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PaCS-Q: Python Toolkits for Path Sampling in MD and QM/MM MD Simulation
Lian Duan1,2, Kowit Hengphasatporn2,3, Yasuteru Shigeta2
1Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.
Abstract:
PaCS-Q is an open-source Python toolkit that simplifies QM/MM MD and MD simulations, making complex pathway sampling accessible and user-friendly. Seamlessly integrated with the AMBER MD suite, it automates QM/MM MD simulations using the parallel cascade selection (PaCS) algorithm, enabling efficient exploration of reaction pathways without predefined reaction coordinates. PaCS-Q supports both RMSD- and distance-based sampling, which is ideal for studying covalent reactions and ligand binding/unbinding events. A key feature is its ability to automatically generate QM input files for Gaussian and ORCA directly from representative structures, streamlining the transition from MD to quantum calculations. With built-in tools for structure analysis and energy profiling, PaCS-Q minimizes setup complexity and enhances reproducibility. Easy to install via pip and compatible with Unix-based systems, PaCS-Q offers a practical, versatile solution for researchers in computational chemistry and drug discovery, enabling advanced simulations with speed, accuracy, and minimal effort. The PaCS-Q Python toolkit publicly available at https://github.com/nyelidl/PaCS-Q/.
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