RSARF: prediction of residue solvent accessibility from protein sequence using random forest method.

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 Lett

authors

Pugalenthi G,Kandaswamy KK,Chou KC,Vivekanandan S,Kolatkar P

doi

10.2174/092986612798472875

subject

Has Abstract

pub_date

2012-01-01 00:00:00

pages

50-6

issue

1

eissn

0929-8665

issn

1875-5305

pii

BSP/ PPL/ E pub/0385

journal_volume

19

pub_type

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