A Computational Approach for the Prediction of p53 and BCL-2 Protein-Protein Interactions.

p53 has long been studied as a major regulator in cellular pathways, resulting in a plethora of information on the structure and function of this protein as a frequently mutated tumor suppressor. Recent studies have demonstrated how the p53 transcription activation domain (TAD) interacts with the BH3-binding pocket of BCL-2 to regulate cell survival/death. While the in vitro studies on p53 and BCL-2 have frequently used truncated and stabilized proteins of p53 to ensure crystallization, these mutated proteins are not naturally observed in cells. Thus, it becomes important to find a way in silico to simulate how a full-length monomer with the unaltered sequence of wild-type (WT) or missense mutant (MT) p53 interacts with BCL-2. Our objective is to provide a predictive insight into how p53 monomers might interact with BCL-2 through the combination of previously published algorithms. Using pre-established computational techniques in silico, the interactions between p53 variants and BCL-2 were compared to existing crystals to ensure the validity of the current method, and the affinities were predicted to explore the strength of these interactions. Here, we found that this protocol was able to replicate some of the amino acid interactions identified in the previous literature, as well as identify affinities between each WT/MT p53 and BCL-2. Most major MT p53 variants are predicted to directly interact with BCL-2, but have a decrease in affinity compared to WT p53, suggesting a potential increase in BCL-2 survival activity. Together, the method described here can potentially be useful as a predictive workflow to inform future studies in vitro and in vivo.