Ensemble proteins

DM Lorber, BK Shoichet. Flexible ligand docking using conformational ensembles. Protein Sci 7 938-950, 1998. 

Multiscale characterization of protein conformational ensembles. Proteins, 76 (4), 837-851. 

Tobias D J, Martyna G J and Klein M L 1993 Molecular dynamics simulations of a protein In the canonical ensemble J. Phys. Chem. 9712959-66... 

Naturally occurring molecular ensembles such as proteins from photosyntlietic systems (plants, algae, photosyntlietic bacteria, etc) are usually relatively rigid systems tliat contain various cliromophores and hold tliem at fixed positions and orientations relative to each otlier. That is why, despite tire numerous energy jumps between tire cliromophores, tlie resulting emitted fluorescence is polarized. The extent of tliis polarization tlius affords invaluable infonnation about tlie internal stmcture of molecular complexes. 

Fig. 9. Two-dimensional sketch of the 3N-dimensional configuration space of a protein. Shown are two Cartesian coordinates, xi and X2, as well as two conformational coordinates (ci and C2), which have been derived by principle component analysis of an ensemble ( cloud of dots) generated by a conventional MD simulation, which approximates the configurational space density p in this region of configurational space. The width of the two Gaussians describe the size of the fluctuations along the configurational coordinates and are given by the eigenvalues Ai.

Step 1 A short conventional MD simulation (typically extending over a few lOOps) is performed to generate an ensemble of protein structures x 6 71 (each described by N atomic positions), which characterizes the initial conformational substate. The 2-dimensional sketch in Fig. 9 shows such an ensemble as a cloud of dots, each dot x representing one snapshot of the protein. 

M.J. Sippl, M. Hendlich and P. Lackner, Assembly of polypeptide and protein backbone conformations from low energy ensembles of short fragments. Protein Sci. 1 (1992), 625-640. 

M J1990. Calculation of Conformational Ensembles from Potentials of Mean Force. An Approach o the Knowledge-Based Prediction of Local Structures in Globular Proteins. Journal of Molecular Siology 213 859-883. 

MI Sippl. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures m globular proteins. I Mol Biol 213 859-883, 1990. 

It is important to emphasize that this lattice database is highly idealized compared to real databases. Unlike the lattice database, real databases cannot be treated as thermodynamic ensembles of protein-ligand complexes equilibrated at room temperature [33,34]. Two of the more straightforward reasons are mentioned here. First, real databases are inherently biased toward strong binders (K < 10 pM), because weak binders are difficult to crystallize and of lesser interest. Second, as mentioned above, real databases are not composed of a representative selection of proteins and ligands, and their compositions are biased toward peptide and peptidomimetic inhibitors and certain protein superfamilies. In contrast, because only one protein and four ligand types are used, the lattice database should have representative ligand compositions. 

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