The elastic network model reveals a consistent picture on intrinsic functional dynamics of type II restriction endonucleases

Abstract

The vibrational dynamics of various type II restriction endonucleases, in complex with cognate/non-cognate DNA and in the apo form, are investigated with the elastic network model in order to reveal common functional mechanisms in this enzyme family. Scissor-like and tong-like motions observed in the slowest modes of all enzymes and their complexes point to common DNA recognition and cleavage mechanisms. Normal mode analysis further points out that the scissor-like motion has an important role in differentiating between cognate and non-cognate sequences at the recognition site, thus implying its catalytic relevance. Flexible regions observed around the DNA-binding site of the enzyme usually concentrate on the highly conserved β-strands, especially after DNA binding. These β-strands may have a structurally stabilizing role in functional dynamics for target site recognition and cleavage. In addition, hot spot residues based on high-frequency modes reveal possible communication pathways between the two distant cleavage sites in the enzyme family. Some of these hot spots also exist on the shortest path between the catalytic sites and are highly conserved.

Second-Shell Basic Residues Expand the Two-Metal-Ion Architecture of DNA and RNA Processing Enzymes

“…Lys61 and Lys126 generate an electrostatic potential distribution around the active site, analogous to that observed for K1 and K2 ions in the group II intron (+8.5 kT/e; Figure 1 B). Notably, Lys61 and Lys126 are strictly conserved in different bacterial species ( Data S1 ) and aid cognate DNA binding via large amplitude motions ( Uyar et al., 2011 ) and favorable Coulombic interactions ( Sun et al., 2003 ) ( Table 1 ).…”

Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes: The Hemoglobin Case

“…Based on ENM results, Chennubhotla et al [ 72 ] revealed that hot spots residues show a moderate-high flexibility at global modes. On the other hand, hot spots correlated very well with the residues with high mean-square fluctuations in the highest frequency modes in both GNM [ 73 , 74 ] and ANM [ 22 ]. Ozbek et al [ 74 ] have found that hot spots predictions based on the highest, the second and third highest, and the average three and five highest GNM modes show similar accuracies.…”

“…ENM is an efficient computational tool to describe the essential vibrational dynamics encoded in the molecular topology [ 17 – 20 ]. It has been proved that the low-frequency modes of ENM are critical of collective motions [ 21 ], while the high-frequency modes can identify hot spots for protein-protein interactions [ 22 ].…”

Computational Ways to Enhance Protein Inhibitor Design

“…The Elastic Network Models (ENM) have proven themselves to be highly useful in representing the global motions for a wide variety of diverse protein structures (Bahar and Jernigan, 1997Bahar et al, 1997a,b,c;Demirel et al, 1998;Keskin et al, 1998Keskin et al, , 2000Keskin et al, , 2002aJernigan et al, 1999Jernigan et al, , 2000Jernigan et al, , 2008Atilgan et al, 2001;Bahar and Rader, 2005;Sen et al, 2006;Jernigan and Kloczkowski, 2007;Yang et al, 2007Yang et al, , 2008Yang et al, , 2009Zhu and Hummer, 2010;Bakan et al, 2011;Karaca and Bonvin, 2011;May and Brooks, 2011;Peng and Head-Gordon, 2011;Uyar et al, 2011;Wieninger et al, 2011;Zheng, 2011;Zheng and Auerbach, 2011;Zimmermann et al, 2011a,b;Duttmann et al, 2012;Gniewek et al, 2012;Isin et al, 2012;Martin et al, 2012;Ruvinsky et al, 2012;Globisch et al, 2013;Kim et al, 2013;Sanejouand, 2013;Dasgupta et al, 2014). Since they have proven to be so successful in capturing the most important motions of protein structures, it is reasonable to expect that they should also be able to estimate the conformational entropies of structures.…”