The recent focus on protein-protein interaction networks has increasingly been shifted towards the disruption of
protein complexes, which either are mediated by the binding of a globular domain in one protein to a short peptide stretch
in another, or involve flat, large, and hydrophobic interfaces that classical small-molecule agents are not always ideally
suited. Rational design of therapeutic peptides with high affinity targeting such interactions has emerged as a new and
promising tool in discovery of potential drug candidates against associated diseases. The design is commonly based on
bioinformatics methods or molecular modeling techniques, indirectly exploiting structure-activity relationship at the level
of peptide sequence or directly deriving lead entities from protein complex architecture. Here, a newly rising subfield
called computational peptidology that focuses on the use of computational and theoretical approaches to treat peptiderelated
problems is comprehensively reviewed on the design and discovery of peptide agents targeting protein-protein interactions.
We address a systematic discussion on several representative cases in which the computational peptidology is
successfully employed to develop peptide therapeutics. Besides, some problems and pitfalls accompanied with the current
use of computational methods in peptide modeling and design are also present.