Molecular docking, molecular modeling, and molecular dynamics studies of azaisoflavone as dual COX-2 inhibitors and TP receptor antagonists

Bioisosteric heterocyclic analogues of natural bioactive flavonoids by scaffold-hopping approaches: State-of-the-art and perspectives in medicinal chemistry

The flavonoid family is a set of well-known bioactive natural molecules, with a wide range of potential therapeutic applications. Despite the promising results obtained in preliminary in vitro/vivo studies, their pharmacokinetic and pharmacodynamic profiles are severely compromised by chemical instability. To address this issue, the scaffold-hopping approach is a promising strategy for the structural optimization of natural leads to discover more potent analogues. In this scenario, this Perspective provides a critical analysis on how the replacement of the chromon-4-one flavonoid core with other bioisosteric nitrogen/sulphur heterocycles might affect the chemical, pharmaceutical and biological properties of the resulting new chemical entities. The investigated derivatives were classified on the basis of their biological activity and potential therapeutic indications. For each session, the target(s), the specific mechanism of action, if available, and the key pharmacophoric moieties were highlighted, as revealed by X-ray crystal structures and in silico structure-based studies. Biological activity data, in vitro/vivo studies, were examined: a particular focus was given on the improvements observed with the new heterocyclic analogues compared to the natural flavonoids. This overview of the scaffold-hopping advantages in flavonoid compounds is of great interest to the medicinal chemistry community to better exploit the vast potential of these natural molecules and to identify new bioactive molecules.

Natural COX-2 Inhibitors as Promising Anti-inflammatory Agents: An Update

COX-2, a key enzyme that catalyzed the rate-limiting steps in the conversion of arachidonic acid to prostaglandins, played a pivotal role in the inflammatory process. Different from other family members, COX-2 was barely detectable in normal physiological conditions and highly inducible during the acute inflammatory response of human bodies to injuries or infections. Therefore, the therapeutic utilization of selective COX-2 inhibitors has already been considered as an effective approach for the treatment of inflammation with diminished side effects. Currently, both traditional and newer NSAIDs are the commonly prescribed medications that treat inflammatory diseases by targeting COX-2. However, due to the cardiovascular side-effects of the NSAIDs, finding reasonable alternatives for these frequently prescribed medicines are a hot spot in medicinal chemistry research. Naturallyoccurring compounds have been reported to inhibit COX-2, thereby possessing beneficial effects against inflammation and certain cell injury. The review mainly concentrated on recently identified natural products and derivatives as COX-2 inhibitors, the characteristics of their structural core scaffolds, their anti-inflammatory effects, molecular mechanisms for enzymatic inhibition, and related structure-activity relationships. According to the structural features, the natural COX-2 inhibitors were mainly divided into the following categories: natural phenols, flavonoids, stilbenes, terpenoids, quinones, and alkaloids. Apart from the anti-inflammatory activities, a few dietary COX-2 inhibitors from nature origin also exhibited chemopreventive effects by targeting COX-2-mediated carcinogenesis. The utilization of these natural remedies in future cancer prevention was also discussed. In all, the survey on the characterized COX-2 inhibitors from natural sources paves the way for the further development of more potent and selective COX-2 inhibitors in the future.

Elucidating direct kinase targets of compound Danshen dropping pills employing archived data and prediction models

Research on direct targets of traditional Chinese medicine (TCM) is the key to study the mechanism and material basis of it, but there is still no effective methods at present. We took Compound Danshen dropping pills (CDDP) as a study case to establish a strategy to identify significant direct targets of TCM. As a result, thirty potential active kinase targets of CDDP were identified. Nine of them had potential dose-dependent effects. In addition, the direct inhibitory effect of CDDP on three kinases, AURKB, MET and PIM1 were observed both on biochemical level and cellular level, which could not only shed light on the mechanisms of action involved in CDDP, but also suggesting the potency of drug repositioning of CDDP. Our results indicated that the research strategy including both in silico models and experimental validation that we built, were relatively efficient and reliable for direct targets identification for TCM prescription, which will help elucidating the mechanisms of TCM and promoting the modernization of TCM.

Computational investigation reveals Picrasidine C as selective PPARα lead: binding pattern, selectivity mechanism and ADME/tox profile

Natural products and their derivatives have been recognized as an important source of therapeutic agents for many years. Previously we isolated a dimeric β-carboline-type alkaloid Picrasidine C from the root of Picrasma quassioides as subtype-selective peroxisome proliferator-activated receptor α (PPARα) agonist. In order to modify this natural product for better affinity and druggability, we investigated a series of properties exhibited by Picrasidine C, such as its binding mode with PPARα, the selectivity mechanism over PPARγ, as well as ADME/Tox profile through computational methods including sequence alignment, molecular docking, pharmacophore modeling and molecular dynamics simulations. The detailed information of binding pattern and affinity for Picrasidine C elucidated here will be valuable for chemical modification. Besides, the steric hindrance of residue Phe363 in PPARγ pocket was speculated as the main isoform selectivity mechanism for Picrasidine C, which would be helpful for the design of selective derivatives. ADME/Tox prediction was conducted to avoid potential undesirable pharmacokinetic properties for reducing the risk of failure. Finally, novel skeletons were derived from lead compound by core hopping method, validated through molecular dynamic simulations and MM-GBSA calculation. In short, the information obtained from computational strategy would be valuable for us to find more potent, safe and selective PPARα agonists during structural optimization.

Automated discovery of GPCR bioactive ligands

While G-protein-coupled receptors (GPCRs) constitute the largest class of membrane proteins, structures and endogenous ligands of a large portion of GPCRs remain unknown. Because of the involvement of GPCRs in various signaling pathways and physiological roles, the identification of endogenous ligands as well as designing novel drugs is of high interest to the research and medical communities. Along with highlighting the recent advances in structure-based ligand discovery, including docking and molecular dynamics, this article focuses on the latest advances for automating the discovery of bioactive ligands using machine learning. Machine learning is centered around the development and applications of algorithms that can learn from data automatically. Such an approach offers immense opportunities for bioactivity prediction as well as quantitative structure-activity relationship studies. This review describes the most recent and successful applications of machine learning for bioactive ligand discovery, concluding with an outlook on deep learning methods that are capable of automatically extracting salient information from structural data as a promising future direction for rapid and efficient bioactive ligand discovery.