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Literature DB >> 10933507

Decoys 'R' Us: a database of incorrect conformations to improve protein structure prediction.

Abstract

The development of an energy or scoring function for protein structure prediction is greatly enhanced by testing the function on a set of computer-generated conformations (decoys) to determine whether it can readily distinguish native-like conformations from nonnative ones. We have created "Decoys 'R' Us," a database containing many such sets of conformations, to provide a resource that allows scoring functions to be improved.

Mesh：

Substances：
Proteins

Year: 2000 PMID： 10933507 PMCID： PMC2144680 DOI： 10.1110/ps.9.7.1399

Source DB: PubMed Journal: Protein Sci ISSN： 0961-8368 Impact factor: 6.725

12 in total

1. Ab initio protein structure prediction using a combined hierarchical approach.

Authors: R Samudrala; Y Xia; E Huang; M Levitt
Journal: Proteins Date: 1999

2. Are predicted structures good enough to preserve functional sites?

Authors: L Wei; E S Huang; R B Altman
Journal: Structure Date: 1999-06-15 Impact factor: 5.006

3. Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins.

Authors: K T Simons; I Ruczinski; C Kooperberg; B A Fox; C Bystroff; D Baker
Journal: Proteins Date: 1999-01-01

4. Discrimination of the native from misfolded protein models with an energy function including implicit solvation.

Authors: T Lazaridis; M Karplus
Journal: J Mol Biol Date: 1999-05-07 Impact factor: 5.469

5. Evaluation of protein models by atomic solvation preference.

Authors: L Holm; C Sander
Journal: J Mol Biol Date: 1992-05-05 Impact factor: 5.469

6. Using a hydrophobic contact potential to evaluate native and near-native folds generated by molecular dynamics simulations.

Authors: E S Huang; S Subbiah; J Tsai; M Levitt
Journal: J Mol Biol Date: 1996-04-05 Impact factor: 5.469

Decoys 'R' Us: a database of incorrect conformations to improve protein structure prediction.

1. Ab initio protein structure prediction using a combined hierarchical approach.

2. Are predicted structures good enough to preserve functional sites?

3. Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins.

4. Discrimination of the native from misfolded protein models with an energy function including implicit solvation.

5. Evaluation of protein models by atomic solvation preference.

6. Using a hydrophobic contact potential to evaluate native and near-native folds generated by molecular dynamics simulations.

7. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction.

8. Energy functions that discriminate X-ray and near native folds from well-constructed decoys.

9. Discriminating compact nonnative structures from the native structure of globular proteins.

10. An analysis of incorrectly folded protein models. Implications for structure predictions.

1. Can correct protein models be identified?

2. Discrete restraint-based protein modeling and the Calpha-trace problem.

3. Design of an optimal Chebyshev-expanded discrimination function for globular proteins.

4. Orientational potentials extracted from protein structures improve native fold recognition.

5. Protein fragment reconstruction using various modeling techniques.

6. Self-complementarity within proteins: bridging the gap between binding and folding.

7. 3DRobot: automated generation of diverse and well-packed protein structure decoys.

Review 8. Selection on protein structure, interaction, and sequence.

9. Decoys for docking.

10. A coarse-grained potential for fold recognition and molecular dynamics simulations of proteins.