Longxing Cao

This paper introduces Pinal, a foundation model that designs proteins from natural language descriptions, achieving functional alignment and experimental success in four design tasks.

This paper modifies Nab-paclitaxel with receptor binders to improve tumor targeting and reduce toxicity, showing enhanced efficacy in cancer cells and xenograft models.

This paper introduces a physics-based generative method for designing ligand-binding proteins and demonstrates its application in creating biosensors for small molecules and metal ions.

This paper introduces IMUSE, a method combining machine learning and ultra-high-throughput screening to explore enzyme spaces, identifying mutations that significantly improve enzyme activity.

This paper extends the HalluDesign framework to nucleic acid design using NA-MPNN, improving confidence scores in ssDNA, ssRNA, and aptamer design.

This paper designs metalloproteases that specifically cleave targeted peptide bonds in amyloid-β using a generative model, achieving high specificity and catalytic efficiency.

HalluDesign optimizes and designs proteins using iterative structure hallucination and sequence design, achieving high success rates and structural accuracy in various tasks.

This paper designs high-affinity proteins that bind to convex protein sites using geometrically matching concave scaffolds, achieving low nanomolar to picomolar affinities.

Proteus generates protein backbones efficiently without pre-training, showing high designability in in silico and experimental tests.

The paper designs EndoTags to trigger endocytosis and degradation of target proteins, enabling tissue-specific targeting and therapeutic applications.

This paper introduces a top-down reinforcement learning approach to design protein nanomaterials, resulting in more compact and robust icosahedral assemblies than previously observed.

The paper designs and characterizes trivalent miniprotein binders that neutralize SARS-CoV-2 variants with low pM IC50 values and provide prophylactic and therapeutic protection in mice.

This paper designs small, stable proteins that bind to diverse target proteins using only structural information, achieving nanomolar to picomolar affinities.

This paper introduces SARSNotch, a sentinel cell system that detects SARS-CoV-2 Spike protein and triggers genetic responses in cell lines and T lymphocytes.

The paper designs picomolar SARS-CoV-2 miniprotein inhibitors using computational methods and experimental validation, showing high potency and structural similarity to computational models.

The paper designs modular biosensors using de novo protein switches that detect various analytes with high sensitivity and modularity.