MINOES

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.

Details

Version:

1.0 (January, 2009)

Authors:

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

Contact:

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

Reference:

• M. Krzeminski, G. Fuentes, R. Boelens and A.M.J.J. Bonvin, "MINOES: a new approach to select a representative ensemble of structures in NMR studies of (partially) unfolded states. Application to d25-PYP.", Proteins: Struc. Funct. & Bioinformatic, 74, 894-905 (2009).