MuD: an interactive web server for the prediction of non-neutral substitutions using protein structural data.
The discrimination between functionally neutral amino acid substitutions and non-neutral mutations, affecting protein function, is very important for our understanding of diseases. The rapidly growing amounts of experimental data enable the development of computational tools to facilitate the annotation of these substitutions. Here, we describe a Random Forests-based classifier, named Mutation Detector (MuD) that utilizes structural and sequence-derived features to assess the impact of a given substitution on the protein function. In its automatic mode, MuD is comparable to alternative tools in performance. However, the uniqueness of MuD is that user-reported protein-specific structural and functional information can be added at run-time, thereby enhancing the prediction accuracy further. The MuD server, available at http://mud.tau.ac.il, assigns a reliability score to every prediction, thus offering a useful tool for the prioritization of substitutions in proteins with an available 3D structure.
Wainreb
Gilad
G
Department of Biochemistry and Molecular Biology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel.
Ashkenazy
Haim
H
Bromberg
Yana
Y
Starovolsky-Shitrit
Alina
A
Haliloglu
Turkan
T
Ruppin
Eytan
E
Avraham
Karen B
KB
Rost
Burkhard
B
Ben-Tal
Nir
N
D000465:Algorithms; D019943:Amino Acid Substitution; D001185:Artificial Intelligence; D020407:Internet; D011487:Protein Conformation; D015203:Reproducibility of Results; D017386:Sequence Homology, Amino Acid; D012984:Software