In the field of molecular modeling, molecular docking is a method for predicting the preferred orientation of one molecule relative to a second molecule when the ligand and target are brought together to form a stable complex. Knowledge of the preferred orientation can then be used to predict the strength of association or binding affinity between two molecules, which is usually achieved through various scoring functions. The association between biologically related molecules, such as proteins, peptides, nucleic acids, carbohydrates, and lipids, plays a central role in signal transduction. Furthermore, the relative orientation between the two interaction partners may influence the type of signal generated (e.g., agonist vs. antagonist). Therefore, molecular docking is extremely useful for predicting the intensity and type of signals.
Molecular docking is one of the most commonly used methods in structure-based drug design because it can predict the binding conformations of small molecule ligands to suitable target binding sites.
Molecular docking can be viewed as a "lock and key" problem, finding the "key" with the correct relative orientation to open the "lock". Here, the protein can be thought of as the "lock" and the ligand as the "key". Molecular docking is defined as an optimization problem to describe the best relative orientation of ligands binding to a specific protein. However, because both the ligand and the protein are flexible, a more appropriate analogy is to use the word "glove and hand". During the docking process, the ligand and protein adjust their conformations to achieve an overall "best fit", and the result of this conformational adjustment is called "induced adaptation".
Two methods are particularly popular in the molecular docking community. One approach uses matching techniques to describe proteins and ligands as complementary surfaces. The second method simulates the actual docking process and calculates the pairwise interaction energies between ligand and protein. Both methods do have significant advantages, but they also have certain limitations.
The geometric matching/shape complementarity approach describes the protein and ligand as a set of features that enable docking. These features may include molecular surface/complementary surface descriptions. In this case, the molecular surface of the receptor can be described by its solvent accessible surface area, while the molecular surface of the ligand can be described by its matching surface description. The complementarity between these two surfaces is not limited to shape matching description but may also help in finding complementary poses for docking of target and ligand molecules.
The simulation of the docking process is more complicated. In this method, a certain physical distance is maintained between the protein and the ligand until the ligand finds the best position to enter the active site of the protein after several "movements". These movements include rigid-body changes such as translations and rotations, as well as changes within the ligand structure, including rotations of torsional angles. Each move produces a change in total energy, so after each move, the total energy of the system needs to be calculated.
The obvious advantage of simulation is that it easily incorporates ligand flexibility, whereas shape complementarity techniques must use clever methods to incorporate this flexibility.
The interdependence between the samples and the scoring functions for molecular docking will affect the ability of docking techniques in predicting feasible poses or binding affinities of new compounds. Therefore, docking protocols often need to be evaluated (when experimental data are available) to determine their predictive power. The accuracy of docking is usually assessed by calculating the match scores or by obtaining information about enhancers from known binding molecules.
The development of many computational methods will make the process of constructing molecular docking more reliable and accurate.
So, as technology advances and computing power increases, how will molecular docking technology continue to improve our understanding and application of drug design in the future?