Introductory Chapter: Molecular Docking—The Transition from the Micro Nature of Small Molecules to the Macro World

1. Introduction

Molecular docking is a frequently employed bioinformatics method that is capable of predicting with great accuracy (when the initial structure preparation is done properly) the conformation of small molecular weight ligands (Latin ligandus, gerundive of ligare “to bind”) within the binding sites of proteins, enzymes, RNA or DNA macromolecular targets [1, 2, 3, 4, 5]. Since the development of its first algorithm in the 1980s, molecular docking has been an indispensable tool in drug discovery, however, following the further recognition of its ability to highly predict intermolecular interactions by researchers, it has also found widespread use in biochemistry, medicinal chemistry, pharmacy, microbiology, genetics, advanced biophysics, and even the textile industry. Although it is not the specific subject of this introductory chapter, the main principle of molecular docking, as software, is based on two main processes: a. conformational search, and, b. determination of the binding energetics. In the conformational search step, the most likely conformation (minimum energy solution) of the ligand on the target receptor is identified by modifying its structural parameters, such as torsional, translational, and rotational degrees of freedom. In the calculation step of the binding energy of the ligand-receptor complex, which is predicted by conformational search, a binding constant (K_d or K_i) and Gibbs free energy value (ΔG°=kcal/mol) are produced using different scoring functions [1, 6, 7, 8, 9, 10, 11].

2. What advantages did molecular docking technique offer us?

In the last two decades, molecular docking has found significant use in the discipline of molecular biology in addition to structure-based drug design (SBDD). For instance, while the molecular docking method predicts the interactions between enzymes and their substrates, quite accurately in terms of binding free energy and conformation [12, 13, 14, 15], it has also proven its ability to calculate the negative functional effects of induced mutations in proteins as well as the effects of naturally occurring point mutations on enzyme-substrate binding [16, 17, 18, 19]. Thus, molecular docking offers a powerful option for investigating the correlation between structure and function. While the utilization of molecular docking in biochemistry is generally aimed at confirming data related to enzyme inhibitory activity, such as experimental dissociation constant (K_d) or half-maximal inhibitory concentration (IC₅₀) [20, 21, 22, 23, 24], in microbiology, it is widely used to theoretically verify the minimum inhibitory concentration (MIC) values of natural herbal extracts or synthetic components targeted against bacterial enzymes [25, 26, 27, 28, 29]. Recently, although molecular docking programs have not been specifically designed to characterize ligand-DNA interactions, the molecular docking method has now been frequently used to predict the binding modes and affinity of small molecules on DNA, especially in genotoxicity studies [30, 31, 32, 33, 34, 35]. Last but not least, the inherent nature of molecular docking, which is based on biochemistry and biophysics, has allowed it to take place even in the COVID-19 pandemic, which has severely affected the world agenda, societies, and the global economy for about 2 years. This method has ultimately become a principle component in bioinformatics-based drug-discovery campaigns against the SARS-CoV-2 virus [36, 37, 38, 39, 40, 41].

3. Molecular docking is in principle closely connected with molecular dynamics simulations

As commonly known, intracellular receptor-ligand interactions are dynamic phenomena by nature, where ions and water molecules in this milieu have undeniable importance during these intermolecular reactions. At the same time, the inherent flexibility of the interacting protein partners and ligands is an important variable that has to be taken into account in docking calculations. Therefore, considering these variables, molecular docking techniques have evolved further over time and new docking algorithms (ex. flexible receptor-flexible ligand docking or solvated docking) have been developed to produce more accurate receptor-ligand poses [42, 43, 44, 45]. However, simulating the movements of all types of atoms around the reaction site is still beyond the limits of the molecular docking technique. In this context, the molecular dynamics simulations have proved to be indispensable molecular interaction simulation methods used as a complement to the molecular docking technique in order to study the receptor-ligand binding dynamics and the time-dependent evolution of the resulting complex. Therefore, the molecular docking technique should be supported by molecular dynamics simulations, regardless of which biological problem it is used to solve.

4. Conclusion

A feature of biological macromolecules or synthetic chemical compounds is that the basic building blocks come together to form larger building blocks, which then come together to form even larger structures, and the process continues in the same way. The structure and function of these macromolecules composed of small monomers are frequently quite different from the building blocks that compose them, and such phenomena are referred as ‘emergence’ if you ask physicists or biologists. Consequently, it is almost impossible to explain the basis of the emergence phenomenon using scientific reductionism. However, molecular docking, which is one of the most powerful supportive tools of scientific reductionism today, can now display atomic interactions (with almost all the details) in intermolecular reactions on a computer screen, which was almost impossible until about 45–50 years ago. Furthermore, with the ever-developing disciplines such as genomics, molecular biology, biochemistry, and genetics, molecular docking has become a more powerful tool today and the scientific disciplines it can directly contribute to are increasing at the same rate. Thus, the importance of scientific reductionism, therefore molecular docking, in imagining the ‘big biological window’ seems likely to continue with increasing importance. In summary, this book is an ultimate reference guide for researchers working in the fields of experimental biology and bioinformatics who would like to understand the principles of the molecular docking technique and integrate it into their research areas, as well as students who are prospective in increasing their knowledge about molecular simulations.