Tools for comparative protein structure modeling and analysis

@article{Eswar2003ToolsFC,
  title={Tools for comparative protein structure modeling and analysis},
  author={Narayanan Eswar and Bino John and Nebojsa Mirkovic and Andr{\'a}s Fiser and Valentin A. Ilyin and Ursula Pieper and Ashley C. Stuart and Marc A. Mart{\'i}-Renom and Mallur S. Madhusudhan and Bozidar Yerkovich and Andrej Sali},
  journal={Nucleic acids research},
  year={2003},
  volume={31 13},
  pages={
          3375-80
        }
}
The following resources for comparative protein structure modeling and analysis are described (http://salilab.org): MODELLER, a program for comparative modeling by satisfaction of spatial restraints; MODWEB, a web server for automated comparative modeling that relies on PSI-BLAST, IMPALA and MODELLER; MODLOOP, a web server for automated loop modeling that relies on MODELLER; MOULDER, a CPU intensive protocol of MODWEB for building comparative models based on distant known structures; MODBASE, a… 
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MODBASE, a database of annotated comparative protein structure models, and associated resources
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The database currently contains 3D models for substantial portions of approximately 17 000 proteins from 10 complete genomes, including those of Caenorhabditis elegans, Saccharomyces cerevisiae and Escherichia coli, as well as all the available sequences from Arabidopsis thaliana and Homo sapiens.
Comparative Protein Structure Modeling Using MODELLER
TLDR
This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications.
Comparative Protein Structure Modeling Using MODELLER
TLDR
This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications.
Parmodel: a web server for automated comparative modeling of proteins.
MODBASE: a database of annotated comparative protein structure models and associated resources
MODBASE () is a database of annotated comparative protein structure models for all available protein sequences that can be matched to at least one known protein structure. The models are calculated…
modbase, a database of annotated comparative protein structure models and associated resources
TLDR
MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models that calculates comparative models on demand, through an interface to the MODWEB modeling server.
ModBase, a database of annotated comparative protein structure models and associated resources
TLDR
A PSI:Biology initiative to maximize the structural coverage of the human alpha-helical transmembrane proteome and a determination of structural determinants of human immunodeficiency virus-1 protease specificity are highlighted.
Comparative Protein Structure Modeling Using Modeller
TLDR
This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications.
Comparative Protein Structure Modeling Using MODELLER
TLDR
This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications.
Comparative Protein Structure Modeling Using MODELLER
TLDR
This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications.
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References

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MODBASE, a database of annotated comparative protein structure models
TLDR
MODBASE is a relational database of annotated comparative protein structure models for all available protein sequences matched to at least one known protein structure by MODPIPE, an automated modeling pipeline that relies on PSI-BLAST, IMPALA and MODELLER.
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TLDR
There is a need to develop an automated, rapid, robust, sensitive, and accurate comparative modeling pipeline applicable to whole genomes and to encourage new kinds of applications for the many resulting models, based on their large number and completeness at the level of the family, organism, or functional network.
Derivation of rules for comparative protein modeling from a database of protein structure alignments
TLDR
A database of protein structure alignments as well as methods and tools that use this database to improve comparative protein modeling are described, including the derivation of the probability density function for comparative modeling of the cis/trans isomerism of the proline residues.
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EVA (http://cubic.columbia.edu/eva/) is a web server for evaluation of the accuracy of automated protein structure prediction methods, and provides useful information to developers as well as users of prediction methods.
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This Viewpoint begins by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes.
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TLDR
EVA is described, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion, that evaluates the performance of a variety of prediction methods available through the internet.
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TLDR
A comparative protein modelling method designed to find the most probable structure for a sequence given its alignment with related structures, which is automated and illustrated by the modelling of trypsin from two other serine proteinases.
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The DBAli database includes approximately 35000 alignments of pairs of protein structures from SCOP and CE, which allows construction of subsets of alignments suitable for a number of applications, such as benchmarking of sequence-sequence and sequence-structure alignment methods under a variety of conditions.
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TLDR
The fold assignment, comparative protein structure modeling, and model evaluation were automated completely and resulted in all-atom 3D models for substantial segments of 1,071 of the yeast proteins, only 40 of which have had their 3D structure determined experimentally.
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