Provide a valid 3D structure to initialize the conformational search.Set the proper protonation and tautomeric state to the molecules.Regardless of the format of the molecules or the differences between docking algorithms, ligand preparation must achieve at least the following objectives: Users, however, can use any known chemical format in their molecules thanks to the use of PyBel and RDKit. The cell below depicts one of the simplest approaches to using molecules from SMILES codes. ZINC15, PubChem, DrugBank, etc) and diverse formats (i.e. The ligand molecules in Virtual Screening protocols could come from a variety of sources (i.e. At this point, we can make use ofca protein structure from Jupyter Dock's _ fix_protein()_ function or implementing LePro (for more information, see the 2.1 section of the Molecular Docking notebook). Receptor preparation ¶ĭespite the fact that Smina is a modified version of AutoDock Vina, the input file for a receptor in Smina can be either a PDBQT file or a PDB file with explicit hydrogens in all residues. As a result, the user can use such a tool by adding the necessary cells or replacing the current docking engine. However, the executable files for qvina and qvina-w are available in the Jupyter Dock repo's bin directory. Info: The following cell contains an example of using Smina to run the current docking example. Smina is maintained by David Koes at the University of Pittsburgh and is not directly affiliated with the AutoDock project. Smina is a fork of AutoDock Vina that is customized to better support scoring function development and high-performance energy minimization. Jupyter Dock can run such binaries in a notebook, giving users more options. Despite the presence of Python bindings in AutoDock Vina 1.2.0, other tools that incorporate AutoDock Vina allow for cool features such as custom score functions (smina), fast execution (qvina), and the use of wider boxes (qvina-w).