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Figure 7 Shows false positive compounds of the test sets.
For the developmental toxicity model two compounds of the test set had descriptors out of the range of descriptors used for the training set.
This model predicted all the ten compounds of the test set within 0.56 log units of the actual pIC50 values; and can be used to guide the rational design of more potent novel 3-keto salicylic acid integrase inhibitors.
For all compounds of the test library, essential chemical and pharmacological information was compiled (Fig. S1, S2; Fig. 3).
External validation was done by predicting the activities of the compounds of the test set which were not used for model generation.
Use of the quantitative pharmacophore modeling is not only to predict the activity of the training set compounds properly, but also to validate whether the model is capable of predicting the activity of external compounds of the test set series.
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The mean total phenolics compounds of the tested honeys was 243.01± 74.91 mg gallic acid/kg.
Correlation coefficient between phenolic and flavonoid compounds of the tested extracts and free radical scavenging activity were r = 0.921 and r = 0.907, respectively.
Conversely, observing a neutral loss of 35.977 u was found at 92.2% specificity for the presence of a chlorine atom in the 2 036 test compounds of the tested NIST11 MS/MS spectra, indicating a neutral loss of HCl.
Three compounds of the 13 tested exhibit anti-proliferative effects in HeLa cancer cells.
Compound 6q showed the most potent activity of all of the compounds against all of the test multidrug-resistant clinical isolates tested.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com