Search Results for "docking protein"
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Showing 10 open source projects for "docking protein"
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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 -... -
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MOLS 2.0 is a free and open-source software package for peptide modeling and protein-ligand docking. Authors: Dr. D. Sam Paul, Dr. S. Nehru Viji, Dr. P. Arun Prasad, Dr. K. Vengadesan, Dr. N. Gautham. If you use MOLS 2.0 for publication, please cite - D. Sam Paul, N. Gautham, MOLS 2.0: software package for peptide modeling and protein–ligand docking, Journal of Molecular Modeling 22 (2016) 1–9. Publications related to MOLS 2.0: 1.
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ADFRsuite
Automated docking software tools from the Sanner lab at Scripps
the ADFRsuite provides a self contain python-based software environment with various tools for automated docking. visit ccsb.scripps.edu/adfr for more info -
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GWOVina 1.0
The Hybrid Grey Wolf Optimization for Protein-Ligand Docking
Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein. Based on the implementation of AutoDock Vina, GWOVina employs grey wolf optimization (GWO) algorithm to speed up the search for optimal ligand poses. Our rigid docking experiments show that GWOVina has enhanced exploration capability leading to significant speedup in the search while maintaining comparable binding pose prediction accuracy to AutoDock Vina. ... -
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PSOVina 2.0
The Hybrid Particle Swarm Optimization for Protein-Ligand Docking
A fast docking tool based on the efficient optimization algorithm of Particle Swarm Intelligence and the framework of AutoDock Vina. Based on the initial PSO implementation, our PSOVina method has undergone several important improvements to enhance the docking accuary and achieve remarkable efficiency as compared to the original AutoDock Vina. https://cbbio.online/software/psovina/index.html -
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irayMol
Molecular visualization
Analyses and Interactive visualizations of the structures, functions and actions of biomolecules including molecular surface computation, and protein-ligand interface and protein-ligand docking where the ligand could a small compound, a nucleic acid, membrane and other proteins, written in C++/Qt/openGL/GLSL with more than 125,000 lines of codes. In addition to Qt, the only external library needed is GSL everything else is coded from the scratch. -
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(NCS) NEQUIM Contact System
Tool for analyze of interactions in ligand-protein complexes
NEQUIM Contact System (NCS) is a system to generate and analyze interaction vectors of protein-ligand complexes. Core features include multiple views of vectors, multiple selection options, cluster analysis and generation of interaction vector model. The input could be from PDB format or from files generated by automatic docking softwares AutoDock/Vina or Surflex. -
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ParallelVSR
ParallelVSR - a pipeline for parallel virtual screening on R platform
...We have integrated Ligand Based Virtual Screening (LBVS) technique which uses ChemmineR - a reliable cheminformatics package on R platform and Structure Based Virtual Screening (SBVS) technique which uses AutoDock Vina - freely available and widely used protein-ligand docking tool. This pipeline has R scripts to perform VS automatically in step-wise manner. To increase the efficiency of VS, we have used data level parallel processing approach using task-pull methodology of Master-Slave communication protocol. -
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OFF-TARGET PIPELINE is a platform intended to carry out a recently introduced chemical systems biology approach for secondary target identification, but may also be useful to other applications in bioinformatics and drug discovery.
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