Andrew L. Ferguson

The paper shows CAHS12 proteins protect synthetic cells under stress by forming a network that maintains membrane integrity and preserves encapsulated components.

ProT-VAE designs functional proteins by learning sequence-function relationships using a transformer-based variational autoencoder, enabling conditional generation of novel sequences with high functionality.

This paper predicts the structures of αIIbβ3 integrin along its minimum free energy activation pathway using a computational method, revealing correlated subdomain movements and providing insights for therapeutic design.

This paper uses an equation-free method to accelerate all-atom simulations of microtubule tips, revealing structural differences between GDP- and GTP-bound states.

This paper introduces BioM3, a framework that uses natural language prompts to design functional proteins, achieving state-of-the-art performance in prediction and generating proteins with native-like structures and function.

This paper introduces ProtWave-VAE, a generative model combining VAE and autoregressive methods for protein design, showing it can infer functional patterns and generate synthetic proteins with experimental validation.

This study uses deep generative models to design synthetic SH3 domains functional in yeast stress signaling, showing a VAE can recapitulate natural function and classify orthologs by phylogeny and function.