Totally Caged Type I Pro-Photosensitizer for Oxygen-Independent Synergistic Phototherapy of Hypoxic Tumors.

Activatable type I photosensitizers are an effective way to overcome the insufficiency and imprecision of photodynamic therapy in the treatment of hypoxic tumors, however, the incompletely inhibited photoactivity of pro-photosensitizer and the limited oxidative phototoxicity of post-photosensitizer are major limitations. It is still a great challenge to address these issues using a single and facile design. Herein, a series of totally caged type I pro-photosensitizers (Pro-I-PSs) are rationally developed that are only activated in tumor hypoxic environment and combine two oxygen-independent therapeutic mechanisms under single-pulse laser irradiation to enhance the phototherapeutic efficacy. Specifically, five benzophenothiazine-based dyes modified with different nitroaromatic groups, BPN 1-5, are designed and explored as latent hypoxia-activatable Pro-I-PSs. By comparing their optical responses to nitroreductase (NTR), it is identified that the 2-methoxy-4-nitrophenyl decorated dye (BPN 2) is the optimal Pro-I-PSs, which can achieve NTR-activated background-free fluorescence/photoacoustic dual-modality tumor imaging. Furthermore, upon activation, BPN 2 can simultaneously produce an oxygen-independent photoacoustic cavitation effect and a photodynamic type I process at single-pulse laser irradiation. Detailed studies in vitro and in vivo indicated that BPN 2 can effectively induce cancer cell apoptosis through synergistic effects. This study provides promising potential for overcoming the pitfalls of hypoxic-tumor photodynamic therapy.

Discovery of benzoheterocyclic-substituted amide derivatives as apoptosis signal-regulating kinase 1 (ASK1) inhibitors.

Three series of benzoheterocyclic-substituted amide derivatives were designed and synthesized as potent ASK1 inhibitors in this work. After undergoing continuous structural optimization, compound 17a was discovered to be a novel inhibitor of ASK1 with good potency (kinase, IC50 = 26 nM), noteworthy liver microsomal stability (human, T1/2 = 340.4 min), good pharmacokinetic parameters (rat, T1/2 p.o. = 2.11 h, AUClast p.o. = 10 900 h ng mL-1) and high oral bioavailability (rat, F = 97.9%), while also being inactive towards hERG (IC50 > 10 µM).

Accelerating and Automating the Free Energy Perturbation Absolute Binding Free Energy Calculation with the RED-E Function.

The accurate prediction of the binding affinities between small molecules and biological macromolecules plays a fundamental role in structure-based drug design, which is still challenging. The free energy perturbation-based absolute binding free energy (FEP-ABFE) approach has shown potential in its reliability. To correctly calculate the energy related to the ligand being restrained by the receptor, additional restraints between the ligand and the receptor are needed. However, determining the restraint parameters for individual ligands empirically is too trivial to be automated, and usually gives rise to numerical instabilities, which set back the applications of FEP-ABFE. To address these issues, we derived the analytical expression for the probability distribution of energy differences, P(ΔU), during the process of restraint addition, which is called the RED-E (restraint energy distribution at equilibrium position) function. Simulations indicated that the RED-E function can accurately describe P(ΔU) when restraints are added at the equilibrium position. Based on the RED-E function, an automatic restraint selection method was proposed to select the best restraint. With this method, there is a high phase-space overlap between the free and restrained states, such that using a 2-λ perturbation can accurately calculate the free energy of the restraint addition, which is a nearly 6 times acceleration compared with current widely used 12-λ perturbation method. The RED-E function gives insight into the non-Gaussian behavior of the sampled P(ΔU) in certain FEP processes in an analytical way. The highly automated and accelerated restraint selection also makes it possible for the large-scale application of FEP-ABFE in real drug discovery practices.

Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning.

To discuss the application method and effect of COPD patients in deep learning in intelligent monitoring, two groups were used under a reasonable selection of antibiotics specifically including reasonable and effective oxygen administration, atomization, sputum discharge treatment, psychotherapy, and rehabilitation training and treatment. Results were indicated, and there were significant differences between the lung function evaluation index and the two groups. Its intelligent monitoring mode was 97.5% and 80.0%, while the red blood cell ratio, arterial oxygen partial pressure (PaO2), pulse blood oxygen saturation (SpO2), arterial carbon dioxide partial pressure (PaCO2), and symptom improvement were better than artificial and were statistically significant (P < 0.05). Therefore, the training of the anti-inspiratory muscle can effectively improve the lung function and dyspnea symptoms of COPD patients at the stable stage, thus greatly improving their respiratory function and ensuring the quality of life of patients, which is worthy of clinical application.