Peptides are increasingly recognized for their pivotal role in various scientific and medical fields, spanning from drug development to biomarker discovery. These bioactive molecules, usually composed of 20 or fewer amino acids, exhibit diverse biological activities, making them valuable candidates for therapeutic applications. In particular, their potential utility in treating diseases such as cancer, hypertension, and microbial infections underscores the significance of ongoing peptide research.

The therapeutic applications of peptides have garnered substantial attention due to their unique properties. Peptides can be designed to target specific biological processes or molecules, enhancing the specificity and efficacy of treatments. For instance, studies have shown that certain peptides can enhance the efficacy of cancer drugs by improving their penetration into tumor cells when used in combination with chemotherapeutic agents (Sugahara et al., 2010). Similar principles apply in the development of peptides aimed at regulating blood pressure, where antihypertensive peptides have been shown to demonstrate considerable promise (Kumar et al., 2014).

Despite their advantages, the practical application of peptides in clinical settings is hindered by several challenges. The most significant include their short half-life in circulation and poor membrane permeability, leading to reduced bioavailability (Polańska et al., 2024). Addressing these challenges requires innovative approaches in peptide design and formulation. Researchers are actively exploring modified peptide derivatives that maintain therapeutic efficacy while exhibiting better stability and reduced toxicity (Gautam et al., 2013). This includes the use of databases such as the Antimicrobial Peptide Database (APD) and the Antihypertensive Peptide Database (AHTPDB), which support the design of peptides with optimal properties by providing accessible biological data (Wang, 2004).

In addition to therapeutic uses, peptides play a crucial role in proteomics—the comprehensive study of proteins, particularly in regard to their functions and structures. Techniques such as mass spectrometry have advanced our ability to analyze complex peptide samples, leading to more accurate protein identification and quantification (Mischak et al., 2015; , Borràs et al., 2021). The integration of computational tools like PeptideCalc facilitates the analysis and property determination of peptides (Lear & Cobb, 2016), thereby improving research methodologies in this field. Furthermore, novel chemistries, such as the copper-catalyzed azide-alkyne cycloaddition (CuAAC), are being utilized to enhance peptide labeling in proteomics, thus supporting the dynamic profiling of nascent proteins (Sun et al., 2020).

Emphasizing the importance of data accessibility, recent advancements have resulted in the establishment of various proteomic databases and repositories that enhance the sharing of peptide-related data (Pérez‐Riverol et al., 2015). Such resources promote collaboration and innovation, allowing researchers to build upon each other’s work in identifying peptide biomarkers for diseases and developing new therapeutic strategies. The recognition of missing data and challenges within existing datasets further highlights the need for refined methodologies in peptide research, fostering an environment that values reproducibility and accuracy (Webb‐Robertson et al., 2015).

In summary, peptides occupy a critical space in modern scientific research and pharmaceutical development. The ongoing exploration of their properties, coupled with advancements in computational biology and proteomics, is vital for harnessing their full potential in therapeutics and diagnostic applications. Continuous investment in peptide research, guided by robust data management and innovative methodologies, promises to elevate our understanding and utilization of these versatile biomolecules.