Comprehensive in silico mutagenesis highlights functionally important residues in proteins

By Yana Bromberg, Burkhard Rost. 2008

60 citations recorded by the source corpus.

Subfields: Genetics, Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Better prediction of functional effects for sequence variants (2015, positive): “Both versions of SNAP2 have been optimized towards runtime efficiency to enable large-scale in silico mutagenesis studies that probe the landscape of protein mutability [56,58] to learn important news about protein structure and function.”
Performance of computational tools in evaluating the functional impact of laboratory-induced amino acid mutations (2012, background): “First, the laboratory mutation sets are expected to contain an overabundance of changes to alanine because of alanine scanning, which is a cost-efficient alternative to testing every possible non-native amino acid (Bromberg and Rost, 2008).”
Gkmexplain: Fast and Accurate Interpretation of Nonlinear Gapped k-mer SVMs Using Integrated Gradients (2018, methodology): “In-silico In-silico mutagenesis (ISM) [4], an interpretation approach that consists of performing individual perturbations and observing the impact on the output, can be computationally inefﬁcient and can fail to reveal the presence of motifs when nonlinear saturation effects are present [13].”
SNAP predicts effect of mutations on protein function (2008, methodology): “…a measure of reliability: here, we present the first webserver implementation of SNAP (screening for non-acceptable polymorphisms), a method that combines many sequence analysis tools in a battery of neural networks to predict the functional effects of nsSNPs (Bromberg and Rost, 2007, 2008).”
Disease-related mutations predicted to impact protein function (2012, background): “the higher the score, the more likely the mutation impacts function [19,21,22].”