Literature DB >> 19408277

The subspace iteration method in protein normal mode analysis.

Reza Sharifi Sedeh1, Mark Bathe, Klaus-Jürgen Bathe.   

Abstract

Normal mode analysis plays an important role in relating the conformational dynamics of proteins to their biological function. The subspace iteration method is a numerical procedure for normal mode analysis that has enjoyed widespread success in the structural mechanics community due to its numerical stability and computational efficiency in calculating the lowest normal modes of large systems. Here, we apply the subspace iteration method to proteins to demonstrate its advantageous properties in this area of computational protein science. An effective algorithm for choosing the number of iteration vectors in the method is established, offering a considerable improvement over the original implementation. In the present application, computational time scales linearly with the number of normal modes computed. Additionally, the method lends itself naturally to normal mode analyses of multiple neighboring macromolecular conformations, as demonstrated in a conformational change pathway analysis of adenylate kinase. These properties, together with its computational robustness and intrinsic scalability to multiple processors, render the subspace iteration method an effective and reliable computational approach to protein normal mode analysis. Copyright 2009 Wiley Periodicals, Inc.

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Year:  2010        PMID: 19408277     DOI: 10.1002/jcc.21250

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  2 in total

1.  A critical assessment of finite element modeling approach for protein dynamics.

Authors:  Giseok Yun; Jaehoon Kim; Do-Nyun Kim
Journal:  J Comput Aided Mol Des       Date:  2017-06-01       Impact factor: 3.686

2.  Predicting breast cancer using an expression values weighted clinical classifier.

Authors:  Minta Thomas; Kris De Brabanter; Johan A K Suykens; Bart De Moor
Journal:  BMC Bioinformatics       Date:  2014-12-31       Impact factor: 3.169

  2 in total

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