Synthesis, characterization, antibacterial evaluation, 2D-QSAR modeling and molecular docking studies for benzocaine derivatives

Aminopyridone-linked benzimidazoles: a fragment-based drug design for the development of CDK9 inhibitors

Aim: A fragment-based design and synthesis of three novel series of aminopyridone-linked benzimidazoles as potential anticancer candidates with significant CDK9 inhibition was implemented. Materials & methods: All synthesized compounds were submitted to National Cancer Institute, 60 cell lines and seven-dose cytotoxicity toward three cancer cells. Results: Compounds 2, 4a, 4c, 4d, 6a and 8a exhibited significant cytotoxicity and selectivity with IC50 range of 7.61-57.75 μM. Regarding the mechanism either in vitro or in silico, 4a, 6a and 8a displayed potent CDK9 inhibition with IC50 value of 0.424-8.461 μM. Compound 6a arrested the cell cycle at S phase and induced apoptosis in MCF-7 cells. Conclusion: Compound 6a is a promising CDK9 inhibitor that warrants additional research for cancer treatment.

Three-component microwave-assisted synthesis of 3,5-disubstituted pyrazolo[3,4-d]pyrimidin-4-ones

A practical three-component method for the synthesis of pyrazolo[3,4-d]pyrimidin-4-ones was developed. The reaction was performed in a one-pot manner under controlled microwave irradiation using easily accessible methyl 5-aminopyrazole-4-carboxylates, trimethyl orthoformate, and primary amines. Under the optimized conditions, challenging substrates, such as N-1 unsubstituted 5-aminopyrazole-4-carboxylates with another substituted amino group in position 3, reacted selectively affording 5-substituted 3-arylamino-1,5-dihydro-4H-pyrazolo[3,4-d]pyrimidin-4-ones. The reaction tolerated a range of primary amines, including anilines. The advantages of the developed protocol include short reaction time, pot- and step-economy, and convenient chromatography-free product isolation. The structural features of representative products were explored by X-ray crystallography.

A Deep Learning-Based Quantitative Structure-Activity Relationship System Construct Prediction Model of Agonist and Antagonist with High Performance

Molecular design and evaluation for drug development and chemical safety assessment have been advanced by quantitative structure–activity relationship (QSAR) using artificial intelligence techniques, such as deep learning (DL). Previously, we have reported the high performance of prediction models molecular initiation events (MIEs) on the adverse toxicological outcome using a DL-based QSAR method, called DeepSnap-DL. This method can extract feature values from images generated on a three-dimensional (3D)-chemical structure as a novel QSAR analytical system. However, there is room for improvement of this system’s time-consumption. Therefore, in this study, we constructed an improved DeepSnap-DL system by combining the processes of generating an image from a 3D-chemical structure, DL using the image as input data, and statistical calculation of prediction-performance. Consequently, we obtained that the three prediction models of agonists or antagonists of MIEs achieved high prediction-performance by optimizing the parameters of DeepSnap, such as the angle used in the depiction of the image of a 3D-chemical structure, data-split, and hyperparameters in DL. The improved DeepSnap-DL system will be a powerful tool for computer-aided molecular design as a novel QSAR system.

Methicillin-resistance Staphylococcus aureus (MRSA) Pyruvate kinase (PK) inhibitors and Their Antimicrobial Activities

Resistance to antibiotics has been widely existed in the health care and community setting, thus developing a novel aspect of new antibiotics is urgently necessary. Methicillin-resistance Staphylococcus aureus (MRSA) Pyruvate kinase (PK) is crucial to the survive of bacterial, making it a novel antimicrobial target. In the past decade, most reported PK inhibitors including indole, flavonoid, phenazine derivative from natural product small molecules or their analogues, or virtual screening from small molecule compound library. This review covers the PK inhibitors and their antimicrobial activities reported from the beginning of 2011 through the middle of 2020. The Structure Activity Relationships (SARs) was discussed briefly as well.