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- Shu, Nanjiang, 1981-, et al.
(författare)
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Describing and Comparing Protein Structures Using Shape Strings
- 2008
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Ingår i: Current protein and peptide science. - : Bentham Science Publishers. - 1389-2037 .- 1875-5550. ; 9:4, s. 310-324
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Tidskriftsartikel (refereegranskat)abstract
- Different methods for describing and comparing the structures of the tens of thousands of proteins that have been determined by X-ray crystallography are reviewed. Such comparisons are important for understanding the structures and functions of proteins and facilitating structure prediction, as well as assessing structure prediction methods. We summarize methods in this field emphasizing ways of representing protein structures as one-dimensional geometrical strings. Such strings are based on the shape symbols of clustered regions of φ/Ψ dihedral angle pairs of the polypeptide backbones as described by the Ramachandran plot. These one-dimensional expressions are as compact as secondary structure description but contain more information in loop regions. They can be used for fast searching for similar structures in databases and for comparing similarities between proteins and between the predicted and native structures.
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| 2. |
- Shu, Nanjiang, 1981-
(författare)
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Prediction of zinc-binding sites in proteins and efficient protein structure description and comparison
- 2008
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A large number of proteins require certain metals to stabilize their structures or to function properly. About one third of all proteins in the Protein Data Bank (PDB) contain metals and it is estimated that approximately the same proportion of all proteins are metalloproteins. Zinc, the second most abundant transition metal found in eukaryotic organisms, plays key roles, mainly structural and catalytic, in many biological functions. Predicting whether a protein binds zinc and even the accurate location of binding sites is important when investigating the function of an experimentally uncharacterized protein. Describing and comparing protein structures with both efficiency and accuracy are essential for systematic annotation of functional properties of proteins, be it on an individual or on a genome scale. Dozens of structure comparison methods have been developed in the past decades. In recent years, several research groups have endeavoured in developing methods for fast comparison of protein structures by representing the three-dimensional (3D) protein structures as one-dimensional (1D) geometrical strings based on the shape symbols of clustered regions of φ/ψ torsion angle pairs of the polypeptide backbones. These 1D geometrical strings, shape strings, are as compact as 1D secondary structures but carry more elaborate structural information in loop regions and thus are more suitable for fast structure database searching, classification of loop regions and evaluation of model structures. In this thesis, a new method for predicting zinc-binding sites in proteins from amino acid sequences is described. This method predicts zinc-binding Cys, His, Asp and Glu (the four most common zinc-binding residues) with 75% precision (86% for Cys and His only) at 50% recall according to a solid 5-fold cross-validation on a non-redundant set of the PDB chains containing 2727 unique chains, of which 235 bind to zinc. This method predicts zinc-binding Cys and His with about 10% higher precision at different recall levels compared to a previously published method. In addition, different methods for describing and comparing protein structures are reviewed. Some recently developed methods based on 1D geometrical representation of backbone structures are emphasized and analyzed in details.
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| 3. |
- Shu, Nanjiang, 1981-, et al.
(författare)
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Prediction of zinc-binding sites in proteins from sequence
- 2008
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 24:6, s. 775-782
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Motivated by the abundance, importance and unique functionality of zinc, both biologically and physiologically, we have developed an improved method for the prediction of zinc-binding sites in proteins from their amino acid sequences. RESULTS: By combining support vector machine (SVM) and homology-based predictions, our method predicts zinc-binding Cys, His, Asp and Glu with 75% precision (86% for Cys and His only) at 50% recall according to a 5-fold cross-validation on a non-redundant set of protein chains from the Protein Data Bank (PDB) (2727 chains, 235 of which bind zinc). Consequently, our method predicts zinc-binding Cys and His with 10% higher precision at different recall levels compared to a recently published method when tested on the same dataset. AVAILABILITY: The program is available for download at www.fos.su.se/~nanjiang/zincpred/download/
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| 4. |
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| 5. |
- Shu, Nanjiang, 1981-
(författare)
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Protein structure prediction : Zinc-binding sites, one-dimensional structure and remote homology
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Predicting the three-dimensional (3D) structure of proteins is a central problem in biology. These computationally predicted 3D protein structures have been successfully applied in many fields of biomedicine, e.g. family assignments and drug discovery. The accurate detection of remotely homologous templates is critical for the successful prediction of the 3D structure of proteins. Also, the prediction of one-dimensional (1D) protein structures such as secondary structures and shape strings are useful for predicting the 3D structure of proteins and important for understanding the sequence-structure relationship. In addition, the prediction of the functional sites of proteins, such as metal-binding sites, can not only reveal the important function of proteins (even in the absence of the 3D structure) but also facilitate the prediction of the 3D structure. Here, three novel methods in the field of protein structure prediction are presented: PREDZINC, a method for predicting zinc-binding sites in proteins; Frag1D, a method for predicting the 1D structure of proteins; and FragMatch, a method for detecting remotely homologous proteins. These methods compete satisfactorily with the best methods previously published and contribute to the task of protein structure prediction.
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