
Últimas noticias
A continuación se muestran las últimas novedades sobre investigaciones, eventos, actividades y descubrimientos que se llevan a cabo en el Instituto de Productos Naturales y Agrobiología.
Próximos Eventos
Publicaciones recientes
Conversion of Hydroxyproline “Doubly Customizable Units” to Hexahydropyrimidines: Access to Conformationally Constrained Peptides
The efficient transformation of hydroxyproline “doubly customizable units” into rigid hexahydropyrimidine units takes place in good global yields and generates compounds of pharmaceutical interest. In particular, the process can readily provide access to peptidomimetics and peptides with reversed sequences or with valuable turns.
Hernández, Dácil; Porras, Marina; Boto, Alicia.
Volcanic ash deposition as a selection mechanism towards woodiness
The high proportion of woody plant species on oceanic islands has hitherto been explained mainly by gradual adaptation to climatic conditions. Here, we present a novel hypothesis that such woodiness is adaptative to volcanic ash (tephra) deposition. Oceanic islands are subject to frequent eruptions with substantial and widespread ash deposition on evolutionary time scales. We postulate that this selects for woodiness through an increased ability to avoid burial of plant organs by ash, and to re-emerge above the new land surface. We sense-checked using observations of plant occurrences and distributions on La Palma (Canary Islands) in April 2022, 4 months after the end of the eruptions of the Tajogaite volcano (Cumbre Vieja ridge). In contrast to herbs and grasses, most woody plants persisted and were already in full flower in areas with 10+ cm ash deposition. Remarkably, these persisting woody plants were almost exclusively endemics.
Beierkuhnlein, Carl; Nogales, Manuel; Field, Richard; Vetaas, Ole R.; Walentowitz, Anna; Weiser, Frank; Stahlmann, Reinhold; Guerrero-Campos, María; Jentsch, Anke; Medina, Félix M.; Chiarucci, Alessandro.
Prediction of Antifungal Activity of Antimicrobial Peptides by Transfer Learning from Protein Pretrained Models
Peptides with antifungal activity have gained significant attention due to their potential therapeutic applications. In this study, we explore the use of pretrained protein models as feature extractors to develop predictive models for antifungal peptide activity. Various machine learning classifiers were trained and evaluated. Our AFP predictor achieved comparable performance to current state-of-the-art methods. Overall, our study demonstrates the effectiveness of pretrained models for peptide analysis and provides a valuable tool for predicting antifungal peptide activity and potentially other peptide properties.
Lobo, Fernando; González, Maily Selena; Boto, Alicia; Pérez de Lastra, José Manuel.
Blog
El blog del IPNA recoge artículos de divulgación sobre los diversos proyectos de investigación desarrollados en el centro, avances en la ciencia y otros temas de interés sobre cultura científica.