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Cancer statistics have increased worldwide over the years. The molecular basis for the onset of a cancer cell lies on genetic predisposition, endogenous compounds produced by cell metabolism, certain types of infection and environmental factors. Accumulated genetic alterations, such as mutations and polymorphisms, lead to a genome instability and consequently makes a regular cell into a cancer cell. Bioinformatics approaches, such as, systems biology and the investigation of hot spots on the interface of protein-protein interactions (PPIs), have helped the identification and design of small bioactive molecules to modulate PPIs and inactivate tumorous cells. Identifying polymorphic hot spot residues within protein domains or within interface of PPIs makes possible to reveal biochemical features and organization of pathways related to the onset of cancer that would confer survivability to cancer cells due to entropic advantage. RAD51 and p53 are strong candidate genes that influence susceptibility to cancer. Both proteins contain functional domains and interact with several other proteins, including tumor suppressors, oncogenes and DNA repairing proteins. Cancer shows a very complex genetic, molecular and biochemical signature. Biomedical research is driven towards a wider comprehension of the functional importance of polymorphisms and their association with human diseases. Here, we analyzed the interface of interaction between RAD51 and p53 and identified hot spots that could be of importance for the conformational structure of those proteins, their function and pattern of interaction with their partners. We have also shown that some of the hot spot amino acid residues are polymorphic, which could disrupt the interaction between p53 and RAD5, leading to a higher susceptibility to cancer. Future studies should be conducted in order to design small molecules that could modulate the interaction between RAD51 and p53 and guarantee proper homologous recombination and maintenance of genomic stability.
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Kleber Santiago Freitas e Silva (2018) studied this question.
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