Introduction
In the field of drug discovery, peptides have become an important class of compounds with great potential in many other scientific fields. Constrained peptides differ from regular peptides in that their supramolecular structure, which is regulated by intramolecular covalent bonds, gives them enhanced biochemical and physicochemical features. Considering their potential use as drugs and as methods for drug discovery, the two main types of constrained peptides—macrocytic and stapled peptides—have attracted the attention of both academia and industry (1).
Investigating peptides is especially important when tackling protein–protein interactions (PPI), a difficult topic for drug development. The medium-sized molecules (500–6000 Daltons) that lie in between these groups are difficult to target by traditional therapeutic classes, such as small molecules and biological products like antibodies. With the ability to modify difficult PPI drug targets along with the wide variety of structures of peptides, constrained peptides offer a novel platform for drug discovery (2).
Peptides in therapeutics
Peptides are essential for the creation of therapeutic agents since they have special benefits and show promise as treatments for a range of illnesses. The specific features of peptides make them important in therapeutic applications, and current developments have proved that they are effective in treating an array of medical ailments (3). It is possible to create peptides that are selectively targeted to interact with certain proteins or receptors linked to various disorders. By minimizing off-target effects, this tailored method improves treatment precision. Peptides such as stapled and macrocyclic peptides, are exceptionally effective in preventing interactions between proteins (4). PPIs are important in many disorders, hence these peptides have potential as medicines. Certain peptides can penetrate cell membranes because of their ability to penetrate cells. This property broadens the pool of possible medication targets by facilitating the delivery of therapeutic substances into cells. Peptides often elicit fewer immune responses than bigger biologics, which lowers the possibility of immunological reactions that could jeopardize the security and effectiveness of therapeutic interventions (5).
Several AMPs have demonstrated efficacy in treating bacterial infections resistant to antibiotics. For example, certain bacterial infections of the skin and circulation are treated with the peptide daptomycin. Insulin and GLP-1 analogs are two examples of peptide-based hormones that have proven crucial in the treatment of diabetes. GLP-1 analog exenatide has been authorized to treat type 2 diabetes. Peptides show potential in the therapy of cancer. The Bcl-2 inhibitor venetoclax is a significant advancement in the targeting of particular proteins essential in the survival of cancer cells (4). As immunomodulators, specific peptides affect how the immune system reacts. A peptide-based immunotherapy called Ipilimumab has been certified to treat advanced melanoma (6). Neurodegenerative illnesses are being investigated with peptides. Analogs of amylin, for example, have the potential to cure Alzheimer’s disease by preventing amyloid-beta peptides from aggregating (1). Angiotensin-converting enzyme (ACE) inhibitor peptides, including enalapril, have been effective in treating coronary artery disease and hypertension (7).
Applications in biotechnology
Peptides are essential for many biotechnological uses; they are particularly useful for bioimaging, biomarker identification, and diagnostics. Peptides are useful tools in diagnostics because they may identify particular biomolecules that are suggestive of different disorders. Peptide-based biosensors improve diagnostic capabilities by enabling sensitive and specific identification through the unique binding interactions involving peptides and target molecules (8).
Peptides also play a key role in the discovery of biomarkers since they may be engineered to interact with markers unique to a given disease, making it easier to recognize and track pathological states. They are versatile enough to be used as imaging agents in bioimaging applications. Peptide-based imaging probes allow for the highly precise viewing of certain biological targets and are frequently used in conjunction with imaging modalities like fluorescence or magnetic resonance imaging (MRI) (9).
Peptide synthesis techniques
Peptide synthesis is the process of creating medicinal medicines by assembling small chains of amino acids, or peptides. Solid-phase peptide Synthesis (SPPS) is a well-known technique that is frequently used because of its excellent purity and capacity for automated procedures. It has trouble generating big, complicated peptides, though (10). The conventional method without strong backing, known as liquid-phase peptide synthesis (LPPS), is appropriate for smaller peptides but is linked to lesser purity. Compared to typical LPPS, Solution-Phase Peptide Synthesis (SPPS), which is a version of SPPS in a solution without solid support, is more appropriate for bigger peptides and can be automated. Peptide production depends on protecting groups like Boc and Fmoc, which provide stability and kinder deprotection circumstances (11).
Large, complicated peptide synthesis is facilitated by chemical ligation, whereas non-standard amino acids can be included in enzymatic synthesis by using enzymes to generate peptide bonds in mild circumstances. Different methods have different benefits and drawbacks, which affect which one is best suited depending on the particular needs of the peptide being made. The efficiency and range of peptide synthesis for drug discovery and other scientific applications are constantly being improved by technological advancements in the field, such as the use of novel coupling reagents and unusual amino acids (2).
Computational Approaches to Peptide Search
Computational techniques have played a key role in the revolution of peptide discovery in recent years, providing effective and focused strategies for finding new bioactive peptides. In this process, bioinformatics tools are essential since they help to speed up and improve the accuracy of peptide search attempts. These computational methods make use of prediction models and algorithms to evaluate large datasets, identify putative peptide candidates, and expedite the process of choosing candidates for validation in experiments. By using in silico methods, scientists may evaluate the structural properties, binding affinities, and possible biological activities of peptides, leading to more targeted and economical experiments (12,13).
Computational techniques greatly improve the effectiveness of peptide discovery via molecular modeling, virtual screening, and structure-activity correlation predictions, providing insightful information that directs further experimental effort. In addition to accelerating the discovery of therapeutic peptides, the combination of computational methods and experimental validation advances our knowledge of structure-function relationships and opens the door to novel uses in the creation of drugs and other fields of study (14).
Conclusion
Peptides, in a nutshell, have become important agents in the field of drug development due to their special ability to target difficult protein-protein interactions and overcome the drawbacks of conventional therapeutic classes. Recent developments in peptide treatments demonstrate their exceptional effectiveness in treating a wide range of illnesses, including cancer, neurological diseases, and bacterial infections. In addition, the use of computational methods has greatly expedited the identification of new peptides, improved candidate selection efficiency and offered insightful information about structure-function correlations that stimulate creativity in drug development and other scientific fields.
References
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