| Title |
Prediction of cyclin-dependent kinase 2 inhibitor potency using the fragment molecular orbital method
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2011
|
| DOI | 10.1186/1758-2946-3-2 |
| Pubmed ID | |
| Authors |
Michael P Mazanetz, Osamu Ichihara, Richard J Law, Mark Whittaker |
| Abstract |
The reliable and robust estimation of ligand binding affinity continues to be a challenge in drug design. Many current methods rely on molecular mechanics (MM) calculations which do not fully explain complex molecular interactions. Full quantum mechanical (QM) computation of the electronic state of protein-ligand complexes has recently become possible by the latest advances in the development of linear-scaling QM methods such as the ab initio fragment molecular orbital (FMO) method. This approximate molecular orbital method is sufficiently fast that it can be incorporated into the development cycle during structure-based drug design for the reliable estimation of ligand binding affinity. Additionally, the FMO method can be combined with approximations for entropy and solvation to make it applicable for binding affinity prediction for a broad range of target and chemotypes. |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 5% |
| Germany | 2 | 2% |
| United Kingdom | 2 | 2% |
| Japan | 2 | 2% |
| Brazil | 1 | 1% |
| Unknown | 70 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 32% |
| Student > Ph. D. Student | 16 | 20% |
| Student > Master | 8 | 10% |
| Other | 5 | 6% |
| Professor > Associate Professor | 4 | 5% |
| Other | 10 | 12% |
| Unknown | 12 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 40 | 49% |
| Agricultural and Biological Sciences | 9 | 11% |
| Computer Science | 5 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 5% |
| Medicine and Dentistry | 4 | 5% |
| Other | 5 | 6% |
| Unknown | 14 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 08 March 2012.
All research outputs
#2,570,236
of 22,707,247 outputs
Outputs from Journal of Cheminformatics
#253
of 828 outputs
Outputs of similar age
#15,969
of 180,914 outputs
Outputs of similar age from Journal of Cheminformatics
#3
of 6 outputs
Altmetric has tracked 22,707,247 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 828 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 180,914 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.