By Arno Proeme.

A version of this post originally appeared on the EPCC blog.

Unfortunately, the APES project (pronounced A-PES) has nothing to do with our chimp cousins, and instead stands for Advanced Potential Energy Surfaces. It will help researchers advance their understanding of the structure and function of molecules by improving the models used to represent their force fields. For example, it could help understand the interaction between the simian olfactory receptors and isoamyl acetate, which gives bananas their irresistible allure.

The APES project will improve a number of software packages used in computational chemistry, such as TINKER, Amber, DL_POLY, ONETEP and Q-Chem. The project will implement more realistic modelling of molecular forces and improve computational performance by improving the parallelisation of the code (a term used to describe the speeding up of code by running it simultaneously on many processors). The project will improve the long-term health of the software by promoting interoperability between the software packages, making it easier for researchers to use the software and for developers to contribute to it.

Together with Mario Antonioletti, my main contribution will be to parallelise TINKER. This will allow the software to take advantage of large-scale compute resources such as HECToR (one of the UK's supercomputers) and its upcoming successor, ARCHER, as well as NFS-provided resources in the US. This may involve significant refactoring of the code, possibly translation of Fortran code, and careful integration of multiple development branches across the collaboration.

Potential energy functions (referred to as force fields by chemists) are used to model how molecules interact. Current models represent molecules using fixed point charges, because it makes computation simpler whilst providing reasonable results. However, this simplification leads to inaccurate results for some systems, such as those that include many molecules or those in which charge distribution varies with time. This limits the application of computer simulations to a variety of grand challenges, such as design of environmentally friendly materials, chemical reactions and reactivity, and biological complexity such as protein-drug interactions. Getting round the problem means changing the way in which force fields are modelled. Polarisable empirical force fields allow the charges in the molecule to change dependent on the environment. They offer a clear improvement in accuracy, but are much more complex and computationally intensive.

AMOEBA is a prominent polarisable empirical force field implemented in TINKER and Amber that provides good results in a number of cases not well described by established force fields. (It is also used in the Folding@Home project.) Together with the EPCC, the Software Sustainability Institute will provide parallel (hybrid OpenMP/MPI) implementations of algorithms so that the AMOEBA can be used on high-performance computing clusters. We will then validate these algorithms in TINKER and ensure interoperability with other packages (Amber, DL_POLY, ONETEP, and Q-Chem) in order to promote uptake.

We will use an open development process to build a community around the packages that implement AMOEBA and variants of this model which, in the long term, will make the future development of this force field self-sustaining. This will also make it easier for AMOEBA to be adopted by other software packages thus growing the community that can exploit this method.

This international partnership consists of members from the Software Sustainability Institute, the EPCC at the University of Edinburgh, the University of Southampton, Daresbury Laboratory and from the US we have the University of California (Berkeley), Rutgers University, Claremont Colleges, Washington University in Saint Louis and New York University. The project started mid-April of this year and we shall blog updates as the project progresses. The project is a collaboration between the Software Sustainability Institute and the EPCC. It is a US-UK funded collaboration by the NSF and EPSRC.