César de la Fuente
@delafuentelab.bsky.social
Presidential Associate Professor @upenn.edu - using AI to reimagine antibiotic discovery and peptide design. Previously @MIT, @UBC
🔗 https://delafuentelab.seas.upenn.edu
🔗 https://delafuentelab.seas.upenn.edu
Thanks for sharing!
October 29, 2025 at 4:49 PM
Thanks for sharing!
5/5 Excited for what this unlocks in de novo protein/peptide design. Check out the paper at Nature Machine Intelligence @natureportfolio.nature.com.
Great collaboration with Yan C. Leyva, Marcelo D. Torres, Carlos A. Oliva, & Carlos A. Brizuela!
www.nature.com/articles/s42...
Great collaboration with Yan C. Leyva, Marcelo D. Torres, Carlos A. Oliva, & Carlos A. Brizuela!
www.nature.com/articles/s42...
Tailored structured peptide design with a key-cutting machine approach - Nature Machine Intelligence
Powerful generative AI models for designing biological macromolecules are being developed, with applications in medicine, biotechnology and materials science, but these models are expensive to train a...
www.nature.com
October 23, 2025 at 7:50 AM
5/5 Excited for what this unlocks in de novo protein/peptide design. Check out the paper at Nature Machine Intelligence @natureportfolio.nature.com.
Great collaboration with Yan C. Leyva, Marcelo D. Torres, Carlos A. Oliva, & Carlos A. Brizuela!
www.nature.com/articles/s42...
Great collaboration with Yan C. Leyva, Marcelo D. Torres, Carlos A. Oliva, & Carlos A. Brizuela!
www.nature.com/articles/s42...
4/5 As a demo, we used a known antimicrobial peptide as the “key” and designed new candidates: active against multiple pathogens in vitro and reduced A. baumannii burden in mouse infection models—with good tolerability.
October 23, 2025 at 7:50 AM
4/5 As a demo, we used a known antimicrobial peptide as the “key” and designed new candidates: active against multiple pathogens in vitro and reduced A. baumannii burden in mouse infection models—with good tolerability.
3/5 KCM performs across α-helices, β-sheets, mixed, and unstructured regions, delivering precise backbone geometry while staying lightweight and accessible for small labs, startups, and even classrooms.
October 23, 2025 at 7:50 AM
3/5 KCM performs across α-helices, β-sheets, mixed, and unstructured regions, delivering precise backbone geometry while staying lightweight and accessible for small labs, startups, and even classrooms.
2/5 Instead of black-box generation, KCM runs an optimization loop with ESMFold in the mix. You can encode your requirements—geometry, energy, and sequence descriptors—directly in the objective, steering designs in a transparent, controllable way.
October 23, 2025 at 7:50 AM
2/5 Instead of black-box generation, KCM runs an optimization loop with ESMFold in the mix. You can encode your requirements—geometry, energy, and sequence descriptors—directly in the objective, steering designs in a transparent, controllable way.