Exploring and expanding the chemical multiverse of peptides

Abstract

Peptides occupy a unique and rapidly expanding domain within the broader chemical space, offering exciting opportunities for therapeutic, nutritional, cosmetic, and materials applications. While efforts to characterize chemical space have traditionally focused on small molecules, growing evidence underscores the value of extending this concept to include peptide-based compounds. In this review, we survey recent advances in the exploration and expansion of the peptide chemical space, focusing on short peptides that bridge chemoinformatics and bioinformatics perspectives. We begin by briefly discussing the impact and applications of peptides in various research and industry areas and then examining the theoretical and practical size of the peptide chemical space, emphasizing how naturally occurring and synthetic peptides vastly increase its diversity. We then discuss molecular representations—from conventional notations to specialized peptide descriptors—highlighting their impact on library design, structural analyses, and activity predictions. Visualization methods and machine learning models are presented as tools for mapping structure–property and structure–function relationships. Next, we explore computational strategies for de novo peptide generation, driven by advances in generative modeling and high-throughput screening. Throughout, we emphasize the role of open-source resources and integrated computational pipelines that combine chemo- and bioinformatics approaches to enhance data quality and predictive performance. We conclude by identifying major challenges—such as the complex structural landscape of peptides, data curation, and the need for consensus screening methods—and outline emerging opportunities for further expanding and refining the peptide chemical space.