DockoMatic: A Resource for Computational Biology or Chemistry Courses

Structure based rational drug design commonly uses receptor models based on X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy to determine specific interactions between the drug and the receptor. Computational approaches have evolved to perform molecular docking to predict ligand (drug) binding properties, such as ideal geometric arrangements and bonding interactions in silico. Dockomatic provides a graphical user interface (GUI) that facilitates job submission to AutoDock, a docking engine that calculates the energy of binding. The objective of this study is to create a laboratory exercise for use in the chemistry and/or biology curriculum that exemplifies how Dockomatic can be used as a computational resource for structure based drug design. The exercise challenges students to analyze the crystal structure of the 16 amino acid peptide conotoxin TxIA (i.e., the ligand) bound to the AcetylCholine Binding Protein from Aplysia californica (Ac-AChBP). Students will propose amino acid side chain substitutions of TxIA that will enhance binding to the receptor, create the peptide analog using DockoMatic, and perform the molecular docking calculation to compare their result to the rest of the class. Analysis of the molecular docking results will determine intermolecular forces, binding energy, and geometric orientation of the newly prepared analog with the AChBP compared to the TxIA interactions with the AChBP. Students are challenged to identify two side chains in TxIA that will most significantly lead to enhanced binding of the peptide. This exercise is designed for a four hour laboratory period and can be accomplished with access to an internet connected PC