One of the great challenges in modern biology is understanding how changes in amino acids that are the building blocks of proteins lead to changes in the characteristics of a living organism. This Research Infrastructure Improvement Track-2 Focused EPSCoR Collaborations (RII Track-2 FEC) award addresses this challenge by using computer simulations, mathematical modeling, and experiments to determine how amino acid changes modify the way that proteins interact with other molecules.
Our central scientific hypothesis : protein biophysical models provide an efficient framework for predicting how mutations – alone, in combination, and in different environments – influence protein stability, affinity for substrates and partners, and the mappings to higher-level phenotypes.
Our methodological hypothesis: this biophysics-first framework can be applied to diverse experimental systems to reveal general underlying principles of genotype to phenotype mapping, uncover gaps in understanding, and suggest potential generic and system specific extensions; these will motivate future competitive research proposals and build research capacity across all jurisdictions.
We will test our scientific and methodological hypotheses via the following objectives:
Determine to what extent modeling can predict the effects of single mutations on biophysical phenotypes and higher-level phenotypes in RSV and beta- lactamase.
Determine to what extent modeling can predict the effects of combinations of small sets of mutations on biophysical phenotypes and higher-level phenotypes in RSV and beta- lactamase.
Extend to additional model systems by applying the lessons and workflow from 1 and 2, thereby catalyzing research and exploring generalities in genotype to phenotype mapping.
Test our models on combinations of larger sets of mutations that arose during selection in clinical, natural, or laboratory settings.
Determine how biophysically-relevant environmental change alters the mapping of genetic variation to organismal phenotypes.