Directory of computer-aided Drug Design tools. Free open source EA based docking software. Exhaustive search based docking program. An Introduction to Molecular Docking. •Induced Fit Docking –far slower, Glide. Docking Packages •Free –AutoDock. AutoDock Vina. AutoDock Vina is an open-source program for doing molecular docking. It was designed and implemented by Dr. Oleg Trott in the Molecular Graphics Lab.
AutoDock Vina AutoDock Vina is an open-source program for doing. It was designed and implemented by in the Molecular Graphics Lab at The Scripps Research Institute.
The image on the left illustrates the results of flexible docking (green) superimposed on the crystal structures of (a) indinavir, (b) atorvastatin, (c) imatinib, and (d) oseltamivir bound to their respective targets. Publication If you used AutoDock Vina in your work, please cite: Features Accuracy AutoDock Vina significantly improves the average accuracy of the binding mode predictions compared to AutoDock 4, judging by our tests on the training set used in AutoDock 4 development.
Additionally and independently, AutoDock Vina has been against a virtual screening benchmark called the by the, and was found to be 'a strong competitor against the other programs, and at the top of the pack in many cases'. It should be noted that all six of the other docking programs, to which it was compared, are distributed commercially. AutoDock Tools Compatibility For its input and output, Vina uses the same PDBQT molecular structure file format used.
PDBQT files can be generated (interactively or in batch mode) and viewed using. Other files, such as the AutoDock and AutoGrid parameter files (GPF, DPF) and grid map files are not needed. Binding mode prediction accuracy on the test set. 'AutoDock' refers to AutoDock 4, and 'Vina' to AutoDock Vina 1.
Ease of Use Vina's design philosophy is not to require the user to understand its implementation details, tweak obscure search parameters, cluster results or know advanced algebra (quaternions). All that is required is the structures of the molecules being docked and the specification of the search space including the binding site. Calculating grid maps and assigning atom charges is not needed. The usage summary can be printed with ' vina -help'. The summary automatically remains in sync with the possible usage scenarios. Implementation Quality.
By design, the results should not have a statistical bias related to the conformation of the input structure. Attention is paid to checking the syntactic correctness of the input and reporting errors to the user in a lucid manner.
The invariance of the covalent bond lengths is automatically verified in the output structures. Vina avoids imposing artificial restrictions, such as the number of atoms in the input, the number of torsions, the size of the search space, the exhaustiveness of the search, etc. Flexible Side Chains Like in AutoDock 4, some receptor side chains can be chosen to be treated as flexible during docking. Speed AutoDock Vina tends to be faster than AutoDock 4 by orders of magnitude. Multiple CPUs/Cores Additionally, Vina can take advantage of multiple CPUs or CPU cores on your system to significantly shorten its running time. World Community Grid Qualified projects can run AutoDock Vina calculations for free on the massively parallel. Existing projects using AutoDock Vina there include those targeting, and.
Some of these projects average over 50 years worth of computation per day. Average time per receptor-ligand pair on the test set. 'AutoDock' refers to AutoDock 4, and 'Vina' to AutoDock Vina 1. License AutoDock Vina is released under a very permissive Apache license, with few restrictions on commercial or non-commercial use, or on the derivative works.
The text of the license can be found. Video Tutorial Questions, problems or suggestions?
The Advantages of Computational Docking The widespread use of combinatorial chemistry and high-throughput screening (HTS) in the pharmaceutical and biotechnology industries means that large numbers of compounds can now routinely be investigated for biological activity. However, screening large chemical libraries remains an expensive and time-consuming process, with significant rates of both false positives and false negatives. High-speed computational methods can now enrich the fraction of suitable lead candidates in a chemical database, thereby creating the potential to greatly enhance productivity and dramatically reduce drug development costs.
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With an ever increasing number of drug discovery projects having access to high-resolution crystal structures of their targets, high-performance ligand-receptor docking is the clear computational strategy of choice to augment and accelerate structure-based drug design. Complete solution: Glide offers the full range of speed vs. Accuracy options, from the HTVS (high-throughput virtual screening) mode for efficiently enriching million compound libraries, to the SP (standard precision) mode for reliably docking tens to hundreds of thousands of ligand with high accuracy, to the XP (extra precision) mode where further elimination of false positives is accomplished by more extensive sampling and advanced scoring, resulting in even higher enrichment.
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Virtual screening: Glide provides a rational workflow for virtual screening from HTVS to SP to XP, enriching the data at every level such that only an order of magnitude fewer compounds need to be studied at the next higher accuracy level. Accurate binding mode prediction: Glide reliably finds the correct binding modes for a large set of test cases. It outperforms other docking programs in achieving lower RMS deviations from native co-crystallized structures.
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Universal applicability: Glide exhibits excellent docking accuracy and high enrichment across a diverse range of receptor types.