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

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Bibliographic Details
Title: PaCS-Q: Python Toolkits for Path Sampling in MD and QM/MM MD Simulation
Authors: Lian Duan, Kowit Hengphasatporn, Yasuteru Shigeta
Publication Year: 2025
Subject Terms: Biochemistry, Medicine, Genetics, Evolutionary Biology, Sociology, Inorganic Chemistry, Plant Biology, Space Science, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, studying covalent reactions, parallel cascade selection, install via pip, https :// github, enabling efficient exploration, source python toolkit, enabling advanced simulations, amber md suite, python toolkits, md simulations, versatile solution, unbinding events, structure analysis, seamlessly integrated, representative structures, quantum calculations, path sampling, orca directly, mm md
Description: 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/.
Document Type: article in journal/newspaper
Language: unknown
DOI: 10.1021/acs.jcim.5c00936.s001
Availability: https://doi.org/10.1021/acs.jcim.5c00936.s001
https://figshare.com/articles/journal_contribution/PaCS-Q_Python_Toolkits_for_Path_Sampling_in_MD_and_QM_MM_MD_Simulation/29413230
Rights: CC BY-NC 4.0
Accession Number: edsbas.96DB39C6
Database: BASE
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