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Evaluation of local structure alphabets based on residue burial
Author(s) -
Karchin Rachel,
Cline Melissa,
Karplus Kevin
Publication year - 2004
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.20008
Subject(s) - predictability , hidden markov model , residue (chemistry) , alphabet , accessible surface area , protein structure prediction , casp , mathematics , computer science , chemistry , artificial intelligence , algorithm , protein structure , pattern recognition (psychology) , statistics , computational chemistry , biochemistry , linguistics , philosophy
Residue burial, which describes a protein residue's exposure to solvent and neighboring atoms, is key to protein structure prediction, modeling, and analysis. We assessed 21 alphabets representing residue burial, according to their predictability from amino acid sequence, conservation in structural alignments, and utility in one fold‐recognition scenario. This follows upon our previous work in assessing nine representations of backbone geometry.1 The alphabet found to be most effective overall has seven states and is based on a count of C β atoms within a 14 Å‐radius sphere centered at the C β of a residue of interest. When incorporated into a hidden Markov model ( HMM ), this alphabet gave us a 38% performance boost in fold recognition and 23% in alignment quality. Proteins 2004. © 2004 Wiley‐Liss, Inc.