The Role of Molecular Docking in Modern Drug Discovery and Development: A Comprehensive Review

Abstract

Molecular docking is an essential computational technique widely used in drug discovery to predict the interaction between small molecules and their protein targets. This review presents a detailed examination of molecular docking, including its historical development and current relevance in pharmaceutical research. It outlines the core principles of molecular docking, differentiating between rigid and flexible docking methods and discussing the critical components such as search algorithms and scoring functions. The review highlights the role of molecular docking in identifying and validating drug targets, supported by case studies demonstrating successful applications. Additionally, it covers the identification and optimization of lead compounds through virtual screening processes. Recent advancements in docking methodologies, such as the integration of machine learning and artificial intelligence, the development of improved scoring functions, and the combination with other computational techniques, are explored. The review also illustrates the application of molecular docking in various therapeutic areas, including oncology, infectious diseases, and neurological disorders, with relevant examples. The challenges faced in molecular docking, such as accuracy, computational demands, and the need for experimental validation, are discussed. Looking forward, the potential of molecular docking in personalized medicine, the impact of quantum computing, and its applications in environmental and agricultural sciences are considered, emphasizing its growing significance across diverse fields.