Sequence based residue depth prediction using evolutionary information and predicted secondary structure |
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| Authors: | Hua Zhang Tuo Zhang Ke Chen Shiyi Shen Jishou Ruan Lukasz Kurgan |
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| Institution: | (1) College of Mathematical Science and LPMC, Nankai University, Tianjin, PR China;(2) Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada;(3) Chern Institute of Mathematics, Tianjin, PR China |
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| Abstract: | Background Residue depth allows determining how deeply a given residue is buried, in contrast to the solvent accessibility that differentiates
between buried and solvent-exposed residues. When compared with the solvent accessibility, the depth allows studying deep-level
structures and functional sites, and formation of the protein folding nucleus. Accurate prediction of residue depth would
provide valuable information for fold recognition, prediction of functional sites, and protein design. |
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