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Molecular docking is a modeling technique that is used to predict how two or more molecular structures fit together. The protein or nucleic acid can form a supramolecular complex with small molecules, which plays a major role in the dynamics of the protein. Moreover, the ability to form complexes may enhance or inhibit the biological function of the protein. Molecular docking can describe the behavior of small molecules in the binding pockets of target proteins. The technique aims to determine the proper positions of ligands in the binding pocket of protein and to predict their affinity. Because of its relatively low-cost implications and apparent ease of use, molecular docking has emerged as a key technique in the drug development toolkit, enjoying rising popularity among academic groups. Creative Biolabs has established the AI-assisted bioinformatics analysis platform to support our customers in molecular docking, molecular dynamics simulation, virtual screening, and Quantitative structural activity relationship (QSAR) analysis.
Fig.1 Elements in molecular docking. (Hernndez, et al., 2013)
Based on the types of ligands, there are three molecular docking model as below.
The crucial process in enzymatic processes is ligand binding. Therefore, a rational approach to drug design may be based on a thorough understanding of interactions between small compounds and proteins. In order to create compounds that treat a wide variety of significant illnesses, such as malignancies or cardiovascular disorders, molecular docking was often taken into consideration. Finding the best binding between a small molecule (ligand) and a protein is the goal of protein-ligand docking. The purpose of protein-ligand docking is to find the optimal binding between a small molecule and a protein. This method is often used in the search for new drug candidates throughout the drug research and development process. The docking process may be divided into three main parts: firstly, identifying a target protein that is usually linked to disease and is known to bind small molecules. Next, assembling a possible small molecules library that binds to a protein and may interfere with protein function. Finally, to find the optimal binding position and energy, every small molecule is then docked into the protein. The system must be carefully selected and prepared before doing any calculations.
Numerous crucial biological activities, such as DNA replication, RNA transcription, RNA splicing, nucleic acid breakdown, and protein synthesis, depend on interactions between proteins and nucleic acids. The interactions are implicated in a number of diseases, such as neurological disorders and cancer, etc. Therefore, it is important to know the structural details and interactions of protein-nucleic acid complexes. The traditional experimental approach is based on high-resolution methods to analyze the complex structure of protein-nucleic acid, which is a tedious and difficult process. In order to understand protein-nucleic acid interactions, computational tools are used to complement the experimental methods. By building theoretical models of the complex structures at the atomic level, in silico docking of proteins with nucleic acids can provide enough details to establish a working hypothesis and guide subsequent experimental analysis to identify key amino acid or nucleotide residues.
Protein-protein interactions are crucial in various aspects of cellular functions, such as signal transduction, cell communication, metabolic control, and gene regulation. Knowing the structural details of a protein-protein interaction helps to understand the interaction mechanism and the function of the proteins involved. Currently, the crystal structure of protein complexes is more difficult to obtain. Therefore, it requires fast and robust computational methods to reliably predict the structure of the protein-protein complexes. Protein-protein docking is a computational tool for predicting protein-protein interactions. By using state-of-the-art docking software tools, Creative Biolabs can find the relative transformation and conformation of two proteins that result in a stable complex. Our platform searches all potential binding modes in the translational and rotational space between the two proteins using computational docking techniques, and then it scores each pose according to its energy.
Fig.2 Protein-protein Docking. (Hashmi & Shehu, 2013)
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