I am docking multiple ligands (new designed ligand) against my protein using Autodock Vina in Chimera. The results displayed in this program are somewhat strange, because in some cases the ligands with no hydrogen bond or fewer bonds has the most negative Score than the ligand with more hydrogen bonds!!? Please look at the picture to get my mean(The best model in ligand with 2 hydrogen bonds has a score -8.3, While the best model in ligand with one or zero hydrogen bond has score -8.7 and -10.1 respectively!).
I understand that checking with other software or tools like PyMOL or PDBSUM will better help to analyze the possible interactions, however since I have several ligands with almost similar score and interaction network or equal hydrogen bond numbers, I am curious to now how to pick the best one (based on the in silico analysis) among them. If any body has suggestion for this I will appreciated it.
I cannot really read texts in the screenshot. In Vina's case, lower score (affinity in kJ) means higher affinity. But comparing those scores between different compounds should be done carefully when deriving some ideas.
You should choose the pose with the highest score (-10.1) since it has a significant score difference with the second pose.
Docking algorithms like Autodock Vina evaluate multiple factors when calculating the docking score, including van der Waals interactions, electrostatic interactions, and hydrogen bonding. While the number of hydrogen bonds can be an important indicator of ligand binding, it's not the sole determinant of the docking score. Other factors such as the strength and geometry of the hydrogen bonds, as well as non-polar interactions, can also contribute to the overall score.
This article should be helpful
Article Software News and Update AutoDock Vina: Improving the speed ...
- Badges
- Science method