Source: Authors
After organizing the molecular docking and ADMET data into a table, it was necessary to normalize the values in order to then compare the results of the compounds holistically. Thus, the data were standardized on a scale from 0 to 1, with 0 being the worst performance and 1 being the best performance of the data set. For this, Min-Max normalization was performed. When the indicator indicated a high value as a good result, the following formula was used:
This equation uses the minimum and maximum values of the sample. Thus, when the best result is a high value, the highest value among the samples receives a score of 1, while the lowest value among the tests receives a score of 0. The other results receive a score proportional to these limits. However, when the best result is a low value, it is necessary to adapt this formula:
Thus, in the adapted formula, the lowest value, which is the best result, receives the normalized score of 1. Furthermore, in the logP and logD7.4 indicators, the value does not matter as long as it is within the established limit, which is, in this case, greater than 1 and less than 3. Therefore, all compounds that had a value within the limit in these indicators received the score of 1, while the others received the normalized score of 0. Therefore, with the data organized, it is possible to formulate a new table.
Source: Authors
Weights were applied to these data to highlight the importance of indicators related to the pharmaceutical viability of the compounds, such as toxicity and inhibitory potency in relation to the object of study (exotoxin A). In this way, it is possible to calculate a final score for each compound corresponding to its therapeutic potential. The maximum sum is 100.
Source: Authors
Thus, it is possible to create a graph showing the final performance of the compounds:
Source: Authors
Therefore, it is clear that Sample 4 was the compound with the best performance. Therefore, with these indicators, this sample has the best therapeutic potential for drug development. With the second highest score, Sample 12 is also promising, with a score slightly higher than that of Sample 11. Additionally, the fourth highest score is that of the control group, PJ34. In addition, the worst score is that of Sample 6, which did not have a good docking result when compared to the other compounds. Finally, Sample 3 also did not perform well, since it did not have adequate physicochemical characteristics for a drug.
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