Open Source Python Molecular Science Software for Windows

Python Molecular Science Software for Windows

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Browse free open source Python Molecular Science Software for Windows and projects below. Use the toggles on the left to filter open source Python Molecular Science Software for Windows by OS, license, language, programming language, and project status.

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  • 1
    PyRx - Virtual Screening Tool

    PyRx - Virtual Screening Tool

    Virtual Screening software for Computational Drug Discovery

    PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for Rational Drug Design. Please visits PyRx home page to learn more about PyRx and watch videos on how to use it.
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    Downloads: 1,819 This Week
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  • 2
    Avogadro

    Avogadro

    An intuitive molecular editor and visualization tool

    Avogadro is an advanced molecular editor designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science and related areas. It offers a flexible rendering framework and a powerful plugin architecture.
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    Downloads: 869 This Week
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  • 3
    MzDOCK - Multiple Ligand Docking Tool

    MzDOCK - Multiple Ligand Docking Tool

    MzDOCK is A Virtual Screening Tool For Drug Discovery Research

    - Molecular Docking Virtual Screening Tool To Aid In Drug Discovery Research. - Published in Wiley, Journal of Computational Chemistry . Link: https://onlinelibrary.wiley.com/doi/abs/10.1002/jcc.27390 - Developed with Synchronized functioning of Python and Batch scripts -Integerated With Pymol-open-source for visualizing interaction (PSE file) generated from MzDOCK - Integrated with Molecule Drawing Tool - JSME Editor - If you are facing any issues or for queries . Contact us - kabeermuzammil614@gmail.com MzDOCK Development - Available on WindowsOS and Linux ubuntu 22.04 and more
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    Downloads: 50 This Week
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  • 4
    BioXTAS RAW

    BioXTAS RAW

    Processing and analysis of Small Angle X-ray Scattering (SAXS) data.

    BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis (EFA) or the regularized alternating least squares (REGALS) methods. Active source code is now maintained on github: https://github.com/jbhopkins/bioxtasraw To install: Check the instructions available at: http://bioxtas-raw.readthedocs.io/en/latest/install.html and in the Files tab. User guides: RAW guides are available at: http://bioxtas-raw.readthedocs.io/ and in the Files tab. To contact us, see: https://bioxtas-raw.readthedocs.io/en/latest/help.html
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    Downloads: 108 This Week
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  • 5
    RDKit

    RDKit

    Open-Source Cheminformatics and Machine Learning

    A collection of cheminformatics and machine-learning software written in C++ and Python. NOTE: the RDKit source code and downloads are now in github: https://github.com/rdkit/rdkit The core algorithms and data structures are written in C++. Wrappers are provided to use the toolkit from either Python or Java. Additionally, the RDKit distribution includes a PostgreSQL-based cartridge that allows molecules to be stored in relational database and retrieved via substructure and similarity searches.