SNAP predicts effect of mutations on protein function

Abstract

Many non-synonymous single nucleotide polymorphisms (nsSNPs) in humans are suspected to impact protein function. Here, we present a publicly available server implementation of the method SNAP (screening for non-acceptable polymorphisms) that predicts the functional effects of single amino acid substitutions. SNAP identifies over 80% of the non-neutral mutations at 77% accuracy and over 76% of the neutral mutations at 80% accuracy at its default threshold. Each prediction is associated with a reliability index that correlates with accuracy and thereby enables experimentalists to zoom into the most promising predictions.

Fig. 1.

Examples of SNAP functionality. (A) SNAP-server predictions for mutations in INS_HUMAN associated with hyperproinsulenemia and diabetes-mellitus type II (Chan et al., ; Sakura et al., ; Shoelson et al., 1983). (B) SNAP predictions for comprehensive in silico mutagenesis (all-to-alanine). The crystal structure [PDB 2omg (Norrman et al., 2007)] shows an insulin NPH hexamer [insulin co-crystallized with zinc (sphere at the center) in presence of protamine/urea (not highlighted); picture produced by GRASP2 (Petrey and Honig, 2003)]. Red represents mutations predicted as non-neutral and blue represents neutral predictions. Residues in wire depiction are the same as in (A): V92, H34, F48 and F49 of INS_HUMAN (A chain V3, B chain H10, F24 and F25). SNAP predicts all of these to impact function when mutated to alanine. (C) More reliably predicted residues are predicted more accurately: for instance, >90% of the predictions with a reliability index=6 are expected to be right.