Protein structure-based evaluation of missense variants: Resources, challenges and future directions
Alessia David, Michael J.E. Sternberg
Abstract
We provide an overview of the methods that can be used for protein structure-based evaluation of missense variants. The algorithms can be broadly divided into those that calculate the difference in free energy (ΔΔG) between the wild type and variant structures and those that use structural features to predict the damaging effect of a variant without providing a ΔΔG. A wide range of machine learning approaches have been employed to develop those algorithms. We also discuss challenges and opportunities for variant interpretation in view of the recent breakthrough in three-dimensional structural modelling using deep learning.
Topics & Concepts
Missense mutationComputer scienceComputational biologyArtificial intelligenceProtein structureMachine learningBiologyMutationGeneticsGeneBiochemistryRNA and protein synthesis mechanismsGenomics and Phylogenetic StudiesProtein Structure and Dynamics