Abstract:
:Prediction of protein structure from its amino acid sequence is still a challenging problem. The complete physicochemical understanding of protein folding is essential for the accurate structure prediction. Knowledge of residue solvent accessibility gives useful insights into protein structure prediction and function prediction. In this work, we propose a random forest method, RSARF, to predict residue accessible surface area from protein sequence information. The training and testing was performed using 120 proteins containing 22006 residues. For each residue, buried and exposed state was computed using five thresholds (0%, 5%, 10%, 25%, and 50%). The prediction accuracy for 0%, 5%, 10%, 25%, and 50% thresholds are 72.9%, 78.25%, 78.12%, 77.57% and 72.07% respectively. Further, comparison of RSARF with other methods using a benchmark dataset containing 20 proteins shows that our approach is useful for prediction of residue solvent accessibility from protein sequence without using structural information. The RSARF program, datasets and supplementary data are available at http://caps.ncbs.res.in/download/pugal/RSARF/.
journal_name
Protein Pept Lettjournal_title
Protein and peptide lettersauthors
Pugalenthi G,Kandaswamy KK,Chou KC,Vivekanandan S,Kolatkar Pdoi
10.2174/092986612798472875subject
Has Abstractpub_date
2012-01-01 00:00:00pages
50-6issue
1eissn
0929-8665issn
1875-5305pii
BSP/ PPL/ E pub/0385journal_volume
19pub_type
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