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This data set comprises 175,000 random compounds from ChemDB [29].
Histogram analysis of the GDB13 set (1 million random compounds) as downloaded from the website.
City block distances were calculated for 1788 ligands of CHRM1 with respect to random compounds from ZINC database.
The DUD-E dataset [45, 46] was used as a source for the selection of 1000 random compounds.
Inclusion of inactive compounds from PubChem better mimics chemogenomics datasets available in the pharmaceutical industry, and it has been shown that inclusion of true inactive compounds results in better models than using random compounds as inactive compounds [15].
Even with multiple mechanisms leading to toxicity, each of which coming with a different pharmacophore, the true actives are expected to be more like each other than random compounds and cross prediction should be easier.
Similar(46)
However, the magnitude of this increase was comparable to those for the random compound pairs, meaning that employing multiple conformers per compound does not increase the separation between the NN-pairs and random compound pairs on average.
A list of 10,000 CIDs, used for construction of the 3-D similarity score distributions for the random compound pairs.
This idea is consistent with the small difference in 3-D scoresrity scores between the NN-pairs and random compound-compound pairs, as depicted in Figure 15.
In each case, three to four times more hits were obtained from the focused compound set than from the random compound set.
A docking-based VS, as explained in the Methods section, was performed using both the kinase-focused compound set and the random compound set.
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