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Computational Design and Therapeutic Applications of Peptide-Based Drugs

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 2477

Special Issue Editor


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Guest Editor
Department of Physics, SSPC the SFI Research Centre for Pharmaceuticals, Bernal Institute, University of Limerick, V94 T9PX Limerick, Ireland
Interests: peptide therapeutics; molecular modeling; drug design; protein-protein interactions; bioavailability optimization

Special Issue Information

Dear Colleagues,

Peptide-based drugs offer unique advantages, including target specificity and lower toxicity, making them promising therapeutic candidates. In silico design of therapeutic peptides is revolutionizing the field of drug discovery by leveraging computational methods to predict, model, and optimize peptide structures before synthesis. Peptides, composed of short chains of amino acids, offer unique therapeutic potential due to their high specificity, low toxicity, and ability to target complex protein–protein interactions. However, poor stability, low bioavailability, and rapid degradation are some of the challenges that need to be addressed for their therapeutic application.

This Special Issue, "Computational Design and Therapeutic Applications of Peptide-Based Drugs", highlights cutting-edge computational and in silico strategies to accelerate peptide drug development. Bioinformatics approaches, structure-based design, molecular dynamics simulations, and quantum mechanical modeling are central to optimizing peptide stability, bioavailability, and receptor binding affinity. Advances in machine learning and AI are shaping therapeutic peptide design rules with enhanced pharmacokinetics. Furthermore, this Special Issue explores how modifications at the molecular level, such as cyclization and amino acid substitutions, are improving peptide resistance to enzymatic degradation. The therapeutic applications discussed cover a range of diseases, including cancer, metabolic disorders, and microbial infections, showcasing the immense potential of computational tools in creating next-generation peptide therapeutics. This collection of original research and review articles illustrates how molecular insights are driving innovations in peptide drug design and therapeutic applications.

Dr. Shayon Bhattacharya
Guest Editor

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Keywords

  • peptide drug design
  • in silico drug discovery
  • peptide–protein interactions
  • therapeutic peptides

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Published Papers (1 paper)

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Research

23 pages, 2484 KB  
Article
In Silico Identification of Potential Clovibactin-like Antibiotics Binding to Unique Cell Wall Precursors in Diverse Gram-Positive Bacterial Strains
by Olimpo Sierra-Hernandez, Oscar Saurith-Coronell, Juan Rodríguez-Macías, Edgar Márquez, José Ramón Mora, José L. Paz, Maryury Flores-Sumoza, Adel Mendoza-Mendoza, Virginia Flores-Morales, Yovani Marrero-Ponce, Stephen J. Barigye and Felix Martinez-Rios
Int. J. Mol. Sci. 2025, 26(4), 1724; https://doi.org/10.3390/ijms26041724 - 18 Feb 2025
Viewed by 1864
Abstract
The rise in multidrug-resistant bacteria highlights the critical need for novel antibiotics. This study explores clovibactin-like compounds as potential therapeutic agents targeting lipid II, a crucial component in bacterial cell wall synthesis, using in silico techniques. A total of 2624 clovibactin analogs were [...] Read more.
The rise in multidrug-resistant bacteria highlights the critical need for novel antibiotics. This study explores clovibactin-like compounds as potential therapeutic agents targeting lipid II, a crucial component in bacterial cell wall synthesis, using in silico techniques. A total of 2624 clovibactin analogs were sourced from the PubChem database and screened using ProTox 3.0 software based on their ADME-Tox properties, prioritizing candidates with favorable pharmacokinetic profiles and minimal toxicity. Molecular docking protocols were then employed to assess the binding interactions of the selected compounds with lipid II. Our analysis identified Compound 22 as a particularly promising candidate, exhibiting strong binding affinity, stable complex formation, and high selectivity for the target. Binding energy analysis, conducted via molecular dynamics simulations, revealed a highly negative value of −25.50 kcal/mol for Compound 22, surpassing that of clovibactin and underscoring its potential efficacy. In addition, Compound 22 was prioritized due to its exceptional binding affinity to lipid II and its favorable ADME-Tox properties, suggesting a lower likelihood of adverse effects. These characteristics position Compound 22 as a promising candidate for further pharmacological development. While our computational results are encouraging, experimental validation is essential to confirm the efficacy and safety of these compounds. This study not only advances our understanding of clovibactin analogs but also contributes to the ongoing efforts to combat antimicrobial resistance through innovative antibiotic development. Full article
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