ΦX174 bacteriophage viability predicted by protein biophysical modeling

Area of Science:

• Evolutionary Biology
• Molecular Biology
• Genetics

Background:

• Genotype-phenotype (GP) maps are crucial for predicting evolutionary trajectories.
• Existing research shows pervasive epistasis, non-normal fitness distributions, and complex GP maps for high-level phenotypes.

Purpose of the Study:

• To evaluate the predictive power of intermediate phenotypes, specifically the stability of the G capsid protein, for complex phenotypes in bacteriophage ΦX174.
• To compare various molecular modeling, phylogenetic, and biochemical methods for predicting the effects of amino acid substitutions.

Main Methods:

• Construction of a large mutational library for the G protein of bacteriophage ΦX174.
• Application of diverse molecular modeling techniques to predict free energies of folding and binding.
• Analysis of phylogenetic and basic biochemical/biophysical properties of amino acid substitutions.

Main Results:

• Bacteriophage ΦX174 tolerates approximately 50% of introduced amino acid substitutions in its G protein.
• Molecular modeling methods complement other substitution models in predicting organism viability.
• Mutations with predicted large destabilizing effects are generally detrimental and often occur at conserved residues.

Conclusions:

• While large-effect mutations are informative, predicting ΦX174 phenotypes remains challenging.
• Further investigation into confounding factors like codon bias may improve viability predictions.
• Intermediate phenotypes like protein stability offer insights but do not fully explain complex genotype-phenotype relationships.