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Literature DB >> 10449371

Energy functions for protein design.

Abstract

Recent successes in protein design have illustrated the promise of computational approaches. These methods rely on energy expressions to evaluate the quality of different amino acid sequences for target protein structures. The force fields optimized for design differ from those typically used in molecular mechanics and molecular dynamics calculations.

Mesh：

Year: 1999 PMID： 10449371 DOI： 10.1016/s0959-440x(99)80072-4

Source DB: PubMed Journal: Curr Opin Struct Biol ISSN： 0959-440X Impact factor: 6.809

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Cited

64 in total

1. Prediction of amino acid sequence from structure.

Authors: K Raha; A M Wollacott; M J Italia; J R Desjarlais
Journal: Protein Sci Date: 2000-06 Impact factor: 6.725

2. Implicit solvation in the self-consistent mean field theory method: sidechain modelling and prediction of folding free energies of protein mutants.

Authors: J Mendes; A M Baptista; M A Carrondo; C M Soares
Journal: J Comput Aided Mol Des Date: 2001-08 Impact factor: 3.686

3. Enzyme-like proteins by computational design.

Authors: D N Bolon; S L Mayo
Journal: Proc Natl Acad Sci U S A Date: 2001-11-27 Impact factor: 11.205

4. Native protein sequences are close to optimal for their structures.

Authors: B Kuhlman; D Baker
Journal: Proc Natl Acad Sci U S A Date: 2000-09-12 Impact factor: 11.205

5. On hydrophobicity and conformational specificity in proteins.

Authors: Erik Sandelin
Journal: Biophys J Date: 2004-01 Impact factor: 4.033

6. Crystal structures and increased stabilization of the protein G variants with switched folding pathways NuG1 and NuG2.

Authors: Sehat Nauli; Brian Kuhlman; Isolde Le Trong; Ronald E Stenkamp; David Teller; David Baker
Journal: Protein Sci Date: 2002-12 Impact factor: 6.725

Energy functions for protein design.

1. Prediction of amino acid sequence from structure.

2. Implicit solvation in the self-consistent mean field theory method: sidechain modelling and prediction of folding free energies of protein mutants.

3. Enzyme-like proteins by computational design.

4. Native protein sequences are close to optimal for their structures.

5. On hydrophobicity and conformational specificity in proteins.

6. Crystal structures and increased stabilization of the protein G variants with switched folding pathways NuG1 and NuG2.

7. Combining computational and experimental screening for rapid optimization of protein properties.

8. Interatomic potentials and solvation parameters from protein engineering data for buried residues.

9. Solvent accessible surface area approximations for rapid and accurate protein structure prediction.

10. Exploring the origins of binding specificity through the computational redesign of calmodulin.