CSSI: Frameworks: Interoperable high-performance classical, machine learning and quantum free energy methds in AMBER

The goal of this CSSI Frameworks project is to develop accurate and efficient free energy software tools within a powerful multiscale modeling framework in the Amber program package. This framework will enable molecular simulations with new classes of potential energy functions that involve interoperability between reactive, machine learning, and quantum many-body potentials. These potentials provide enhanced accuracy, robustness, and predictive capability with respect to classical molecular mechanics force fields and can be customized to meet the needs of applications in fields as diverse as chemical catalysis, enzyme design, and drug discovery. Free energy capability will be enabled through a robust endpoint approach that leverages the performance of the GPU-enabled Amber molecular dynamics engine.

The framework combines capabilities of the PuReMD, DeePMD, QUICK and Amber programs and employs industry-standard programming models to ensure performance portability and scalability on a diverse range of hardware architectures.