Literature DB >> 35475517

Using steered molecular dynamic tension for assessing quality of computational protein structure models.

Lyman Monroe1, Daisuke Kihara1,2,3.   

Abstract

The native structures of proteins, except for notable exceptions of intrinsically disordered proteins, in general take their most stable conformation in the physiological condition to maintain their structural framework so that their biological function can be properly carried out. Experimentally, the stability of a protein can be measured by several means, among which the pulling experiment using the atomic force microscope (AFM) stands as a unique method. AFM directly measures the resistance from unfolding, which can be quantified from the observed force-extension profile. It has been shown that key features observed in an AFM pulling experiment can be well reproduced by computational molecular dynamics simulations. Here, we applied computational pulling for estimating the accuracy of computational protein structure models under the hypothesis that the structural stability would positively correlated with the accuracy, i.e. the closeness to the native, of a model. We used in total 4929 structure models for 24 target proteins from the Critical Assessment of Techniques of Structure Prediction (CASP) and investigated if the magnitude of the break force, that is, the force required to rearrange the model's structure, from the force profile was sufficient information for selecting near-native models. We found that near-native models can be successfully selected by examining their break forces suggesting that high break force indeed indicates high stability of models. On the other hand, there were also near-native models that had relatively low peak forces. The mechanisms of the stability exhibited by the break forces were explored and discussed.
© 2022 Wiley Periodicals LLC.

Entities:  

Keywords:  assessment; model quality; protein bioinformatics; protein structure prediction; steered molecular dynamics

Mesh:

Substances:

Year:  2022        PMID: 35475517      PMCID: PMC9133218          DOI: 10.1002/jcc.26876

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.672


  43 in total

Review 1.  Atomic force microscopy: mechanical unfolding of proteins.

Authors:  Ross Rounsevell; Julia R Forman; Jane Clarke
Journal:  Methods       Date:  2004-09       Impact factor: 3.608

2.  Force-dependent switch in protein unfolding pathways and transition-state movements.

Authors:  Pavel I Zhuravlev; Michael Hinczewski; Shaon Chakrabarti; Susan Marqusee; D Thirumalai
Journal:  Proc Natl Acad Sci U S A       Date:  2016-01-27       Impact factor: 11.205

3.  Identification of correct regions in protein models using structural, alignment, and consensus information.

Authors:  Björn Wallner; Arne Elofsson
Journal:  Protein Sci       Date:  2006-03-07       Impact factor: 6.725

4.  On the remarkable mechanostability of scaffoldins and the mechanical clamp motif.

Authors:  Alejandro Valbuena; Javier Oroz; Rubén Hervás; Andrés Manuel Vera; David Rodríguez; Margarita Menéndez; Joanna I Sulkowska; Marek Cieplak; Mariano Carrión-Vázquez
Journal:  Proc Natl Acad Sci U S A       Date:  2009-07-31       Impact factor: 11.205

5.  CASP 11 target classification.

Authors:  Lisa N Kinch; Wenlin Li; R Dustin Schaeffer; Roland L Dunbrack; Bohdan Monastyrskyy; Andriy Kryshtafovych; Nick V Grishin
Journal:  Proteins       Date:  2016-01-27

6.  Definition and classification of evaluation units for tertiary structure prediction in CASP12 facilitated through semi-automated metrics.

Authors:  Luciano A Abriata; Lisa N Kinch; Giorgio E Tamò; Bohdan Monastyrskyy; Andriy Kryshtafovych; Matteo Dal Peraro
Journal:  Proteins       Date:  2017-10-24

Review 7.  Probing membrane proteins using atomic force microscopy.

Authors:  Guangyong Li; Ning Xi; Donna H Wang
Journal:  J Cell Biochem       Date:  2006-04-15       Impact factor: 4.429

8.  Critical assessment of methods of protein structure prediction (CASP)--round x.

Authors:  John Moult; Krzysztof Fidelis; Andriy Kryshtafovych; Torsten Schwede; Anna Tramontano
Journal:  Proteins       Date:  2013-12-17

9.  Unfolding of titin immunoglobulin domains by steered molecular dynamics simulation.

Authors:  H Lu; B Isralewitz; A Krammer; V Vogel; K Schulten
Journal:  Biophys J       Date:  1998-08       Impact factor: 4.033

10.  SVMQA: support-vector-machine-based protein single-model quality assessment.

Authors:  Balachandran Manavalan; Jooyoung Lee
Journal:  Bioinformatics       Date:  2017-08-15       Impact factor: 6.937

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