Die Plant Science Student Conference (PSSC) wird seit 20 Jahren im jährlichen Wechsel von Studierenden der beiden Leibniz-Institute IPK und IPB organisiert. Im Interview erläutern Christina Wäsch (IPK) und Carolin Apel (IPB),…
Über 600 Gäste kamen am 4. Juli ans IPB zur Langen Nacht, die Wissen schafft, um bei unserem Wissenschafts-Quiz-Parcours viel Neues zu erfahren und ihre Kenntnisse unter Beweis zu stellen. Unser Programm in diesem Jahr…
Llanes, D.; Rennert, R.; Jänicke, P.; Morgan, I.; Reguera, L.; Rivera, D. G.; Ricardo, M. G.; Wessjohann, L. A.;Development of bombesin-tubulysin conjugates using multicomponent chemistry to functionalize both the payload and the homing peptideFrontiers in Pharmacology151408091(2024)DOI: 10.3389/fphar.2024.1408091
Peptide-drug conjugates (PDCs) have recently gained significant attention for the targeted delivery of anticancer therapeutics, mainly due to their cost-effective and chemically defined production and lower antigenicity compared to ADCs, among other benefits. In this study, we designed and synthesized novel PDCs by conjugating new thiol-functionalized tubulysin analogs (tubugis) to bombesin, a peptide ligand with a relevant role in cancer research. Two tubulysin analogs bearing ready-for-conjugation thiol groups were prepared by an on-resin multicomponent peptide synthesis strategy and subsequently tested for their stand-alone in vitro anti-proliferative activity against human cancer cells, which resulted in IC50 values in the nanomolar range. In addition, various fluorescently labeled [K5]-bombesin(6–14) peptides, non-lipidated and lipidated with fatty acid chains of variable length, were also synthesized using the versatile multicomponent chemistry. These bombesin derivatives were tested for their gastrin-related peptide receptor (GRPR)-mediated internalization into cancer cells using flow cytometry, proving that the lipid tail (especially C14) enhances the cell internalization. Using the tubugi toxins and bombesin peptides, three different bombesin-tubugi conjugates were synthesized with different cleavage propensity and lipophilicity. Preliminary in vitro experiments revealed that, depending on the linker and the presence of a lipid tail, these novel PDCs possess good to potent anticancer activity and moderate selectivity for GRPR-overexpressing cancer cells.
Publikation
Goles, M.; Daza, A.; Cabas-Mora, G.; Sarmiento-Varón, L.; Sepúlveda-Yañez, J.; Anvari-Kazemabad, H.; Davari, M. D.; Uribe-Paredes, R.; Olivera-Nappa, A.; Navarrete, M. A.; Medina-Ortiz, D.;Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptidesBriefings in Bioinformatics25bbae275(2024)DOI: 10.1093/bib/bbae275
With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as short half-life, limited oral bioavailability and susceptibility to plasma degradation. The rise of computational tools and artificial intelligence (AI) in peptide research has spurred the development of advanced methodologies and databases that are pivotal in the exploration of these complex macromolecules. This perspective delves into integrating AI in peptide development, encompassing classifier methods, predictive systems and the avant-garde design facilitated by deep-generative models like generative adversarial networks and variational autoencoders. There are still challenges, such as the need for processing optimization and careful validation of predictive models. This work outlines traditional strategies for machine learning model construction and training techniques and proposes a comprehensive AI-assisted peptide design and validation pipeline. The evolving landscape of peptide design using AI is emphasized, showcasing the practicality of these methods in expediting the development and discovery of novel peptides within the context of peptide-based drug discovery.