Literature DB >> 19833875

Computational design of ligand binding is not a solved problem.

Bettina Schreier1, Christian Stumpp, Silke Wiesner, Birte Höcker.   

Abstract

Computational design has been very successful in recent years: multiple novel ligand binding proteins as well as enzymes have been reported. We wanted to know in molecular detail how precise the predictions of the interactions of protein and ligands are. Therefore, we performed a structural analysis of a number of published receptors designed onto the periplasmic binding protein scaffold that were reported to bind to the new ligands with nano- to micromolar affinities. It turned out that most of these designed proteins are not suitable for structural studies due to instability and aggregation. However, we were able to solve the crystal structure of an arabinose binding protein designed to bind serotonin to 2.2 A resolution. While crystallized in the presence of an excess of serotonin, the protein is in an open conformation with no serotonin bound, although the side-chain conformations in the empty binding pocket are very similar to the conformations predicted. During subsequent characterization using isothermal titration calorimetry, CD, and NMR spectroscopy, no indication of binding could be detected for any of the tested designed receptors, whereas wild-type proteins bound their ligands as expected. We conclude that although the computational prediction of side-chain conformations appears to be working, it does not necessarily confer binding as expected. Hence, the computational design of ligand binding is not a solved problem and needs to be revisited.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19833875      PMCID: PMC2773959          DOI: 10.1073/pnas.0907950106

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  30 in total

1.  Conversion of a maltose receptor into a zinc biosensor by computational design.

Authors:  J S Marvin; H W Hellinga
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-24       Impact factor: 11.205

2.  Computational design of receptor and sensor proteins with novel functions.

Authors:  Loren L Looger; Mary A Dwyer; James J Smith; Homme W Hellinga
Journal:  Nature       Date:  2003-05-08       Impact factor: 49.962

3.  Refinement of macromolecular structures by the maximum-likelihood method.

Authors:  G N Murshudov; A A Vagin; E J Dodson
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  1997-05-01

4.  Using NMRView to visualize and analyze the NMR spectra of macromolecules.

Authors:  Bruce A Johnson
Journal:  Methods Mol Biol       Date:  2004

5.  Analysis of ligand binding to a ribose biosensor using site-directed mutagenesis and fluorescence spectroscopy.

Authors:  Natalie C Vercillo; Kaitlin J Herald; John M Fox; Bryan S Der; Jonathan D Dattelbaum
Journal:  Protein Sci       Date:  2007-01-22       Impact factor: 6.725

6.  Kemp elimination catalysts by computational enzyme design.

Authors:  Daniela Röthlisberger; Olga Khersonsky; Andrew M Wollacott; Lin Jiang; Jason DeChancie; Jamie Betker; Jasmine L Gallaher; Eric A Althoff; Alexandre Zanghellini; Orly Dym; Shira Albeck; Kendall N Houk; Dan S Tawfik; David Baker
Journal:  Nature       Date:  2008-03-19       Impact factor: 49.962

7.  Multiple open forms of ribose-binding protein trace the path of its conformational change.

Authors:  A J Björkman; S L Mowbray
Journal:  J Mol Biol       Date:  1998-06-12       Impact factor: 5.469

8.  Systematic analysis of domain motions in proteins from conformational change: new results on citrate synthase and T4 lysozyme.

Authors:  S Hayward; H J Berendsen
Journal:  Proteins       Date:  1998-02-01

9.  NMRPipe: a multidimensional spectral processing system based on UNIX pipes.

Authors:  F Delaglio; S Grzesiek; G W Vuister; G Zhu; J Pfeifer; A Bax
Journal:  J Biomol NMR       Date:  1995-11       Impact factor: 2.835

10.  MolProbity: all-atom contacts and structure validation for proteins and nucleic acids.

Authors:  Ian W Davis; Andrew Leaver-Fay; Vincent B Chen; Jeremy N Block; Gary J Kapral; Xueyi Wang; Laura W Murray; W Bryan Arendall; Jack Snoeyink; Jane S Richardson; David C Richardson
Journal:  Nucleic Acids Res       Date:  2007-04-22       Impact factor: 16.971

View more
  35 in total

1.  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

Review 2.  Converting a protein into a switch for biosensing and functional regulation.

Authors:  Margaret M Stratton; Stewart N Loh
Journal:  Protein Sci       Date:  2011-01       Impact factor: 6.725

3.  Computational biology: A recipe for ligand-binding proteins.

Authors:  Giovanna Ghirlanda
Journal:  Nature       Date:  2013-09-04       Impact factor: 49.962

4.  Key protein-design papers challenged.

Authors:  Erika Check Hayden
Journal:  Nature       Date:  2009-10-15       Impact factor: 49.962

5.  Computational design of an endo-1,4-beta-xylanase ligand binding site.

Authors:  Andrew Morin; Kristian W Kaufmann; Carie Fortenberry; Joel M Harp; Laura S Mizoue; Jens Meiler
Journal:  Protein Eng Des Sel       Date:  2011-02-24       Impact factor: 1.650

Review 6.  Structure-switching biosensors: inspired by Nature.

Authors:  Alexis Vallée-Bélisle; Kevin W Plaxco
Journal:  Curr Opin Struct Biol       Date:  2010-06-02       Impact factor: 6.809

7.  Structural biology: A toolbox for protein design.

Authors:  Birte Höcker
Journal:  Nature       Date:  2012-11-08       Impact factor: 49.962

8.  Rational design of a ligand-controlled protein conformational switch.

Authors:  Onur Dagliyan; David Shirvanyants; Andrei V Karginov; Feng Ding; Lanette Fee; Srinivas N Chandrasekaran; Christina M Freisinger; Gromoslaw A Smolen; Anna Huttenlocher; Klaus M Hahn; Nikolay V Dokholyan
Journal:  Proc Natl Acad Sci U S A       Date:  2013-04-08       Impact factor: 11.205

Review 9.  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

10.  Thermodynamic additivity of sequence variations: an algorithm for creating high affinity peptides without large libraries or structural information.

Authors:  Matthew P Greving; Paul E Belcher; Chris W Diehnelt; Maria J Gonzalez-Moa; Jack Emery; Jinglin Fu; Stephen Albert Johnston; Neal W Woodbury
Journal:  PLoS One       Date:  2010-11-11       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.