Accessible Surface Area and the Prediction of the Phenotypes of Missense
Mutations
Abstract
Distinguishing between harmful and benign genetic variations is
fundamental to our understanding of the relationship between genome and
disease in general and for personalized medicine in particular. We
investigated the relationship between predicted change in RASA and the
phenotype of a missense mutation (MM). The ASAquick program was used to
obtain RASA predictions for the original and mutated sequence and a
parameter, δ , was introduced to assess the change in RASA for a given
MM. We find that predicted RASA shows a robust, intricate signal with
respect to genetic variation and that changes in RASA between variants
can form a basis for a simple and quick predictor of the effect of MMs.
Furthermore, we find that for hydrophobic residues, increase in the RASA
corresponds to an increase in the likelihood that a MM would be harmful.
For hydrophilic residues we find that a decrease in the RASA corresponds
to a likelihood that a MM would be harmful. We also find that the size
of the change in predicted RASA plays a role in determining the effect
of a given MM. In future work we plan to use these results in developing
more sophisticated forms of MM phenotype predictors.