Innate Immunomodulatory Activity of Cedrol, a Component of Essential Oils Isolated from Juniperus Species

Little is known about the immunomodulatory activity of essential oils isolated from Juniperus species. Thus, we isolated essential oils from the cones and leaves of eight juniper species found in Montana and in Kazakhstan, including J. horizontalis, J. scopolorum, J. communis, J. seravschanica, J. sabina, J. pseudosabina, J. pseudosabina subsp. turkestanica, and J. sibirica. We report here the chemical composition and innate immunomodulatory activity of these essential oils. Compositional analysis of the 16 samples of Juniper essential oils revealed similarities and differences between our analyses and those previously reported for essential oils from this species. Our studies represent the first analysis of essential oils isolated from the cones of four of these Juniper species. Several essential oil samples contained high levels of cedrol, which was fairly unique to three Juniper species from Kazakhstan. We found that these essential oils and pure (+)-cedrol induced intracellular Ca2+ mobilization in human neutrophils. Furthermore, pretreatment of human neutrophils and N-formyl peptide receptor 1 and 2 (FPR1 and FPR2) transfected HL60 cells with these essential oils or (+)-cedrol inhibited agonist-induced Ca2+ mobilization, suggesting these responses were desensitized by this pretreatment. In support of this conclusion, pretreatment with essential oils from J. seravschanica cones (containing 16.8% cedrol) or pure (+)-cedrol inhibited human neutrophil chemotaxis to N-formyl peptide. Finally, reverse pharmacophore mapping predicted several potential kinase targets for cedrol. Thus, our studies have identified cedrol as a novel neutrophil agonist that can desensitize cells to subsequent stimulation by N-formyl peptide.

Integrated computational analysis on some Indolo-quinoline derivatives for the development of novel antiplasmodium agents: CoMFA, Pharmacophore mapping, molecular docking and ADMET studies

Background: The development of multi-resistant strains of the Plasmodium parasite has become a global problem. Therefore, designing of new antimalarial agents is an exclusive solution.: Objective: To improve the activity and identify potentially efficacious new antimalarial agents, integrated computational perspectives such as pharmacophore mapping, 3D-QSAR and docking study have been applied to a series of indolo-quinoline derivatives. Methods: The pharmacophore mapping generated various hypotheses based on key functional features and the best hypothesis ADRRR_1 revealed that indolo-quinoline scaffold is essential for antimalarial activity. 3D-QSAR model was established based on CoMFA and CoMSIA models by using 30 indolo-quinoline analogues as training set and the rest of 19 as test set. Results: The molecular field analysis (MFA) with PLS (partial least-squares) method was used to develop significant CoMFA (q2=0.756, r2=0.996) and CoMSIA (q2=0.703, r2=0.812) models. The CoMFA and CoMSIA models showed good predictive ability with r2pred values of 0.9623 and 0.9214 respectively. Docking studies were performed by using pfLDH to identify structural insight into the active site and results signify that the quinoline nitrogen acts as a hydrogen bond acceptor region to facilitate interaction with Glu122. Finally, designed molecules were screened through the ADMET tool to evaluate the pharmacokinetic and drug-likeness parameters. Conclusion: Thus, these studies suggested that established models have good predictability and would help in the optimization of newly designed molecules that may produce potent antimalarial activity.

Integrated Transcriptomics and Reverse Pharmacophore Mapping-based Network Pharmacology to Explore the Mechanisms of Natural Compounds against Doxorubicin-induced Cardiotoxicity

Background: Doxorubicin-induced cardiotoxicity (DIC) has greatly limited the clinical benefits of this frontline drug in oncotherapy. Drug combination with natural compounds (NCs) that possess potency against DIC is considered as a promising intervention strategy. However, the mechanisms of action (MoAs) underlying such drug interactions remain poorly understood. The aim of this study was to systematically pursuit of the molecular mechanisms of NCs against DIC. Methods: First, the gene expression signatures of DIC were characterized from transcriptomics datasets with doxorubicin-treated and untreated cardiomyocytes using differentially expressed gene identification, functional enrichment analysis, and protein-protein interaction network analysis. Secondly, reverse pharmacophore mapping-based network pharmacology was employed to illustrate the MoAs of 82 publicly reported NCs with anti-DIC potency. Cluster analysis based on their enriched pathways was performed to gain systematic insights into the anti-DIC mechanisms of the NCs. Finally, the typical compounds were validated using gene set enrichment analysis (GSEA) of the relevant gene expression profiles from a public gene expression database. Results: Based on their anti-DIC MoAs, the 82 NCs could be divided into four groups, which corresponded to ten MoA clusters. GSEA and literature evidence on these compounds were provided to validate the MoAs identified through this bioinformatics analysis. The results suggested that NCs exerted potency against DIC through both common and different MoAs. Conclusion: This strategy integrating different types of bioinformatics approaches is expected to create new insights for elucidating the MoAs of NCs against DIC.

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: from pharmacophore-based virtual screening to molecular dynamics

The lack of effective treatment remains the biggest bottleneck in combating the current novel coronavirus (COVID-19) pandemic. Drug discovery is a complex and time-consuming process, while various in silico methods dramatically reduce the time and cost of this process. The infection begins with the binding of the receptor-binding domain (RBD) of Spike (S) glycoprotein from SARS-CoV-2 to the host angiotensin-converting enzyme (ACE2) receptor. We, therefore, present computational screening methods aimed to identify inhibitors potentially able to target RBD. For this purpose, pharmacophore mapping, molecular docking, and molecular dynamics (MD) simulations were performed to screen potential candidates against ACE2/SARS-CoV-2. In particular, pharmacophore-based virtual screening used over a hundred million compounds to construct protein-protein interactions (PPIs) inhibitor library. In conclusion, PubChem-84280085 compound is suggested as a potential PPIs inhibitor for preventing SARS-CoV-2 RBD/ACE2 interactions.