Overview of ligand preparation

Meeko provides both command line scripts and a Python API. Here, we briefly describe how data flows under the hood, and some of the key methods and data structures. While this information is primarily for those using Meeko from Python, it provides context for users of the command line script mk_prepare_ligand.py. When using this script, the input are SD files (.sdf extension), and the output are PDBQT files.

Use of RDKit

Meeko takes as input an RDKit molecule that has 3D positions and all hydrogens as real atoms, and creates an object called MoleculeSetup that stores all the parameters, such as atom types, partial charges, or rotatable bonds. RDKit checks the valence of atoms, making it difficult to have molecules with incorrect bond orders or formal charges. Adding hydrogens and 3D positions is not performed by Meeko.

Parameterization using SMARTS patterns

Many of the parameters are assigned using SMARTS strings, which are a compact and versatile query language for identifying chemical substructures. This makes it easier to define custom atom types and other parameters. The SMARTS that define the AutoDock parameters are included in Meeko and set as the default, The goal of this feature is to facilitate the implementation of custom docking workflows.

The MoleculePreparation class stores all the configuration required to parameterize a ligand, and contains the methods that take an RDKit molecule as input, and return a parameterized MoleculeSetup. The MoleculePreparation offers several options to control how molecules are parameterized, and most are exposed as command line options in mk_prepare_ligand.py.

Preparing the input for docking

AutoDock-GPU and Vina use the PDBQT format for input molecules. PDBQT files, or strings in Python, are produced from a parameterized instance of MoleculeSetup. The methods to write PDBQT are in the PDBQTWriterLegacy class. PDBQT strings can be passed directly to Vina using its Python API.