In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning models.

There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein design pipeline that uses iterative rounds of deep learning (DL)-based structure prediction (AlphaFold2) and sequence optimization (ProteinMPNN) to design autoinhibitory domains (AiDs) for a PD-L1 antagonist. With the goal of creating an anticancer agent that is inactive until reaching the tumor environment, we sought to create autoinhibited (or masked) forms of the PD-L1 antagonist that can be unmasked by tumor-enriched proteases. Twenty-three de novo designed AiDs, varying in length and topology, were fused to the antagonist with a protease-sensitive linker, and binding to PD-L1 was measured with and without protease treatment. Nine of the fusion proteins demonstrated conditional binding to PD-L1, and the top-performing AiDs were selected for further characterization as single-domain proteins. Without any experimental affinity maturation, four of the AiDs bind to the PD-L1 antagonist with equilibrium dissociation constants (KDs) below 150 nM, with the lowest KD equal to 0.9 nM. Our study demonstrates that DL-based protein modeling can be used to rapidly generate high-affinity protein binders.

In silico evolution of protein binders with deep learning models for structure prediction and sequence design.

There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein design pipeline that uses iterative rounds of deep learning (DL)-based structure prediction (AlphaFold2) and sequence optimization (ProteinMPNN) to design autoinhibitory domains (AiDs) for a PD-L1 antagonist. Inspired by recent advances in therapeutic design, we sought to create autoinhibited (or masked) forms of the antagonist that can be conditionally activated by proteases. Twenty-three de novo designed AiDs, varying in length and topology, were fused to the antagonist with a protease sensitive linker, and binding to PD-L1 was tested with and without protease treatment. Nine of the fusion proteins demonstrated conditional binding to PD-L1 and the top performing AiDs were selected for further characterization as single domain proteins. Without any experimental affinity maturation, four of the AiDs bind to the PD-L1 antagonist with equilibrium dissociation constants (KDs) below 150 nM, with the lowest KD equal to 0.9 nM. Our study demonstrates that DL-based protein modeling can be used to rapidly generate high affinity protein binders.

Single-Cell Activation of the cAMP-Signaling Pathway in 3D Tissues with FRET-Assisted Two-Photon Activation of bPAC.

Bacterial photoactivated adenylyl cyclase (bPAC) has been widely used in signal transduction research. However, due to its low two-photon absorption, bPAC cannot be efficiently activated by two-photon (2P) excitation. Taking advantage of the high two-photon absorption of monomeric teal fluorescent protein 1 (mTFP1), we herein developed 2P-activatable bPAC (2pabPAC), a fusion protein consisting of bPAC and mTFP1. In 2pabPAC, the energy absorbed by mTFP1 excites bPAC by Fürster resonance energy transfer (FRET) at ca. 43% efficiency. The light-induced increase in cAMP was monitored by a red-shifted FRET biosensor for PKA. In 3D MDCK cells and mouse liver, PKA was activated at single-cell resolution under a 2P microscope. We found that PKA activation in a single hepatocyte caused PKA activation in neighboring cells, indicating the propagation of PKA activation. Thus, 2pabPAC will provide a versatile platform for controlling the cAMP signaling pathway and investigating cell-to-cell communication in vivo.

FRET-assisted photoactivation of flavoproteins for in vivo two-photon optogenetics.

Optical dimerizers have been developed to untangle signaling pathways, but they are of limited use in vivo, partly due to their inefficient activation under two-photon (2P) excitation. To overcome this problem, we developed Förster resonance energy transfer (FRET)-assisted photoactivation, or FRAPA. On 2P excitation, mTagBFP2 efficiently absorbs and transfers the energy to the chromophore of CRY2. Based on structure-guided engineering, a chimeric protein with 40% FRET efficiency was developed and named 2P-activatable CRY2, or 2paCRY2. 2paCRY2 was employed to develop a RAF1 activation system named 2paRAF. In three-dimensionally cultured cells expressing 2paRAF, extracellular signal-regulated kinase (ERK) was efficiently activated by 2P excitation at single-cell resolution. Photoactivation of ERK was also accomplished in the epidermal cells of 2paRAF-expressing mice. We further developed an mTFP1-fused LOV domain that exhibits efficient response to 2P excitation. Collectively, FRAPA will pave the way to single-cell optical control of signaling pathways in vivo.

Successful single-lung transplantation for multicentric Castleman disease.

We report a rare case of multicentric Castleman disease treated successfully with single-lung transplantation. A 12-year-old patient developed increasing dyspnea. Elevated serum interleukin-6 (177.0 pg/mL) and immunoglobulin G (IgG; 13,900 mg/dL) levels were observed. Steroid therapy was effective but the respiratory condition gradually deteriorated. He underwent single-lung transplantation at 36 years of age. Preoperative interleukin-6 and IgG levels were 0.3 pg/mL and 5,260 mg/dL, respectively. After 6 months he is alive without symptoms. Postoperative IgG levels were restored to normal limits (1,624 mg/dL) and interleukin-6 levels remained within normal limits (1.4 pg/mL). Overinflation of the native left lung also improved.