Aditya Krishnakumar

This paper demonstrates that AI-designed receptor modulators can drive efficient human fibroblast-to-muscle transdifferentiation by rewiring extracellular signaling.

The paper designs novel cytokines by fusing computationally generated receptor-binding domains, identifying several that activate signaling pathways and have specific biological effects.

This paper designs synthetic cytokine agonists with controlled receptor geometry to modulate signaling outcomes and functional effects.

This study uses target-conditioned diffusion to design high-affinity TNFR superfamily antagonists and agonists with switchable specificity.

This study uses deep learning to predict protein-protein interactions in bacterial pathogens, identifying new complexes involving essential genes and virulence factors, with half of tested predictions validated.