| Title |
Ultrafast protein structure-based virtual screening with Panther
|
|---|---|
| Published in |
Perspectives in Drug Discovery and Design, September 2015
|
| DOI | 10.1007/s10822-015-9870-3 |
| Pubmed ID | |
| Authors |
Sanna P. Niinivehmas, Kari Salokas, Sakari Lätti, Hannu Raunio, Olli T. Pentikäinen |
| Abstract |
Molecular docking is by far the most common method used in protein structure-based virtual screening. This paper presents Panther, a novel ultrafast multipurpose docking tool. In Panther, a simple shape-electrostatic model of the ligand-binding area of the protein is created by utilizing the protein crystal structure. The features of the possible ligands are then compared to the model by using a similarity search algorithm. On average, one ligand can be processed in a few minutes by using classical docking methods, whereas using Panther processing takes <1 s. The presented Panther protocol can be used in several applications, such as speeding up the early phases of drug discovery projects, reducing the number of failures in the clinical phase of the drug development process, and estimating the environmental toxicity of chemicals. Panther-code is available in our web pages ( http://www.jyu.fi/panther ) free of charge after registration. |
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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 2% |
| Denmark | 1 | 2% |
| Unknown | 52 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 28% |
| Student > Ph. D. Student | 9 | 17% |
| Student > Master | 6 | 11% |
| Student > Bachelor | 5 | 9% |
| Student > Doctoral Student | 4 | 7% |
| Other | 8 | 15% |
| Unknown | 7 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 24% |
| Chemistry | 13 | 24% |
| Pharmacology, Toxicology and Pharmaceutical Science | 7 | 13% |
| Agricultural and Biological Sciences | 6 | 11% |
| Computer Science | 5 | 9% |
| Other | 2 | 4% |
| Unknown | 8 | 15% |
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 29 September 2015.
All research outputs
#20,723,600
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#817
of 949 outputs
Outputs of similar age
#209,928
of 286,425 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#8
of 12 outputs
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