Recent Advances and Computational Approaches in Peptide Drug Discovery

Background: Drug design and development is a vast field that requires huge investment along with a long duration for providing approval to suitable drug candidates. With the advancement in the field of genomics, the information about druggable targets is being updated at a fast rate which is helpful in finding a cure for various diseases. Methods: There are certain biochemicals as well as physiological advantages of using peptide-based therapeutics. Additionally, the limitations of peptide-based drugs can be overcome by modulating the properties of peptide molecules through various biomolecular engineering techniques. Recent advances in computational approaches have been helpful in studying the effect of peptide drugs on the biomolecular targets. Receptor - ligand-based molecular docking studies have made it easy to screen compatible inhibitors against a target. Furthermore, there are simulation tools available to evaluate stability of complexes at the molecular level. Machine learning methods have added a new edge by enabling accurate prediction of therapeutic peptides. Results: Peptide-based drugs are expected to take over many popular drugs in the near future due to their bio-safety, lower off-target binding chances and multifunctional properties. Conclusion: This article summarises the latest developments in the field of peptide-based therapeutics related to their usage, tools, and databases.