GneimoSim: A modular internal coordinates molecular dynamics simulation package

Abstract

The Generalized Newton Euler Inverse Mass Operator (GNEIMO) method is an advanced method for internal coordinates molecular dynamics (ICMD). GNEIMO includes several theoretical and algorithmic advancements that address longstanding challenges with ICMD simulations. In this paper we describe the GneimoSim ICMD software package that implements the GNEIMO method. We believe that GneimoSim is the first software package to include advanced features such as the equipartition principle derived for internal coordinates, and a method for including the Fixman potential to eliminate systematic statistical biases introduced by the use of hard constraints. Moreover, by design, GneimoSim is extensible and can be easily interfaced with third party force field packages for ICMD simulations. Currently, GneimoSim includes interfaces to LAMMPS, OpenMM, Rosetta force field calculation packages. The availability of a comprehensive Python interface to the underlying C++ classes and their methods provides a powerful and versatile mechanism for users to develop simulation scripts to configure the simulation and control the simulation flow. GneimoSim has been used extensively for studying the dynamics of protein structures, refinement of protein homology models, and for simulating large scale protein conformational changes with enhanced sampling methods. GneimoSim is not limited to proteins and can also be used for the simulation of polymeric materials.

Distinct structural mechanisms determine substrate affinity and kinase activity of protein kinase Cα

“…The Rosetta software suite has many functionalities that have been shown to perform well consistently, for protein structure refinement and side chain repacking 4 . We have previously combined the GneimoSim software 5 with the Rosetta software to (1) perform torsion MD simulations with Rosetta forcefield 6 and to (2) enhance the conformational sampling during protein structure refinement by combining the benefits torsional MD in GNEIMO with the torsional Monte Carlo sampling and side chain repacking in Rosetta using a rotamer library. The details of the software integration can be found in reference number 5.…”

Overcoming potential energy distortions in constrained internal coordinate molecular dynamics simulations

“…[20][21][22][23][24][25] Here, we describe the GNEIMO method briefly since it is the basis for the hybrid ICMD method. Since some of the bond lengths and bond angles can be treated as rigid in the hybrid ICMD GNEIMO method, the degrees of freedom in the equations of motion in ICMD method become coupled and have the form…”

“…Additionally, the GNEIMO-Fixman method 19,20 for the calculation of the Fixman torque continues to apply even when the bond angles are open. The GNEIMO method forms the basis of the GneimoSim ICMD software package 25 which has been used for a variety of biomolecular applications such as protein folding, 23,24,27 domain motion, 28,29 and refinement of protein homology models. 22,23,30,31 A. Fixman potential to correct for the intrinsic distortion…”

High‐performance transformation of protein structure representation from internal to Cartesian coordinates

“…On the other hand, internal-coordinate dynamics have seen a recent increase in popularity for specialized applications. [23,25,31,32,44] In general, we expect that the most valuable applications for this algorithm are those in which internal-coordinate representations are recognized as an advantageous way to sample large numbers of polymeric conformations. These include tasks such as fitting protein structures to low-resolution experimental data [44][45][46] (e.g., cryo-EM and SAXS/WAXS [47,48] ), constructing free energy landscapes, [49,50] Monte Carlo simulations of proteins, [51][52][53] and simulations of polymeric materials.…”

“…Abagyan and Mazur et al have spent enormous effort to develop such an infrastructure, and others have recently begun to implement comparable tools. [23,24,31,32] Instead, our work aims primarily to advance capabilities for applications where IC have significant advantages, but where complex software infrastructure is currently Cartesian-centric and expected to remain so.…”