Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

• Published in: Frontiers in molecular biosciences 2021-05, Vol.8, p.681617-681617
• Main Authors: Perez, Juan J., Perez, Roman A., Perez, Alberto
• Format: Article
• Language: English
• Subjects: computational methods; epitopes; linear peptide motifs; Molecular Biosciences; p53; protein-protein interactions; tissue engineering
• ISSN: 2296-889X; 2296-889X
• DOI: 10.3389/fmolb.2021.681617

Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.