07 December 2018

RIP-MD: a tool to study residue interaction networks in protein molecular dynamics.

DOI : 10.7717/peerj.5998

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Alberto J. Martín, PhD.

Protein structure is not static; residues undergo conformational rearrangements

and, in doing so, create, stabilize or break non-covalent interactions.

Molecular dynamics (MD) is a technique used to simulate these movements with

atomic resolution. However, given the data-intensive nature of the technique,

gathering relevant information from MD simulations is a complex and time

consuming process requiring several computational tools to perform these

analyses. Among different approaches, the study of residue interaction networks

(RINs) has proven to facilitate the study of protein structures. In a RIN, nodes

represent amino-acid residues and the connections between them depict

non-covalent interactions. Here, we describe residue interaction networks in

protein molecular dynamics (RIP-MD), a visual molecular dynamics (VMD) plugin to

facilitate the study of RINs using trajectories obtained from MD simulations of

proteins. Our software generates RINs from MD trajectory files. The non-covalent

interactions defined by RIP-MD include H-bonds, salt bridges, VdWs, cation-π,

π-π, Arginine-Arginine, and Coulomb interactions. In addition, RIP-MD also

computes interactions based on distances between Cαs and disulfide bridges. The

results of the analysis are shown in an user friendly interface. Moreover, the

user can take advantage of the VMD visualization capacities, whereby through

some effortless steps, it is possible to select and visualize interactions

described for a single, several or all residues in a MD trajectory. Network and

descriptive table files are also generated, allowing their further study in

other specialized platforms. Our method was written in python in a parallelized

fashion. This characteristic allows the analysis of large systems impossible to

handle otherwise. RIP-MD is available at http://www.dlab.cl/ripmd.

Participating Center Researchers

Network Biology Laboratory

PhD in Computer Science, University College Dublin, Ireland.


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