A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

Effect of single intravenous injection of esketamine on postpartum depression after labor analgesia and potential mechanisms: a randomized, double-blinded controlled trial

BACKGROUND

The study was designed to investigate effects of single intravenous injection of esketamine on the incidence of postpartum depression (PPD) after labor analgesia and explore the potential mechanisms.

METHODS

A total of 120 women who underwent labor analgesia by epidural analgesia pump were enrolled and divided into two groups randomly. Esketamine at a dose of 0.2 mg/kg was intravenously injected after fetal disengagement in the test group and placebo was administered in the control group. The occurrence of PPD and side effects after delivery were recorded. Some indicators related to stress and inflammation were measured before labor analgesia and at 24 h, 1 week, and 6 weeks after delivery in this study. Data were analyzed by independent t-test, repeated measures analysis of variance and Chi-square test in SPSS software (version 25.0). It was considered statistically significant since a p value less than 0.05.

RESULTS

The incidence of PPD was significantly decreased both for one week and six weeks after delivery by using of esketamine (3.4% vs. 15.3%, p = 0.004 and 5.2% vs. 18.6%, p = 0.006, respectively). There were also significant differences between the stress and inflammation-related indicators in different time points in this study, while the side effects for 48 h after delivery were similar between the two groups.

CONCLUSIONS

Single intravenous injection of esketamine after delivery in participants underwent labor analgesia can decrease the occurrence of postpartum depression for one week and six weeks after delivery, while the side effects were not increased. The antidepressant effects of esketamine may be related to the reduction of stress response and inflammation.

TRIAL REGISTRATION

The trial was registered at the Chinese Clinical Trial Registry on 5/30/2022 (CTRI registration number-ChiCTR2200060387). URL of registry: https://www.chictr.org.cn/bin/home .