Automating Protein Engineering: Applications of Computational Methods in Protein Design

The availability of new pharmaceuticals discovered through traditional means is becoming increasingly limited with the passage of time due to the drawbacks of conventional methods. Established organic synthesis techniques for drug development are hindered by long development time, high cost and a high probability of unfavorable side effects in human subjects. Compounding the problem, mounting costs of research and development due to an increasingly saturated repository of pharmaceuticals that have been discovered through remunerative means is making the consideration of investing billions of dollars into researching new compounds less lucrative by the day, even for federal and commercial entities capable of doing so. Many of these concerns are currently being addressed through the application of protein engineering, a rapidly emerging field that concerns the design and utilization of nucleic acid sequences for the purpose of achieving some desired function such as catalysis or cell signaling. Enzymatic catalysis is an exceptionally potent method of organic synthesis due to its high throughput and efficiency, as exemplified by its central role in the maintenance of life. However, protein engineering faces similar challenges to traditional methods, as enzymes are highly complex and require a large investment of financial resources and time to design top-down. To solve this problem, computational methods are increasingly being employed to assist in the design and testing of novel amino acid sequences, as well as the modification of existing ones. Herein we discuss computational methods currently being used in protein design, as well as potential future implementations and improvements in these methods.