Discovery of novel dual VEGFR2 and Src inhibitors using a multistep virtual screening approach

Synthesis and Structure–Activity Relationships for the Anti-Mycobacterial Activity of 3-Phenyl-N-(Pyridin-2-ylmethyl)Pyrazolo[1,5-a]Pyrimidin-7-Amines

Pyrazolo[1,5-a]pyrimidines have been reported as potent inhibitors of mycobacterial ATP synthase for the treatment of Mycobacterium tuberculosis (M.tb). In this work, we report the design and synthesis of approximately 70 novel 3,5-diphenyl-N-(pyridin-2-ylmethyl)pyrazolo[1,5-a]pyrimidin-7-amines and their comprehensive structure–activity relationship studies. The most effective pyrazolo[1,5-a]pyrimidin-7-amine analogues contained a 3-(4-fluoro)phenyl group, together with a variety of 5-alkyl, 5-aryl and 5-heteroaryl substituents. A range of substituted 7-(2-pyridylmethylamine) derivatives were also active. Some of these compounds exhibited potent in vitro M.tb growth inhibition, low hERG liability and good mouse/human liver microsomal stabilities, highlighting their potential as inhibitors of M.tb.

Applications of machine-learning methods for the discovery of NDM-1 inhibitors

The emergence of New Delhi metal beta-lactamase (NDM-1)-producing bacteria and their worldwide spread pose great challenges for the treatment of drug-resistant bacterial infections. These bacteria can hydrolyze most β-lactam antibacterials. Unfortunately, there are no clinically useful NDM-1 inhibitors. In the current work, we manually collected NDM-1 inhibitors reported in the past decade and established the first NDM-1 inhibitor database. Four machine-learning models were constructed using the structural and property characteristics of the collected compounds as input training set to discover potential NDM-1 inhibitors. In order to distinguish between high active inhibitors and putative positive drugs, a three-classification strategy was introduced in our study. In detail, the commonly used positive and negative divisions are converted into strongly active, weakly active, and inactive. The accuracy of the best prediction model designed based on this strategy reached 90.5%, compared with 69.14% achieved by the traditional docking-based virtual screening method. Consequently, the best model was used to virtually screen a natural product library. The safety of the selected compounds was analyzed by the ADMET prediction model based on machine learning. Seven novel NDM-1 inhibitors were identified, which will provide valuable clues for the discovery of NDM-1 inhibitors.

Discovery of a Natural Syk Inhibitor from Chinese Medicine through a Docking-Based Virtual Screening and Biological Assay Study

Spleen tyrosine kinase (Syk) is a critical target protein for treating immunoreceptor signalling-mediated allergies. In this study, a virtual screening of an in-house Chinese medicine database followed by biological assays was carried out to identify novel Syk inhibitors. A molecular docking method was employed to screen for compounds with potential Syk inhibitory activity. Then, an in vitro kinase inhibition assay was performed to verify the Syk inhibitory activity of the virtual screening hits. Subsequently, a β-hexosaminidase release assay was conducted to evaluate the anti-mast cell degranulation activity of the active compounds. Finally, tanshinone I was confirmed as a Syk inhibitor (IC₅₀ = 1.64 μM) and exhibited anti-mast cell degranulation activity in vitro (IC₅₀ = 2.76 μM). Docking studies showed that Pro455, Gln462, Leu377, and Lys458 were key amino acid residues for Syk inhibitory activity. This study demonstrated that tanshinone I is a Syk inhibitor with mast cell degranulation inhibitory activity. Tanshinone I may be a potential lead compound for developing effective and safe Syk-inhibiting drugs.

Effect of Melatonin on the Expression of VEGF-A and on the Degeneration of Follicle Reserve in Rat Ovary

Objective

To analyze the effects of melatonin on vascular endothelial growth factor A (VEGF-A) expression and follicle reserve in rat ovary.

Materials and Methods

A total of 45 female Wistar rats were used in the present study. Rats were divided into three groups: group 1 (control), group 2 (vehicle), and group 3 (melatonin). Rats in the melatonin group were treated with an intraperitoneal injection of melatonin at a dose of 50 mg/kg/day for 56 days. We investigated VEGF-A expression in rat ovary in all the groups using Western blot and reverse transcription-polymerase chain reaction. Histopathological parameters were evaluated using light microscopy.

Results

The number of atretic follicles was significantly lower in the melatonin treatment rats than in the control rats (p<0.05); however, the number of antral follicles was significantly higher in the former (p<0.05). Additionally, we observed a weak immunoblot stain in the melatonin group for VEGF-A protein. Interestingly, melatonin treatment induced a significant decrease in VEGF-A expression in the ovary of group 3 rats (p<0.05), whereas no such difference was observed between group 1 and group 2 rats (p>0.05).

Conclusion

The present study demonstrates that the protective effect of melatonin on the degeneration of follicles in rat ovary is reduced by decreasing the VEGF-A expression. These results suggest that melatonin is effective against follicular atresia and preserves antral follicles, thus, offering a therapeutic advantage in clinical use.

Discovery of VEGFR2 inhibitors by integrating naïve Bayesian classification, molecular docking and drug screening approaches

The high morbidity and mortality of cancer make it one of the leading causes of global death, thus it is an urgent need to develop effective drugs for cancer therapy.