PaCS-Q: Python Toolkits for Path Sampling in MD and QM/MM MD Simulation

• Published in: Journal of chemical information and modeling Vol. 65; no. 13; pp. 6441 - 6445
• Main Authors: Duan, Lian, Hengphasatporn, Kowit, Shigeta, Yasuteru
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 14.07.2025
• Subjects: Algorithms; Complexity; Computational chemistry; Molecular Dynamics Simulation; Quantum Theory; Sampling; Simulation; Software; Structural analysis; Toolkits
• ISSN: 1549-9596; 1549-960X; 1549-960X
• DOI: 10.1021/acs.jcim.5c00936

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/.