Literature DB >> 12948494

A large scale test of computational protein design: folding and stability of nine completely redesigned globular proteins.

Gautam Dantas1, Brian Kuhlman, David Callender, Michelle Wong, David Baker.   

Abstract

A previously developed computer program for protein design, RosettaDesign, was used to predict low free energy sequences for nine naturally occurring protein backbones. RosettaDesign had no knowledge of the naturally occurring sequences and on average 65% of the residues in the designed sequences differ from wild-type. Synthetic genes for ten completely redesigned proteins were generated, and the proteins were expressed, purified, and then characterized using circular dichroism, chemical and temperature denaturation and NMR experiments. Although high-resolution structures have not yet been determined, eight of these proteins appear to be folded and their circular dichroism spectra are similar to those of their wild-type counterparts. Six of the proteins have stabilities equal to or up to 7kcal/mol greater than their wild-type counterparts, and four of the proteins have NMR spectra consistent with a well-packed, rigid structure. These encouraging results indicate that the computational protein design methods can, with significant reliability, identify amino acid sequences compatible with a target protein backbone.

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Year:  2003        PMID: 12948494     DOI: 10.1016/s0022-2836(03)00888-x

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  98 in total

1.  In silico protein design by combinatorial assembly of protein building blocks.

Authors:  Hui-Hsu Gavin Tsai; Chung-Jung Tsai; Buyong Ma; Ruth Nussinov
Journal:  Protein Sci       Date:  2004-10       Impact factor: 6.725

2.  Energy functions for protein design I: efficient and accurate continuum electrostatics and solvation.

Authors:  Navin Pokala; Tracy M Handel
Journal:  Protein Sci       Date:  2004-03-09       Impact factor: 6.725

3.  A new hydrogen-bonding potential for the design of protein-RNA interactions predicts specific contacts and discriminates decoys.

Authors:  Yu Chen; Tanja Kortemme; Tim Robertson; David Baker; Gabriele Varani
Journal:  Nucleic Acids Res       Date:  2004-09-30       Impact factor: 16.971

4.  Automated selection of stabilizing mutations in designed and natural proteins.

Authors:  Benjamin Borgo; James J Havranek
Journal:  Proc Natl Acad Sci U S A       Date:  2012-01-17       Impact factor: 11.205

5.  Improving computational protein design by using structure-derived sequence profile.

Authors:  Liang Dai; Yuedong Yang; Hyung Rae Kim; Yaoqi Zhou
Journal:  Proteins       Date:  2010-08-01

6.  Discovery of entry inhibitors for HIV-1 via a new de novo protein design framework.

Authors:  M L Bellows; M S Taylor; P A Cole; L Shen; R F Siliciano; H K Fung; C A Floudas
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

7.  Protein backbone ensemble generation explores the local structural space of unseen natural homologs.

Authors:  Christian D Schenkelberg; Christopher Bystroff
Journal:  Bioinformatics       Date:  2016-01-18       Impact factor: 6.937

8.  Massive sequence perturbation of a small protein.

Authors:  F-X Campbell-Valois; K Tarassov; S W Michnick
Journal:  Proc Natl Acad Sci U S A       Date:  2005-10-07       Impact factor: 11.205

9.  1H, 13C and 15N resonance assignments of URNdesign, a computationally redesigned RRM protein.

Authors:  Neil Dobson; Gautam Dantas; Gabriele Varani
Journal:  J Biomol NMR       Date:  2005-10       Impact factor: 2.835

Review 10.  Energy functions in de novo protein design: current challenges and future prospects.

Authors:  Zhixiu Li; Yuedong Yang; Jian Zhan; Liang Dai; Yaoqi Zhou
Journal:  Annu Rev Biophys       Date:  2013-02-28       Impact factor: 12.981

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