RENNSH: A Novel Alpha-helix Identification Approach for Intermediate Resolution Electron Density Maps

03.03.2011

Ma L, Reisert M, Burkhardt H.

IEEE/ACM Trans Comput Biol Bioinform. 2011 Mar 3. [Epub ahead of print]

IEEE/ACM Trans Comput Biol Bioinform      online article

A!ccurate identification of protein secondary structures is beneficial to understand three-dimensional structures of biological macromolecules. In this paper, a novel refined classification framework is proposed, which treats alpha-helix identification as a machine learning problem by representing each voxel in the density map with its Spherical Harmonic Descriptors (SHD). An energy function is defined to provide statistical analysis of its identification performance, which can be applied to all the alpha-helix identification approaches. Comparing with other existing alpha-helix identification methods for intermediate resolution electron density maps, the experimental results demonstrate that our approach gives the best identification accuracy and is more robust to the noise.