Exploring and Expanding the Chemical Multiverse of Peptides

Abstract

Peptides occupy a distinct and rapidly expanding domain within the broader chemical space, offering tremendous opportunities for therapeutic, nutritional, cosmetic, and materials science applications. While efforts to characterize chemical space have traditionally focused on small molecules, increasing evidence highlights the value of extending this concept to peptide-based compounds. In this review, we summarize recent advances in the exploration and expansion of peptide chemical space, focusing on short peptides that bridge cheminformatics and bioinformatics perspectives. We begin by briefly discussing the impact and applications of peptides across diverse scientific and industrial areas, followed by an examination of the theoretical and practical size of peptide chemical space, emphasizing how naturally occurring and synthetic peptides collectively broaden its diversity. We then discuss molecular representations—from conventional notations to specialized peptide descriptors—highlighting their impact on library design, structural analyses, and activity prediction. Visualization methods and machine-learning models are presented as powerful tools for mapping structure–property and structure–function relationships. Next, we explore computational strategies for the de novo design and generation of peptides, 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 intricate structural landscape of peptides, data curation issues, and the need for consensus screening methods—and outline emerging opportunities for further expanding and refining peptide chemical space.