I am Sai Pavithra doing research in Biotechnology related to herbal medicine. I did molecular docking using Autodoc Vina software. I am preparing for my viva voce. Kindly can anyone please tell me how should I present my molecular docking data for viva.
First, you can present the protein-ligand binding affinity as kcal/mol. The lower binding energy indicate that docking result of ligand and protein is more stable meaning that ligand has better binding affinity. You can screen various components of your interested nature products, then ranking them by the binding affinities. Secondly, choosing the top ranking compounds for protein-ligand interaction analysis.
Please read this paper. They have performed molecular docking and showed their results in different ways. You may get an idea.
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As Yi-Fong Chen has answered, you can rank them by binding affinities. Further, for visual representation you can show the residues which are directly interacting with your ligand using Pymol as given in this paper.
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Hi K. Sai Pavithra ,
In the first place, I would present all the ligands you have explored and show the chemical differences between them, followed by a presentation of your target (if this is not so relevant, you can just comment it); additionally, you could also include a brief remark of the methodology you used.
Then, I would include a table with the Z-score values provided by Vina, and also some pictures of the most relevant poses brought. Here, you can also explain the differences and the main interactions you found and considered as relevant and interesting for your binding mode. Furthermore, you can build a picture by overlapping different poses and explain slightly the possible binding mode of the ligands.
Finally, the presentation could end by showing final remarks as a summary, and some conclusions about what you obtained, personal thoughts about it or also you may propose questions that lead to the active participation of the public (maybe they can help you to largely explore the way you took in your research).
Bests!
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