↓ Skip to main content

Activity prediction of substrates in NADH-dependent carbonyl reductase by docking requires catalytic constraints and charge parameterization of catalytic zinc environment

Overview of attention for article published in Perspectives in Drug Discovery and Design, November 2015
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
33 Mendeley
Title
Activity prediction of substrates in NADH-dependent carbonyl reductase by docking requires catalytic constraints and charge parameterization of catalytic zinc environment
Published in
Perspectives in Drug Discovery and Design, November 2015
DOI 10.1007/s10822-015-9878-8
Pubmed ID
Authors

Gaurao V. Dhoke, Christoph Loderer, Mehdi D. Davari, Marion Ansorge-Schumacher, Ulrich Schwaneberg, Marco Bocola

Abstract

Molecular docking of substrates is more challenging compared to inhibitors as the reaction mechanism has to be considered. This becomes more pronounced for zinc-dependent enzymes since the coordination state of the catalytic zinc ion is of greater importance. In order to develop a predictive substrate docking protocol, we have performed molecular docking studies of diketone substrates using the catalytic state of carbonyl reductase 2 from Candida parapsilosis (CPCR2). Different docking protocols using two docking methods (AutoDock Vina and AutoDock4.2) with two different sets of atomic charges (AM1-BCC and HF-RESP) for catalytic zinc environment and substrates as well as two sets of vdW parameters for zinc ion were examined. We have selected the catalytic binding pose of each substrate by applying mechanism based distance criteria. To compare the performance of the docking protocols, the correlation plots for the binding energies of these catalytic poses were obtained against experimental Vmax values of the 11 diketone substrates for CPCR2. The best correlation of 0.73 was achieved with AutoDock4.2 while treating catalytic zinc ion in optimized non-bonded (NBopt) state with +1.01 charge on the zinc ion, compared to 0.36 in non-bonded (+2.00 charge on the zinc ion) state. These results indicate the importance of catalytic constraints and charge parameterization of catalytic zinc environment for the prediction of substrate activity in zinc-dependent enzymes by molecular docking. The developed predictive docking protocol described here is in principle generally applicable for the efficient in silico substrate spectra characterization of zinc-dependent ADH.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 3%
Unknown 32 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 33%
Student > Bachelor 5 15%
Researcher 5 15%
Student > Master 5 15%
Professor 3 9%
Other 2 6%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 39%
Engineering 5 15%
Chemistry 5 15%
Biochemistry, Genetics and Molecular Biology 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 1 3%
Unknown 4 12%
Attention Score in Context

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 08 September 2016.
All research outputs
#22,830,981
of 25,457,858 outputs
Outputs from Perspectives in Drug Discovery and Design
#868
of 949 outputs
Outputs of similar age
#253,827
of 296,623 outputs
Outputs of similar age from Perspectives in Drug Discovery and Design
#10
of 14 outputs
Altmetric has tracked 25,457,858 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 949 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 296,623 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.