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

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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.CEF90121
Database: BASE
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  – Url: https://doi.org/10.1021/acs.jcim.5c00936.s001#
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  Data: PaCS-Q: Python Toolkits for Path Sampling in MD and QM/MM MD Simulation
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Lian+Duan%22">Lian Duan</searchLink><br /><searchLink fieldCode="AR" term="%22Kowit+Hengphasatporn%22">Kowit Hengphasatporn</searchLink><br /><searchLink fieldCode="AR" term="%22Yasuteru+Shigeta%22">Yasuteru Shigeta</searchLink>
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2025
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Biochemistry%22">Biochemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Medicine%22">Medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Evolutionary+Biology%22">Evolutionary Biology</searchLink><br /><searchLink fieldCode="DE" term="%22Sociology%22">Sociology</searchLink><br /><searchLink fieldCode="DE" term="%22Inorganic+Chemistry%22">Inorganic Chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Plant+Biology%22">Plant Biology</searchLink><br /><searchLink fieldCode="DE" term="%22Space+Science%22">Space Science</searchLink><br /><searchLink fieldCode="DE" term="%22Biological+Sciences+not+elsewhere+classified%22">Biological Sciences not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22Chemical+Sciences+not+elsewhere+classified%22">Chemical Sciences not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Systems+not+elsewhere+classified%22">Information Systems not elsewhere classified</searchLink><br /><searchLink fieldCode="DE" term="%22studying+covalent+reactions%22">studying covalent reactions</searchLink><br /><searchLink fieldCode="DE" term="%22parallel+cascade+selection%22">parallel cascade selection</searchLink><br /><searchLink fieldCode="DE" term="%22install+via+pip%22">install via pip</searchLink><br /><searchLink fieldCode="DE" term="%22https+%3A%2F%2F+github%22">https :// github</searchLink><br /><searchLink fieldCode="DE" term="%22enabling+efficient+exploration%22">enabling efficient exploration</searchLink><br /><searchLink fieldCode="DE" term="%22source+python+toolkit%22">source python toolkit</searchLink><br /><searchLink fieldCode="DE" term="%22enabling+advanced+simulations%22">enabling advanced simulations</searchLink><br /><searchLink fieldCode="DE" term="%22amber+md+suite%22">amber md suite</searchLink><br /><searchLink fieldCode="DE" term="%22python+toolkits%22">python toolkits</searchLink><br /><searchLink fieldCode="DE" term="%22md+simulations%22">md simulations</searchLink><br /><searchLink fieldCode="DE" term="%22versatile+solution%22">versatile solution</searchLink><br /><searchLink fieldCode="DE" term="%22unbinding+events%22">unbinding events</searchLink><br /><searchLink fieldCode="DE" term="%22structure+analysis%22">structure analysis</searchLink><br /><searchLink fieldCode="DE" term="%22seamlessly+integrated%22">seamlessly integrated</searchLink><br /><searchLink fieldCode="DE" term="%22representative+structures%22">representative structures</searchLink><br /><searchLink fieldCode="DE" term="%22quantum+calculations%22">quantum calculations</searchLink><br /><searchLink fieldCode="DE" term="%22path+sampling%22">path sampling</searchLink><br /><searchLink fieldCode="DE" term="%22orca+directly%22">orca directly</searchLink><br /><searchLink fieldCode="DE" term="%22mm+md%22">mm md</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: 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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  Data: article in journal/newspaper
– Name: Language
  Label: Language
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  Data: unknown
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1021/acs.jcim.5c00936.s001
– Name: URL
  Label: Availability
  Group: URL
  Data: https://doi.org/10.1021/acs.jcim.5c00936.s001<br />https://figshare.com/articles/journal_contribution/PaCS-Q_Python_Toolkits_for_Path_Sampling_in_MD_and_QM_MM_MD_Simulation/29413230
– Name: Copyright
  Label: Rights
  Group: Cpyrght
  Data: CC BY-NC 4.0
– Name: AN
  Label: Accession Number
  Group: ID
  Data: edsbas.CEF90121
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      – Type: doi
        Value: 10.1021/acs.jcim.5c00936.s001
    Languages:
      – Text: unknown
    Subjects:
      – SubjectFull: Biochemistry
        Type: general
      – SubjectFull: Medicine
        Type: general
      – SubjectFull: Genetics
        Type: general
      – SubjectFull: Evolutionary Biology
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      – SubjectFull: Sociology
        Type: general
      – SubjectFull: Inorganic Chemistry
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      – SubjectFull: Plant Biology
        Type: general
      – SubjectFull: Space Science
        Type: general
      – SubjectFull: Biological Sciences not elsewhere classified
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      – SubjectFull: Chemical Sciences not elsewhere classified
        Type: general
      – SubjectFull: Information Systems not elsewhere classified
        Type: general
      – SubjectFull: studying covalent reactions
        Type: general
      – SubjectFull: parallel cascade selection
        Type: general
      – SubjectFull: install via pip
        Type: general
      – SubjectFull: https :// github
        Type: general
      – SubjectFull: enabling efficient exploration
        Type: general
      – SubjectFull: source python toolkit
        Type: general
      – SubjectFull: enabling advanced simulations
        Type: general
      – SubjectFull: amber md suite
        Type: general
      – SubjectFull: python toolkits
        Type: general
      – SubjectFull: md simulations
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      – SubjectFull: versatile solution
        Type: general
      – SubjectFull: unbinding events
        Type: general
      – SubjectFull: structure analysis
        Type: general
      – SubjectFull: seamlessly integrated
        Type: general
      – SubjectFull: representative structures
        Type: general
      – SubjectFull: quantum calculations
        Type: general
      – SubjectFull: path sampling
        Type: general
      – SubjectFull: orca directly
        Type: general
      – SubjectFull: mm md
        Type: general
    Titles:
      – TitleFull: PaCS-Q: Python Toolkits for Path Sampling in MD and QM/MM MD Simulation
        Type: main
  BibRelationships:
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          Name:
            NameFull: Lian Duan
      – PersonEntity:
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            NameFull: Kowit Hengphasatporn
      – PersonEntity:
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            NameFull: Yasuteru Shigeta
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
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