In nature, some proteins partially unfold under specific environmental conditions. These unfolded states typically consist of a large ensemble of conformations; their proper description is therefore a challenging problem. NMR spectroscopy is particularly well suited for this task: information on conformational preferences can be derived for example from chemical shifts or residual dipolar couplings. This information, which is measured as a time- and ensemble-average, can be used to model these states by generating large ensembles of conformations. The challenge is then to select a minimum representative set of conformations out of a large ensemble to represent the unfolded state. 

We have developed for this purpose an algorithm called MINOES (MINimum Optimal Ensemble Selection), that is based on an iterative procedure based on a driven expansion/contraction selection process. MINOES aims at selecting an optimal and minimal ensemble of conformations that, on average, maximizes the agreement between back-calculated and experimental (NMR) data, without any a-priori assumption about the required ensemble size.



1.0 (January, 2009)


Krzeminski, M., Fuentes, G. Boelens R. and A.M.J.J. Bonvin, Utrecht University


Bijvoet Center for Biomolecular Research
Padualaan 8, 3584 CH Utrecht, the Netherlands
Email: a.m.j.j.bonvin_AT_uu.nl
Phone: +31-30-2533859
Fax: +31-30-2537623