Bioinformatics Algorithms for Molecular Docking: IT and Chemistry Synergy

Abstract

Drug discovery and molecular biology can be advanced through the synergistic combination of bioinformatics techniques and molecular docking. This research attempts to investigate the most recent developments in this multidisciplinary subject, emphasizing enhancing the efficiency and accuracy of predictions. The process entails a thorough literature review and an analysis of significant advancements in search algorithms, machine learning integration, and scoring systems. Notable discoveries include improved search and scoring algorithms powered by machine learning methods that enhance protein flexibility and binding affinity predictions. The report highlights issues like data availability and computational complexity and suggests policy solutions, such as data-sharing programs, computational infrastructure investments, and regulatory guidelines for AI-driven drug discovery. This study highlights the revolutionary potential of bioinformatics docking synergy, opening the door for faster therapeutic advancements in the biomedical sciences and personalized medicine.