Computational Applications in the Drug Discovery and Development Processes

The traditional drug discovery and development process has been shown to be not only time-consuming and risky, but also expensive. The identification of disease-related targets, the identification and optimization of novel leads, and drug development are the three critical steps in modern drug discovery. Approaches such as genomics, proteomics, molecular biology, cell biology, structure biology, computational biology, and bioinformatics are commonly used to identify diseaserelated targets. Here, we appraised the significance of computational applications in modern drug discovery and development. It was revealed that the adoption of novel computational technologies has proven to be efficient in identifying drug targets and drug candidates against degenerative diseases such as diabetes, cancer and bacterial infections, and the concept holds significant promise for a future breakthrough in drugs discovery, design and development. The challenges involved with computational applications in drug discovery are basically those of precision and accuracy in handler and software limitations. However, future breakthroughs and effective outcomes depend on the combination of advanced models with vast experience in the field of drug discovery and an understanding of the limitations of the existing computational tools.