Table 3. 2HF in silico ADMET predictions.
| Model | Result | Probability |
|---|---|---|
| Absorption | ||
| BBB | + | 90.44% |
| HIA | + | 100% |
| Caco-2 | + | 79.59% |
| P-glycoprotein substrate | NS | 57.38% |
| P-glycoprotein inhibitor | NI | 81.82% |
| Metabolism | ||
| CYP450 2C9 Substrate | NS | 73.86% |
| CYP450 2D6 Substrate | NS | 88.10% |
| CYP450 3A4 Substrate | NS | 64.87% |
| CYP450 1A2 Inhibitor | I | 79.45% |
| CYP450 2C9 Inhibitor | I | 90.58% |
| CYP450 2D6 Inhibitor | NI | 85.61% |
| CYP450 2C19 Inhibitor | I | 90.03% |
| CYP450 3A4 Inhibitor | NI | 80.55% |
| Toxicity | ||
| AMES Toxicity | N | 83.11% |
| Carcinogens | N | 92.06% |
| Lipinski’s rule of 5 | ||
| HBA (≤10) | 3 | 0 violations |
| HBD (≤5) | 1 | |
| miLogP (≤5) | 3.123 | |
| n-ROTB (≤10) | 1 | |
| MW (≤500) | 240.25 | |
BBB—blood-brain barrier; HIA—human intestinal absorption; + positive;—negative; I—inhibitor; NI—noninhibitor; NS—non-substrate; n-ROTB—number of rotatable bonds; HBA—number of hydrogen bond acceptors; HBD—number of hydrogen bond donors; milogP—logarithm of compound partition coefficient between n-octanol and water; MW—molecular weight.