Literature DB >> 12498804

In vitro and in silico design of alpha1-antitrypsin mutants with different conformational stabilities.

Dimitri Gilis1, Holly R McLennan, Yves Dehouck, Lisa D Cabrita, Marianne Rooman, Stephen P Bottomley.   

Abstract

Alpha(1)-antitrypsin, a protein belonging to the serine protease inhibitor (serpin) superfamily, is characterized by the ability to undergo dramatic conformational changes leading to inactive polymers. Serpin polymerization, which causes a range of diseases such as emphysema, thrombosis and dementia, occurs through a process in which the reactive center loop residues of one serpin molecule insert into the A beta-sheet of another. PoPMuSiC, a program that uses database-derived mean force potentials to predict changes in folding free energy resulting from single-site mutations, was used to modulate rationally the polymerization propensity of alpha(1)-antitrypsin. This was accomplished by generating mutants with a stabilized active form and destabilized polymerized form, or the converse. Of these mutants, five were expressed and characterized experimentally. In agreement with the predictions, three of them, K331F, K331I and K331V, were shown to stabilize the active form and decrease the polymerization rate, and one of them, S330R, to destabilize the active form and to increase polymerization. Only one mutant (K331T) did not display the expected behavior. Thus, strikingly, the adjacent positions 330 and 331, which are located at the beginning of the beta-strand next to the additionally inserted beta-strand in the polymerized form, have opposite effects on the conformational change. These residues therefore appear to play a key role in inducing or preventing such conformational change. Copyright 2003 Elsevier Science Ltd.

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Year:  2003        PMID: 12498804     DOI: 10.1016/s0022-2836(02)01221-4

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


  9 in total

1.  Enhancing the stability and solubility of TEV protease using in silico design.

Authors:  Lisa D Cabrita; Dimitri Gilis; Amy L Robertson; Yves Dehouck; Marianne Rooman; Stephen P Bottomley
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2.  Computational tools help improve protein stability but with a solubility tradeoff.

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4.  Flanking domain stability modulates the aggregation kinetics of a polyglutamine disease protein.

Authors:  Helen M Saunders; Dimitri Gilis; Marianne Rooman; Yves Dehouck; Amy L Robertson; Stephen P Bottomley
Journal:  Protein Sci       Date:  2011-08-18       Impact factor: 6.725

5.  PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality.

Authors:  Yves Dehouck; Jean Marc Kwasigroch; Dimitri Gilis; Marianne Rooman
Journal:  BMC Bioinformatics       Date:  2011-05-13       Impact factor: 3.307

6.  An antibody that prevents serpin polymerisation acts by inducing a novel allosteric behaviour.

Authors:  Neda Motamedi-Shad; Alistair M Jagger; Maximilian Liedtke; Sarah V Faull; Arjun Scott Nanda; Enrico Salvadori; Joshua L Wort; Christopher W M Kay; Narinder Heyer-Chauhan; Elena Miranda; Juan Perez; Adriana Ordóñez; Imran Haq; James A Irving; David A Lomas
Journal:  Biochem J       Date:  2016-07-12       Impact factor: 3.857

7.  Nascent chains can form co-translational folding intermediates that promote post-translational folding outcomes in a disease-causing protein.

Authors:  Elena Plessa; Lien P Chu; Sammy H S Chan; Oliver L Thomas; Anaïs M E Cassaignau; Christopher A Waudby; John Christodoulou; Lisa D Cabrita
Journal:  Nat Commun       Date:  2021-11-08       Impact factor: 14.919

8.  Altered native stability is the dominant basis for susceptibility of α1-antitrypsin mutants to polymerization.

Authors:  James A Irving; Imran Haq; Jennifer A Dickens; Sarah V Faull; David A Lomas
Journal:  Biochem J       Date:  2014-05-15       Impact factor: 3.857

Review 9.  Computational Approaches to Prioritize Cancer Driver Missense Mutations.

Authors:  Feiyang Zhao; Lei Zheng; Alexander Goncearenco; Anna R Panchenko; Minghui Li
Journal:  Int J Mol Sci       Date:  2018-07-20       Impact factor: 5.923

  9 in total

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