This chapter offers a concise yet thorough exploration of the computational landscape that has driven advancements in macromolecular modeling and simulation. Beginning with a brief historical overview, it navigates through the evolution of computational methodologies. Introducing the Monte Carlo sampling technique, we elucidate its theoretical foundations, practical applications, and inherent limitations. Subsequently, the chapter delves into molecular docking approaches, investigating the structural compatibility and atomistic interactions governing protein-ligand binding. The chapter then discusses molecular dynamics simulations, offering readers a comprehensive understanding of the theoretical framework. Finally, the chapter briefly explores advanced sampling techniques, specifically umbrella sampling, and metadynamics, which are crucial for capturing rare events and deciphering intricate, multidimensional energy landscapes of macromolecules.