| Title |
DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina
|
|---|---|
| Published in |
Perspectives in Drug Discovery and Design, January 2017
|
| DOI | 10.1007/s10822-016-0006-1 |
| Pubmed ID | |
| Authors |
Elena Di Muzio, Daniele Toti, Fabio Polticelli |
| Abstract |
Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 141 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 18 | 13% |
| Student > Bachelor | 16 | 11% |
| Student > Ph. D. Student | 15 | 10% |
| Researcher | 13 | 9% |
| Professor | 10 | 7% |
| Other | 14 | 10% |
| Unknown | 57 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 29 | 20% |
| Chemistry | 21 | 15% |
| Agricultural and Biological Sciences | 10 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 6% |
| Computer Science | 2 | 1% |
| Other | 14 | 10% |
| Unknown | 59 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 January 2017.
All research outputs
#20,723,696
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#817
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Outputs of similar age
#320,631
of 422,076 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#8
of 8 outputs
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