Are computational approaches critically important for solving real-world problems?

Calculation of macromolecule are very challenging. Various computational approaches that are used in such calculations were surveyed in this chapter: molecular dynamics (MD), atomistic models, coarse-grained (CG) models, hybrid/mixed methods, Monte-Carlo methods, Ab initio methods (DFT), “machine learning” methods—QSAR, QSPR, and methods based on quantum crystallography (QCr)—and kernel energy method (KEM). These methods were used in the past 30 years to solve real-world problems studies. A short survey of these researches is given. In silico methods were used to calculate physical and chemical properties in very good agreement with experimental results. These methods were used to modify materials and even design new materials that were tailored according to requested features. Computational biochemistry paved a new way to understand the essential features of life. These all researches demonstrate that computational approaches are critically important for solving real-world problems.