Abstract
The rapid advancements in computational methods have revolutionized drug discovery and development. These methods, ranging from molecular modelling to machine learning algorithms, have drastically increased in number and sophistication. However, a comprehensive understanding of these diverse approaches is essential for researchers aiming to make significant contributions to this evolving field. This review aims to provide a detailed overview of the most prominent computational methods currently used in drug discovery. It will analyze their underlying principles, discuss their applications, and highlight their potential for future advancements in the field. Through this examination, we aim to equip researchers with the necessary insights to navigate and contribute to the rapidly expanding landscape of computational drug discovery.