Orientational Restraints

2002 ◽  
pp. 179-205 ◽  
Author(s):  
Eva de Alba ◽  
Nico Tjandra
Keyword(s):  
Orientational Restraints

Atomic Refinement Using Orientational Restraints from Solid-State NMR

2000 ◽  
Vol 147 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Richard Bertram ◽  
J.R Quine ◽  
Michael S Chapman ◽  
Timothy A Cross
Keyword(s):  
Solid State ◽  
Solid State Nmr ◽  
Orientational Restraints

scholarly journals Continuity conditions and torsion angles from ssNMR orientational restraints

2008 ◽  
Vol 191 (1) ◽  
pp. 24-30 ◽  
Author(s):  
S. Achuthan ◽  
T. Asbury ◽  
J. Hu ◽  
R. Bertram ◽  
T.A. Cross ◽  
...  
Keyword(s):  
Torsion Angles ◽  
Orientational Restraints

Calculation ofz-Coordinates and Orientational Restraints Using a Metal Binding Tag†

Biochemistry ◽  
2000 ◽  
Vol 39 (49) ◽  
pp. 15217-15224 ◽  
Author(s):  
Vadim Gaponenko ◽  
Alex Dvoretsky ◽  
Charles Walsby ◽  
Brian M. Hoffman ◽  
Paul R. Rosevear
Keyword(s):  
Metal Binding ◽  
Orientational Restraints

scholarly journals Protein loop closure using orientational restraints from NMR data

2011 ◽  
Vol 80 (2) ◽  
pp. 433-453 ◽  
Author(s):  
Chittaranjan Tripathy ◽  
Jianyang Zeng ◽  
Pei Zhou ◽  
Bruce Randall Donald
Keyword(s):  
Loop Closure ◽  
Nmr Data ◽  
Orientational Restraints

DADIMODO: a program for refining the structure of multidomain proteins and complexes against small-angle scattering data and NMR-derived restraints

2011 ◽  
Vol 44 (6) ◽  
pp. 1264-1271 ◽  
Author(s):  
Guillaume Evrard ◽  
Fabien Mareuil ◽  
Francois Bontems ◽  
Christina Sizun ◽  
Javier Perez
Keyword(s):  
Conformational Changes ◽  
Small Angle ◽  
Scattering Data ◽  
Multidomain Proteins ◽  
Domain Structures ◽  
X Ray Scattering ◽  
Angle Scattering ◽  
Stochastic Optimization Algorithm ◽  
User Friendly ◽  
Orientational Restraints

DADIMODOis a program for refining atomic models of multidomain proteins or complexes against small-angle X-ray scattering data. Interdomain distance and orientational restraints, such as those derived from NMR measurements, can be included in the optimization process. While domain structures are mainly kept rigid, flexible regions can be user defined. Stepwise generic conformational changes, specified by the user, are applied cyclically in a stochastic optimization algorithm that performs a search in the protein conformation space. The convergence for this genetic algorithm is driven by an adaptable selection pressure. The algorithmic structure guarantees that a physically acceptable full atomic model of the structure is present at all stages of the optimization. A graphical user interface ensures user-friendly handling.

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