inhibition of DNA repair contributes to the carcinogenic and co-carcinogenic actions of arsenic. Two DNA repair proteins (PARP-1 and XPA) have been reported as direct arsenic targets based on interference with zinc finger function. To date, identification of arsenic targets in DNA repair pathways has been based solely on empirical evidence and it is unknown whether there are additional direct and highly sensitive DNA repair targets. Our recent work demonstrates preferential interaction of arsenite with zinc finger peptides containing 3 or 4 cysteine residues and arsenite-dependent zinc release from specific DNA repair proteins isolated from exposed cells in C3H1 (e.g. PARP-1) and C4 (e.g. XPA), but not C2H2, zinc finger proteins. These findings provide evidence for target selectivity of zinc finger proteins based on the number of cysteine residues. The objective of this project is to implement an iterative bioinformatic/ experimental approach to identify, test and refine the selection of high-affinity arsenic targets in the DNA repair pathway, in order to gain insights into mechanisms of arsenic co-carcinogenicity and DNA repair inhibition. This work will yield critical information on the relative sensitivities of identified targets, the importanceof number and configuration of cysteine residues in governing observed sensitivities, and the role of distinct zinc finger secondary structures (e.g. ring finger, treble clef, zinc ribbon) in determining vulnerability to arsenic attack. Preliminary results using a bioinformatic approach identified novel candidate DNA repair targets containing zinc finger structures and activities distinct from PARP-1 or XPA, suggesting possible new actions of arsenic in DNA repair inhibition. Based on our published and preliminary findings, we hypothesize that a coupled bioinformatic/ experimental approach can be developed and applied to predict high affinity arsenic targets in DNA repair, based on zinc finger configuration. To test this hypothesis we will: 1) Identify putative arsenic targets in DNA repair using an unbiased zinc finger motif pattern recognition algorithm, correlated with structural bioinformatic data and literature annotations from automated online database searches, and further classified through phylogenetic and pathway analyses. The DNA repair pathway is used as the validation set since it represents a well-established and biologically-relevant focus of direct significance to arsenic cancer biology and epidemiology. 2) Test arsenite interaction with predicted targets using biochemical and cell biology approaches to validate potential targets, establish relative sensitivities to arsenic, and provide information on structural characteristics for iterative refinement of the bioinformatics approach. The outcomes from the proposed studies are expected to advance the field by 1) expanding our understanding of the scope of zinc finger DNA repair protein disruption by arsenic, 2) identifying novel and sensitive targets, and 3) establishing whether specific zinc finger structures represent preferential targets. These results will inform testable hypotheses regarding additional potential arsenic targets in cancer and other arsenic-associated diseases.
Given the widespread public exposure to arsenic in municipal and private water supplies, there is interest and concern in observations that arsenic concentrations at or near the EPA maximum contaminant level greatly enhance the carcinogenic potential of other DNA damaging agents and inhibit DNA repair. Thus, arsenic may contribute to elevated cancer risk when individuals are exposed to other carcinogens through occupational, environmental or lifestyle exposures. This project represents the first effort to computationally predict highly sensitive arsenic targets to better understand the impact of arsenic on DNA repair and inform strategies to reverse or prevent the adverse health effects of arsenic exposure in humans.