Influence of Model Structures on Predictors of Protein Stability Changes from Single-Point Mutations.
Cesare RolloCorrado PancottiGiovanni BiroloIvan RossiTiziana SanaviaPiero FariselliPublished in: Genes (2023)
Missense variation in genomes can affect protein structure stability and, in turn, the cell physiology behavior. Predicting the impact of those variations is relevant, and the best-performing computational tools exploit the protein structure information. However, most of the current protein sequence variants are unresolved, and comparative or ab initio tools can provide a structure. Here, we evaluate the impact of model structures, compared to experimental structures, on the predictors of protein stability changes upon single-point mutations, where no significant changes are expected between the original and the mutated structures. We show that there are substantial differences among the computational tools. Methods that rely on coarse-grained representation are less sensitive to the underlying protein structures. In contrast, tools that exploit more detailed molecular representations are sensible to structures generated from comparative modeling, even on single-residue substitutions.
Keyphrases
- high resolution
- protein protein
- amino acid
- binding protein
- magnetic resonance
- healthcare
- stem cells
- computed tomography
- small molecule
- autism spectrum disorder
- cell therapy
- intellectual disability
- working memory
- genome wide
- mass spectrometry
- social media
- sensitive detection
- copy number
- single molecule
- fluorescent probe