Workflow-Tools for Molecular Modeling

A common goal within computational chemistry, whether using Newtonian- or quantum-based methods (QM), is the accurate modeling of physical forces and energetics. Through reliable modeling of the underlying forces, molecular simulations provide atomistic insights into macroscopic experimental observations.

Although there are some commercial developments, most scientific software packages are written by scientists rather than by software engineers. This is due to the demanding and continuously evolving concepts from physics and chemistry that need to be transferred into proper algorithmic solutions. Our way for enabling our software to evolve is to decouple tasks – in doing so, algorithmic solutions can be introduced in a modular fashion, allowing us to easily identify and update specific tasks as needed. Using this idea, our group has developed several independent software tools.

© Fraunhofer SCAI

The figure shows how they address various inter-linked resolutions of molecular modeling to solve one of the primary goals of our research: To develop accurate and reliable molecular parameters and models in a reasonable time and as error-free as possible. For intramolecular interactions, we have created a scientific “Workflow for force-field optimization package” (Wolf2Pack) that incorporates our approach for transfering knowledge gained from QM to Newtonian- based models. We define a scientific workflow as a series of independent steps that are linked together according to the data flow and the dependencies between them. For intermolecular interactions we developed a systematic optimization workflow, based on efficient gradient-based numerical algorithms called GROW. GROW is a modular tool kit of programs and scripts. It is a generic implementation and can be easily extended by other developers.

Both programs facilitate: a) the development and optimization of molecular parameters for a given simulation engine, b) the transfer of parameters from one software package to another, and c) testing of the parameters using a standard test suite and protocol via a semi-automated iterative parameterization process.

In combination, the joint efforts of scientists and software engineers at SCAI greatly enhance the task of molecular modeling through superior software tools. Their modular structure not only eases the addition of new functions and maintenance, but more importantly accelerates the modeling process and makes it more robust. Users will therefore benefit in terms of both time and resources due to our software and services.


M. Hülsmann, T. Köddermann, J. Vrabec, and D. Reith: “GROW: A Gradient-based optimisation workflow for the automated development of molecular models”, Computer Physics Communications 181, 499–513 (2010).

M. Hülsmann, J. Vrabec, A. Maaß, and D. Reith: “Assessment of Numerical Optimization Algorithms for the Development of New Molecular Models.”  Computer Physics Communications 18,  887–905 (2010).

M. Hülsmann, T. J. Müller, T. Köddermann, and D. Reith: „Automated Force Field Optimisation of Small Molecules using a Gradient–Based Workflow Package.” Molecular Simulation 36, 1182-96 (2010).

D. Reith and K. N. Kirschner, “A modern workflow for force-field development – bridging quantum mechanics and atomistic computational models.,” Comp. Phys. Comm. 182, 2184 (2011).