As an important method of computer-aided drug design, molecular docking refers to the process in which two or more molecules recognize each other through geometric matching and energy matching. Scientists use it to simulate the geometric structure and intermolecular forces of molecules with the support of multiple disciplines such as computational chemistry. The essence of molecular docking is the process of mutual recognition between two or more molecules, which involves spatial matching and energy matching between molecules.
Figure 1. Flexible molecular docking. (Dolezal, R.; et al. 2015)
In the rigid docking process, the conformation of the molecules participating in the docking does not change, and only the spatial position and posture of the molecules change. We perform rigid docking for molecules with relatively large structures, which are generally used in the preliminary analysis after the model is established.
At Alfa Chemistry, semi-flexible docking is mainly applied in the docking between small molecules and large molecules (enzymes or nucleic acids). In the semi-flexible docking process, the conformation of the receptor is rigid and fixed, and only the conformation of the ligand is allowed to change within a certain range, such as the bond angle and bond length of some non-critical parts. We take into account the predictive ability of the model in the entire docking calculation process. Our teams provide a preliminary design plan for the drug molecule by fixing the conformation of the receptor protein and continuously adjusting the chemical structure of the drug molecule.
In the flexible docking process, the conformation of the ligand and the receptor is allowed to change freely. We apply flexible docking with high-precision molecular conformation to accurately investigate the recognition between molecules.
We have designed a multi-feature integration algorithm which is developed based on an algorithm-based matching and a machine learning containing various descriptors.
Our ligand-based is based on the molecular similarity evaluation between the submitted molecule(s) and those in an active compound database. The database is constituted by multiple reported bioactive molecules with target or mechanism information. We can conduct virtual screening and target prediction based on the two-dimensional and three-dimensional similarity evaluation of molecular structures.
In grid docking, the receptor molecule is divided into grid points, and then different types of atoms are used as probes to scan. We can calculate the binding energy of the probe atoms with the receptor on the grid points using the generated gridmap.
Our teams have designed genetic algorithm combining the semi-flexible docking technology to predict the binding mode of small molecules. Our docking steps are: Determine the bond length and bond angle of the small molecule, then disassemble the small ligand molecule into several rigid fragments, and finally recombine the rigid fragments of the ligand small molecule according to the geometric properties of the receptor surface for conformation search. In terms of energy calculation, we fully consider non-bonding interactions such as electrostatic interaction and van der Waals force.
Alfa Chemistry also provides the fragment growth method to find the best conformation, and selects the best conformation according to the value of the docking free energy. The basic workflow of using fragment growth method for molecular optimization is: First select the core fragment and place it in the correct position of the active site, and then the other parts of the ligand molecule 'grow' on the core structure in turn. A number of optimal ligand and receptor binding forms can be obtained when the ligand growth is over.
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