Editorial
, Volume: 15( 4)Molecular Docking: Principles, Applications, and Significance in Drug Discovery
Molecular docking is a computational technique widely used in drug discovery to predict the interaction between small molecules and target biomacromolecules such as proteins and nucleic acids. By simulating binding orientations and estimating binding affinities, docking helps identify promising lead compounds, understand structure–activity relationships, and guide rational drug design. Advances in algorithms, scoring functions, and computational power have significantly improved the accuracy of docking predictions. Molecular docking serves as a cost-effective and time-saving approach compared to traditional experimental methods. This article provides an overview of the principles, workflow, tools, and applications of molecular docking, emphasizing its growing importance in modern pharmaceutical research. functions Keywords: Molecular docking, computational drug design, binding affinity, protein–ligand interactions, virtual screening, scoring
Molecular docking is a fundamental computational tool used to predict how small molecules, such as potential drug candidates, interact with biological targets. It plays a vital role in structure-based drug design by estimating the preferred orientation and binding strength of a ligand when it interacts with a receptor. The core concept of molecular docking is based on the complementary fit between the ligand and the binding site of the target, which resembles a “lock-and-key” or “induced-fit” mechanism. With the rapid expansion of structural biology databases, particularly the Protein Data Bank (PDB), molecular docking has become more accessible and widely used in pharmaceutical and biomedical research. Docking involves two primary components: sampling algorithms that explore various ligand conformations and orientations, and scoring functions that evaluate the binding affinity of each predicted pose. Common docking tools such as AutoDock, AutoDock Vina, Glide, GOLD, and MOE utilize Citation: Chen Wei. Molecular Docking: Principles, Applications, and Significance in Drug Discovery .ActaChimPharIndica. 15(3):3.2. 1 © 2025 Trade Science Inc. www.tsijournals.com | December-2025 different algorithms to balance computational efficiency with prediction accuracy. These tools allow researchers to screen large chemical libraries, prioritize compounds for synthesis or testing, and identify new scaffolds for drug development. One of the major advantages of molecular docking is its ability to significantly reduce the time and cost associated with experimental drug discovery. By predicting potential drug–target interactions in silico, researchers can eliminate weak candidates early in the process. Docking also supports mechanistic studies by revealing key interactions such as hydrogen bonds, hydrophobic contacts, electrostatic interactions, and π–π stacking. These insights help in optimizing molecular structures to enhance potency, selectivity, and pharmacokinetic properties. Beyond drug discovery, molecular docking is applied in fields such as enzyme engineering, protein protein interaction analysis, and biotechnology. Integration with molecular dynamics simulations, pharmacophore modeling, and machine learning techniques has further improved predictive capabilities. Despite its wide utility, limitations such as scoring inaccuracies and protein flexibility challenges highlight the need for continued methodological improvements. As computational power advances and algorithms evolve, molecular docking will continue to grow as a valuable tool in rational drug design and molecular research. Conclusion Molecular docking has become an indispensable technique in modern drug discovery, offering rapid, cost-effective predictions of protein–ligand interactions. Its ability to screen vast numbers of compounds, provide structural insights, and guide medicinal chemistry optimization makes it a powerful tool for pharmaceutical research. Although challenges remain, ongoing advancements in algorithms, scoring functions, and computational integration continue to enhance its accuracy and reliability. As structural biology and computational technologies progress, molecular docking will remain at the forefront of rational drug design and molecular innovation.
