Computational protein design: Advancing biotechnology through in silico engineering

Currently, computational protein design (CPD) is a disruptive force in biotechnology, changing the paradigm by which proteins are engineered for many applications. In this article, the evolution of CPD has been tracked from its initial forays in the late 1990s to the current advanced and sophisticated domain that it now occupies as one driven by artificial intelligence (AI). It highlights recent advancements that have extended its scope and into which broader elements including protein backbone modeling, energy functions, sampling algorithms, and techniques for sequence optimization were placed. Computer-aided protein design has thus become increasingly accurate and efficient through machine learning, quantum mechanics, and high-throughput virtual screening. In biotechnology, CPD finds applications in developing innovative therapeutics, industrial enzymes, and synthetic biomaterials. Such remarkable successes aside, however, CPD has various challenges, such as energy function, structural predictions, and computational resource requirements. Future predictions in areas such as programmable cellular systems and self-assembling protein-based materials could establish new avenues for growth. Finally, the review points out the need for multidisciplinarity and ethical considerations as well in utilizing CPD to reach its full potential for solving global issues of health, energy, and environmental sustainability. Having moved in that direction, CPD promises to open new avenues of biotechnological development that will enable the creation of proteins with functions and properties never before possible.