Simplified Normal Mode Analysis of Conformational Transitions in DNA-dependent Polymerases: the Elastic Network Model

Abstract

The Elastic Network Model is used to investigate the open/closed transition in all DNA-dependent polymerases whose structure is known in both forms. For each structure the model accounts well for experimental crystallographic B-factors. It is found in all cases that the transition can be well described with just a handful of the normal modes. Usually, only the lowest and/or the second lowest frequency normal modes deduced from the open form give rise to calculated displacement vectors that have a correlation coefficient larger than 0.50 with the observed difference vectors between the two forms. This is true for every structural class of DNA-dependent polymerases where a direct comparison with experimental structural data is available. In cases where only one form has been observed by X-ray crystallography, it is possible to make predictions concerning the possible existence of another form in solution by carefully examining the vector displacements predicted for the lowest frequency normal modes. This simple model, which has the advantage to be computationally inexpensive, could be used to design novel kind of drugs directed against polymerases, namely drugs preventing the open/closed transition from occurring in bacterial or viral DNA-dependent polymerases.

Long-range energy transfer in proteins

“…solved through x-ray crystallography) and R c is a distance cutoff that specifies which pairs of nodes are interacting. Note that k 4 = 0 corresponds to the widely used elastic network model (ENM) [41][42][43], which has proven useful for quantitatively describing amino acid fluctuations at room temperature [41,42,44,45], as well as for predicting or characterizing large-amplitude functional motions of proteins [46][47][48][49][50] in agreement with all-atom models [51][52][53], paving the way for numerous applications in structural biology [54][55][56][57].…”

Solution structure of RNase P RNA

“…MD simulations are highly sensitive to, and restricted by, the starting conformation, and so may fail to capture significant motions in macromolecular models based primarily on homology and biochemical information, e.g., the Eco and Atu RNA models described above. Since such collective motions in macromolecules often correlate with perturbations along elastic normal modes (Delarue and Sanejouand 2002;Tama et al 2003;Mitra et al 2005; Matsumoto and Ishida 2009), we investigated whether coarse-grain normal mode analysis (NMA) (Tirion 1996) combined with the ensemble optimization method (Bernado et al 2007) could extract structural models of these RNase P RNAs with improved fit to the SAXS data.…”

Vibrational subsystem analysis: A method for probing free energies and correlations in the harmonic limit

“…[5][6][7][8][9] This ability is predicated on the theory that harmonic dynamics are sufficient for understanding the collective motions of near-native states with low frequency normal modes dominating the qualitative dynamics. 7,[10][11][12][13][14] This assertion has been shown to be a good approximation by numerous groups [15][16][17][18][19][20][21][22][23] and has led to the development of elastic network model ͑ENM͒ methods. [2][3][4] These methods typically replace all-atom descriptions with C ␣ -centered harmonic potentials that utilize a single force constant to account for all pairwise interactions within some cutoff distance ͑R c ͒.…”