Photoinduced Electron Transfer-Based Glutathione-Sensing Theranostic Nanoprodrug with Self-Tracking and Real-Time Drug Release Monitoring for Cancer Treatment.

The rapid development of nanomedicine has considerably advanced precision therapy for cancer treatment. Superior to traditional chemotherapy, emerging theranostic nanoprodrugs can effectively realize inherent self-tracking, targeted drug delivery, stimuli-triggered drug release, and reduced systemic toxicity of chemotherapeutic drugs. However, theranostic nanoprodrugs with real-time drug release monitoring have remained rare so far. In this work, we developed a new glutathione-responsive theranostic nanoprodrug with a high drug-loading content of 59.4 wt % and an average nanoscale size of 46 nm, consisting of the anticancer drug paclitaxel and a fluorescent imaging probe with a high fluorescence quantum yield, which are linked by a disulfide-based glutathione-sensitive self-immolating linker. The strong fluorescence emission of the fluorophore enables efficacious self-tracking and sensitive fluorescence "ON-OFF" glutathione sensing. Upon encountering high-level glutathione in cancer cells, the disulfide bond is cleaved, and the resulting linker halves spontaneously collapse into cyclic small molecules at the same pace, leading to the simultaneous release of the therapeutic drug and the fluorescence-OFF imaging probe. Thereby, the drug release process is efficiently monitored by the fluorescence change in the nanoprodrug. The nanoprodrugs exerted high cytotoxicity toward various cancer cells, especially for A549 and HEK-293 cells, in which the nanoprodrugs generated better therapeutic effects than free paclitaxel. Our work demonstrated a new modality of smart theranostic nanoprodrugs for precise cancer therapy.

Protein Molecular Dynamics Simulations with Approximate QM: What Can We Learn?

Classical force fields are essential for computer simulations of proteins and are typically parameterized to reproduce secondary and tertiary structure of isolated proteins. However, while protein-protein interactions are ubiquitous in nature, they are not considered in parameterization efforts and are far less understood than isolated proteins. A better characterization of intermolecular interactions is widely recognized as a key to revolutionizing drug and therapeutic developments with high-throughput computational screening. Urgently needed is a critical assessment of the performance of modern protein force fields against first-principles electronic structure methods and experiments. In a daring step toward this goal, we here describe a comparison of peptide folding dynamics as predicted by a molecular mechanics force field on the one hand and by an approximate electronic structure quantum mechanical (QM) method based on density-functional tight-binding (DFTB) on the other. We further compare the dynamics from straightforward DFTB simulations with a near-linear scaling version of DFTB for massively parallel computation based on the fragment molecular orbital (FMO-DFTB) method. We illustrate differences between the phenomenology of the folding dynamics from these three methods for a small model peptide, as well as charge polarization and dynamic fluctuations, point out possible correlations and implications for force field developers, and discuss the lessons learned that might become applicable to future predictive high-throughput computer screening for personalized neoantigen cancer therapy.