Protein dynamic communities from elastic network models align closely to the communities defined by molecular dynamics

Abstract

Dynamic communities in proteins comprise the cohesive structural units that individually exhibit rigid body motions. These can correspond to structural domains, but are usually smaller parts that move with respect to one another in a protein’s internal motions, key to its functional dynamics. Previous studies emphasized their importance to understand the nature of ligand-induced allosteric regulation. These studies reported that mutations to key community residues can hinder transmission of allosteric signals among the communities. Usually molecular dynamic (MD) simulations (~ 100 ns or longer) have been used to identify the communities—a demanding task for larger proteins. In the present study, we propose that dynamic communities obtained from MD simulations can also be obtained alternatively with simpler models–the elastic network models (ENMs). To verify this premise, we compare the specific communities obtained from MD and ENMs for 44 proteins. We evaluate the correspondence in communities from the two methods and compute the extent of agreement in the dynamic cross-correlation data used for community detection. Our study reveals a strong correspondence between the communities from MD and ENM and also good agreement for the residue cross-correlations. Importantly, we observe that the dynamic communities from MD can be closely reproduced with ENMs. With ENMs, we also compare the community structures of stable and unstable mutant forms of T4 Lysozyme with its wild-type. We find that communities for unstable mutants show substantially poorer agreement with the wild-type communities than do stable mutants, suggesting such ENM-based community structures can serve as a means to rapidly identify deleterious mutants.

Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-Grained Simulations and Elastic Network Models

“…Except as mentioned above, ENMs have been successfully used in many combinations with different input information and methods, such as, for example, data from electron microscopy [ 14 ], atomistic MD simulations [ 17 , 77 ], Brownian simulations [ 78 ], structure-based models [ 79 , 80 ], and many other combinations that have been thoroughly reviewed [ 13 , 14 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ].…”

Structural compliance: A new metric for protein flexibility

“…The compliance and stiffness maps proposed in this paper can serve as another way to study protein packing. The compliance and stiffness profiles can help us to determine the dynamic communities 32‐34 and to coarse‐grain them for further analysis. We can use a hinge prediction method (PACKMAN 22 ) based on packing densities to identify the hinges in the parts of the protein that tend to be more flexible, making these sites responsible for the global deformability.…”

Modeling of Protein Structural Flexibility and Large-Scale Dynamics: Coarse-grained Simulations and Elastic Network Models

“…Except as mentioned above, ENMs have been successfully used in many combinations with different input information and methods, such as for example data from electron microscopy [14], atomistic MD simulations [17,78], Brownian simulations [79], structure-based models [80,81] and many other combinations that have been thoroughly reviewed [13,14,[54][55][56][57][58][59][60][61][62][63]. When the range of protein structural dynamics studies can be limited to a roughly defined vicinity of a specific folded structure (determined by experiment), ENM, CG models or their modifications can be very effective in predicting protein flexibility [8,36,[82][83][84].…”

“…Since such large-scale conformational transitions are frequently slow and difficult for detailed modeling with MD simulations the above mentioned ENM approach represents a very useful and computationally inexpensive alternative method to study them. Both approaches usually give similar results [78]. ENM-based methods have been successfully applied to structural transitions of very large molecular structures [14], such as a ribosome [120][121][122].…”