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PDB2ENTROPY and PDB2TRENT: Conformational and Translational-Rotational Entropy from Molecular Ensembles.

Federico FogolariOrnela MalokuCedrix Jurgal Dongmo FoumthuimAlessandra CorazzaGennaro Esposito
Published in: Journal of chemical information and modeling (2018)
Entropy calculation is an important step in the postprocessing of molecular dynamics trajectories or predictive models. In recent years the nearest neighbor method has emerged as a powerful method to deal in a flexible way with the dimensionality of the problem. Here we provide two programs, PBD2ENTROPY and PDB2TRENT that compute the conformational and translational-rotational entropy, respectively, based on the nearest neighbor method. PDB2ENTROPY takes in input two files containing the following: (1) conformational ensembles of the same molecule(s) in PDB format and (2) definitions of torsion angles (a default file is provided where additional user definitions can be easily implemented). PDB2TRENT takes in a file containing samples of the complexed molecules, a string specifying atoms providing the reference framework to superimpose samples, and a string specifying atoms used to compute rotation and translation of one molecule with respect to the other. The C programs and sample demonstration data are available on the GitHub repository (URL: http://github.com/federico-fogolari/pdb2entropy and http://github.com/federico-fogolari/pdb2trent ).
Keyphrases
  • molecular dynamics
  • single molecule
  • molecular dynamics simulations
  • density functional theory
  • machine learning
  • deep learning