Open Source Python Molecular Science Software for Linux
Sort By:
Python Molecular Science Software for Linux
View 270 business solutionsBrowse free open source Python Molecular Science Software for Linux and projects below. Use the toggles on the left to filter open source Python Molecular Science Software for Linux by OS, license, language, programming language, and project status.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Windocks - Docker Oracle and SQL Server ContainersWindocks is a leader in cloud native database DevOps, recognized by Gartner as a Cool Vendor, and as an innovator by Bloor research in Test Data Management. Novartis, DriveTime, American Family Insurance, and other enterprises rely on Windocks for on-demand database environments for development, testing, and DevOps. Windocks software is easily downloaded for evaluation on standard Linux and Windows servers, for use on-premises or cloud, and for data delivery of SQL Server, Oracle, PostgreSQL, and MySQL to Docker containers or conventional database instances.
-
1
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.">
-
2
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. -
3
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 - Software Authorship - Muzammil Kabier -
4
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">
-
Run your private office with the ONLYOFFICEA Comprehensive Alternative to Office 365 for Business
-
5
Molecular Dynamics Studio
Molecular Dynamics Cell Construction
This is a collection of software modifications created to integrate NanoEngineer-1, PACKMOL and MSI2LMP for the purpose of easily creating molecular dynamics cells. NanoEngineer-1 is a molecular CAD software written by Nanorex and provides the user an easy way to create molecules, while the software modifications allow the user to type atoms using multiple force fields. PACKMOL can generate a random collection of molecules using the molecule templates from NanoEngineer-1 thus providing the initial MD cell. Modifications to PACKMOL allow the atom type data to be passed through to the MSI2LMP software. MSI2LMP creates a LAMMPS input file based on class I or class II force fields. MSI2LMP was modified to use numerically coded force field data generated by NanoEngineer-1. The MMP file format was extended and integrated into all three software applications. http://www.nanoengineer-1.net http://www.ime.unicamp.br/~martinez/packmol/ http://lammps.sandia.gov/ -
6
ERmod
Approximate solvation free energy calculator
ERmod (Energy Representation Module) is a program to calculate the solvation free energy based on the energy representation method (J. Chem. Phys. 113, 6070 (2000)). The program allows users to calculate the solvation free energy to arbitrary solvents, including inhomogeneous systems, and can run in cooperation with state-of-art molecular simulation software, such as LAMMPS, GROMACS and/or AMBER. -
7
The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.
-
8
relax
Molecular dynamics by NMR data analysis
The software package 'relax' is designed for the study of molecular dynamics through the analysis of experimental NMR data. Organic molecules, proteins, RNA, DNA, sugars, and other biomolecules are all supported. It supports exponential curve fitting for the calculation of the R1 and R2 relaxation rates, calculation of the NOE, reduced spectral density mapping, the Lipari and Szabo model-free analysis, study of domain motions via the N-state model and frame order dynamics theories using anisotropic NMR parameters such as RDCs and PCSs, the investigation of stereochemistry in dynamic ensembles, and the analysis of relaxation dispersion data. -
9
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. -
Resco toolkit for building mobile appsDeploying mobile apps with Resco takes days, not months—all without writing a single line of code. Workers can download the Resco app from AppStore, Google Play, or Windows Store, log into your company environment, and instantly use the app you have published on any device.
-
10
KimBlast
Blast+ the easy way
KimBlast GUI formats and indexes Fasta databases for Blast, performs Blast searches and analyzes results. Python 3.x version. For more information, you can have a look at the README.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/kimblast3/code/ci/default/tree/README.md -
11
PyMOlyze is a graphical program to analyze the results of quantum chemistry (HF/DFT) calculations. Features include various population analyses, fragment analysis, monitoring structures during an optimization, and a simple, but powerful, XYZ editor.
-
12
NanoCap
Carbon Fullerene and Capped Nanotube Generator
NanoCap is a generic application for the construction of low energy fullerene and capped nanotube structures. It provides an ideal tool to accompany the study of finite carbon molecules using computer simulation. The implementation involves a standalone application which includes a GUI and allows for dynamic visual inspection through 3D rendering. In addition, the NanoCap core libraries can be used in custom Python scripts that enabled the user to produce structures in bulk or to include the structure generation routines into pre-existing code. -
13
PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
-
14
CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and analyzing molecular simulations, in particular of systems of biological relevance. It focuses on a wide availability of algorithms for (advanced) sampling and is capable of combining Monte Carlo and molecular dynamics in seamless fashion. CAMPARI offers the user a very high level of control over all implemented features. For more information and features, please refer to the project's homepage at http://campari.sourceforge.net/V5 -
15
Larch: Data Analysis for X-ray Spectra
Data Processing and Analysis for X-ray Spectroscopy and More
Larch is a scientific data processing language that is designed to be easy to use for novices and complete enough for advanced data processing and analysis. Larch provides a wide range of functionality for dealing with arrays of scientific data, and basic tools to make it easy to use and organize complex data. Larch has been primarily developed for dealing with x-ray spectroscopic and scattering data, especially the kind of data collected at modern synchrotrons and x-ray sources. Larch is written in Python and relies heavily on the standard tools for scientific computing with Python (numpy, scipy, matplotlib, and h5py). -
16
ProtPOS
Prediction of PROTtein Preferred Orientation on a Surface
ProtPOS is a self-contained, lightweight, and easy-to-use software package for predicting the preferred orientation of protein on a given surface upon initial adsorption. It searches quickly for the low energy protein poses in all translational and rotational degrees of freedom of the protein with respect to the surface using particle swarm optimization. Each successful run returns the lowest energy orientation of the protein on the surface in PDB format, which is readily used for MD simulations. ProtPOS is implemented in Python, making use of the PyMOL library for generating protein conformations and calling GROMACS externally to calculate protein-surface interaction energies. https://cbbio.online/software/protpos/ -
17
PySpline is a graphical, cross-platform program for processing X-ray absorption spectroscopy (XAS) and Extended X-ray absorption fine structure (EXAFS) data. It allows processing parameters to be adjusted and observe the effect on R-space data.
-
18
The CCP1GUI
An extensible GUI for computational chemistry codes
The CCP1GUI project aims to develop a free, extensible Graphical User Interface to various computational chemistry codes developed by the worldwide academic community, with an emphasis on ab initio Quantum Chemistry codes. -
19
UniPyRange
Tool to fetch protein/DNA truncation constructs from Uniprot DB
Very simple python script which saves you the pains of counting the amino acids/DNA bases in fasta files from the Uniprot and NCBI RefSeq Database (1, 2). Lets say you want the amino acid sequence of range 128-387 from a 1000 amino acid protein - this script will help you to avoid counting mistakes by just showing you the specified sequence in amino acids and coding DNA base pairs (ideal for amplification primer design) of a specified Uniprot ID. - Requires BioPython (3) and Bioservices Package (4) (1) The UniProt Consortium UniProt: a hub for protein information Nucleic Acids Res. 43: D204-D212 (2015). (2) RefSeq: an update on mammalian reference sequences. Nucleic Acids Res. 2014 Jan 1;42(1):D756-63. (3) Cock PJ et al. Bioinformatics (2009) (4) Cokelaer et al, Bioinformatics (2013) -
20
This project is A Mitochondrial OxydoReduction Simulation System. It consists of two linked projects: a program for displaying and analysing large biomolecular systems (Floral) and a multi-agent simulator for biomolecular oxydoreduction systems (AMORSS).
-
21
APBS
Biomolecular electrostatics software
This software has moved to http://www.poissonboltzmann.org/. -
22
BASILISK is a probabilistic model of the conformational space of amino acid side chains in proteins. Unlike rotamer libraries, BASILISK models the chi angles in continuous space, including the influence of the protein's backbone.
-
23
A collection of bioinformatics-related software created by members of Cancer Research UK (possibly among others).
-
24
Biskit is a python library for structural bioinformatics research. It simplifies the analysis of macromolecular structures, protein complexes, and molecular dynamics trajectories and offers a platform for the rapid integration of external programs. PLEASE NOTE: The Biskit source code as well as any later releases are now hosted on https://github.com/graik/biskit The sourceforge repo is only kept here for reference.
-
25
Cellogica is a cellular logic analysis tool. It incorporates sequential logic and finite state machine to elucidate the relationship between transcription factors and corresponding gene expression.