Molecular Docking: State-of-the-Art Scoring Functions and Search Algorithms

This study addresses the technique of molecular docking in drug design, emphasizing the importance of advanced scoring functions and search algorithms. It explores the generation of detailed models involving protein targets and ligand molecules and the evaluation of multiple ligand conformations to identify favorable molecular interactions. Additionally, it underscores the prediction of the ligand’s most stable and energetically favorable conformation to interact with the target protein. Molecular docking plays a fundamental role in the early stages of drug discovery and development, assisting in selecting promising drug candidates and estimating the affinity between candidate molecules and target proteins. The key contributions of this chapter include the exploration of the importance of molecular docking in drug design and the analysis of advanced scoring functions and search algorithms. These topics are essential components for successful molecular docking. In addition, this chapter will discuss the relevance of result validation and the need for accuracy in the predictions based on docking simulations. Furthermore, it evaluates the challenges faced in molecular docking and reflects on using machine learning techniques in this context. It provides insights into the interaction between molecules and target proteins, which is essential for understanding the mechanisms of action of bioactive substances. It also emphasizes the acceleration in drug discovery and design, resource management, and the enhancement of understanding of molecular interactions as significant outcomes. These contributions underscore the importance of molecular docking as a fundamental tool in pharmaceutical research and drug development.