Project Grant 2209718

This $750,000 Project Grant from the National Science Foundation Division of Chemistry, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of accurate and efficient free energy simulation software within the widely-used AMBER molecular modeling framework. The grant recipient, Rutgers, The State University, will enhance AMBER to enable the routine application of free energy methods using quantum mechanics, machine learning, reactive and classical potentials to problems advancing biological and chemical sciences.

Specifically, open-source high-performance software for free energy simulations will be designed for multi-layered hybrid potentials combining linear-scaling quantum mechanical methods via GPU-accelerated Quick, scalable reactive ReaxFF force fields via PureMD, and machine learning potentials such as DeepPotent, ANI, and AP-Net. The cyberinfrastructure will leverage AMBER's CUDA MD engine and GPU architectures using standard programming models, with innovative parallel algorithms ensuring scalability. This will expand the scope and success of free energy applications among AMBER's broad user base in academia, industry, and national laboratories in areas like drug discovery, enzyme catalysis, and biomaterials design.