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Download e-book for iPad: Computational Methods for Protein Structure Prediction and by Ying Xu, Dong Xu, Jie Liang

4 April 2018 adminBioinformatics

By Ying Xu, Dong Xu, Jie Liang

ISBN-10: 0387333215

ISBN-13: 9780387333212

Quantity of this two-volume series offers a finished assessment of protein constitution prediction tools and comprises protein threading, De novo tools, functions to membrane proteins and protein complexes, structure-based drug layout, in addition to constitution prediction as a platforms challenge. a chain of appendices evaluate the organic and chemical fundamentals with regards to protein constitution, desktop technology for structural informatics, and prerequisite arithmetic and facts.

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Extra info for Computational Methods for Protein Structure Prediction and Modeling: Volume 2: Structure Prediction (Biological and Medical Physics, Biomedical Engineering)

Example text

2004) performed structure prediction for all of the ORFs of Pyrococcusfuriosus, which is found in the marine sand surrounding sulfurous volcanoes and can grow at temperatures above 100a e. The microbe utilizes peptides, proteins, and some carbohydrates as carbon sources. Its entire genome is about 2 Mb in length with 2195 annotated ORFs. Out of a total of 2195 ORFs, 540 are predicted to be membrane proteins, and 753 proteins can be predicted with structures in high confidence, among which 190 ORFs cannot be detected using PSI-BLAST.

To do this, one needs to put all the atoms, backbone and side chains, into a structural model. One can use alignments with the selected templates in fold recognition to produce a 3D atomic model through homology modeling tools, such as MODELLER (Sali and Blundell, 1990), which runs a protocol ofenergy minimization and molecular dynamics simulation to refine a structural model. , 1993) to evaluate the packing and backbone conformations, the inside/outside occupancies ofhydrophobic and hydrophilic residues, and stereochemical quality of a predicted structure.

These partial structural data might be in the form of (a) residue-residue distances such as disulfides between specific cysteines, (b) specific residues involved in particular active sites, binding sites, or other functionally important sites, (c) specific residues known to be on the surface ofa protein structure, or any other information providing geometric information about specific residues in a protein structure. In addition to such information about specific residues, there are experimental techniques that can be used to generate geometric information in a systematic manner.

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Computational Methods for Protein Structure Prediction and Modeling: Volume 2: Structure Prediction (Biological and Medical Physics, Biomedical Engineering) by Ying Xu, Dong Xu, Jie Liang


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