Literature DB >> 21136323

FINGAR: A new genetic algorithm-based method for fitting NMR data.

D A Pearlman1.   

Abstract

A new NMR refinement method, FINGAR (FIt NMR using a Genetic AlgoRithm), has been developed, which allows one to determine a weighted set of structures that best fits measured NMR-derived data. This method shows appreciable advantages over commonly used refinement methods. FINGAR generates an ensemble of conformations whose average reproduces the experimental NMR-derived restraints. In addition, a statistical importance weight is assigned to each of the conformations in the ensemble. As a result, one is not limited to simply presenting an envelope of sampled conformers. Instead, one can subsequently focus on a select few conformers of high weight. This is critical, because many structural analyses depend on using discrete conformations, not simply averages or ensembles. The genetic algorithm used by FINGAR allows one to simultaneously and reliably fit against many restraints, and to generate solutions which include as many conformations with non-zero weights as are necessary to generate the best fit. An added benefit of FINGAR is that because the time-consuming step in this method needs only to be performed once, in the beginning of the first run, numerous FINGAR simulations can be performed rapidly.

Entities:  

Year:  1996        PMID: 21136323     DOI: 10.1007/BF00198139

Source DB:  PubMed          Journal:  J Biomol NMR        ISSN: 0925-2738            Impact factor:   2.835


  30 in total

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5.  How is an NMR structure best defined? An analysis of molecular dynamics distance-based approaches.

Authors:  D A Pearlman
Journal:  J Biomol NMR       Date:  1994-01       Impact factor: 2.835

6.  Probability assessment of conformational ensembles: sugar repuckering in a DNA duplex in solution.

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Journal:  Biophys J       Date:  1995-01       Impact factor: 4.033

7.  Assessing the quality of solution nuclear magnetic resonance structures by complete cross-validation.

Authors:  A T Brünger; G M Clore; A M Gronenborn; R Saffrich; M Nilges
Journal:  Science       Date:  1993-07-16       Impact factor: 47.728

8.  Molecular dynamics with weighted time-averaged restraints for a DNA octamer. Dynamic interpretation of nuclear magnetic resonance data.

Authors:  U Schmitz; N B Ulyanov; A Kumar; T L James
Journal:  J Mol Biol       Date:  1993-11-20       Impact factor: 5.469

9.  Multiconformational analysis of solution NOE data for the Ac-(L)proline-(D)alanine-NHMe dipeptide in a nonprotic solvent.

Authors:  C R Landis; L L Luck; J M Wright
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10.  The three-dimensional structure of alpha1-purothionin in solution: combined use of nuclear magnetic resonance, distance geometry and restrained molecular dynamics.

Authors:  G M Clore; M Nilges; D K Sukumaran; A T Brünger; M Karplus; A M Gronenborn
Journal:  EMBO J       Date:  1986-10       Impact factor: 11.598

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  4 in total

1.  Automated detection of problem restraints in NMR data sets using the FINGAR genetic algorithm method.

Authors:  D A Pearlman
Journal:  J Biomol NMR       Date:  1999-04       Impact factor: 2.835

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Authors:  M Groth; J Malicka; C Czaplewski; S Ołdziej; L Lankiewicz; W Wiczk; A Liwo
Journal:  J Biomol NMR       Date:  1999-12       Impact factor: 2.835

3.  Dynamic NMR structures of [Rp]- and [Sp]-phosphorothioated DNA-RNA hybrids: is flexibility required for RNase H recognition?

Authors:  Marco Tonelli; Nikolai B Ulyanov; Todd M Billeci; Boleslaw Karwowski; Piotr Guga; Wojciech J Stec; Thomas L James
Journal:  Biophys J       Date:  2003-10       Impact factor: 4.033

4.  Enhanced Sampling of Interdomain Motion Using Map-Restrained Langevin Dynamics and NMR: Application to Pin1.

Authors:  Jill J Bouchard; Junchao Xia; David A Case; Jeffrey W Peng
Journal:  J Mol Biol       Date:  2018-05-16       Impact factor: 5.469

  4 in total

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