Letters in Drug Design & Discovery - Volume 18, Issue 10, 2021

Background: SARS-CoV-2, a novel coronavirus that caused a pandemic respiratory disease, has recently emerged from China. Since it is a life-threatening virus, investigation of curative medications along with protective vaccines still maintains its importance. Drug repurposing is a reasonable and immediate approach to combat SARS-CoV-2 infection by identifying inhibitory molecules from marketed drugs. PL protease (PL^pro) is one of the essential enzymes for the progression of SARS-CoV-2 replication and life cycle. Objective: We aimed to investigate the potential of 4 HCV protease inhibitors as probable repurposing drugs in Covid-19 treatment. Methods: In order to understand possible binding affinity of HCV protease inhibitors, Boceprevir, Grazoprevir, Simeprevir, and Telaprevir, against PL^pro, we performed docking analysis in silico. Docking study was accomplished using AutoDock 4.2 Software. Potential druggable pockets on PL^pro were predicted by DoGSiteScorer tool in order to explore any overlapping with binding regions and these pockets. Results: This analysis demonstrated Boceprevir, Grazoprevir, Simeprevir and Telaprevir interacted by PL^pro with binding energies (kcal/mol) of -4.97, -4.24, -6.98, -1.08, respectively. Asn109, one of the interacted residues with both Boceprevir and Simeprevir, is a neighbouring residue to catalytic Cys111. Additionally, Telaprevir notably interacted with catalytic His272 in the active site. Conclusion: Present study explains the binding efficiency and repurposing potential of certain HCV protease inhibitors against to SARS-CoV-2 PL^pro enzyme. Docking sites and potential druggability of ligands were also crosschecked by the estimation of druggable pockets. Thereby our results can promote promising preliminary data for research on drug development in the fight of Covid-19.

Background: Kinases are proteins that control many biological functions. They are involved in cellular regulation, and many of them are deregulated in cancer proliferation. The evidence of this deregulation in many pathologies served as the origin of kinases as a therapeutic class and constitutes the motive that leads numerous teams to search for inhibitors of these targets. Objective: Based on 3D-QSAR studies and the molecular docking approach, we have developed new potential inhibitors that could be optimized and transformed into colon cancer drugs. Methods: To design new bioactive molecules and study their interactions with the cyclin-dependent kinase type 2 (CDK2) enzyme, we used two virtual screening methods: 3D-QSAR modeling and molecular docking on a series of 28 pyrimidine-based benzothiazole derivatives. Results: To develop the model (3D QSAR), we used CoMFA and CoMSIA techniques using SYBYLX2.0 molecular modeling software. The statistical parameters reveal that the good CoMFA model displays Q² = 0.587 and R²= 0.895 and CoMSIA displays Q² = 0.552 and R² = 0.768), which are considered to be very good internal prediction values, while an external validation of a test series of 5 compounds not included in the model development series gives R² test values of 0.56 for CoMFA and R² t est values of 0.51 for CoMSIA. The molecular docking approach with AutoDock Tools-1.5.6 is introduced in this work to enrich the interpretations extracted from the CoMFA and CoMSIA contour maps and to provide an in silico research method for the most favorable mode of interaction of an inhibitor within its receptor (CDK2). Conclusion: We have constructed and validated a quantitative 3D model of structure-activity relationships of pyrimidine-based benzothiazole derivatives as CDK2 inhibitors. This model allows us to identify the nature and position of the groups that enhance the activity, giving us directions to discover new, more powerful molecules in a limited time.

Background: Frankincense has been used as a traditional medicine in many countries. It is an important herb with multiple targets and therapeutic effects, including liver protection. However, its mechanism of action in drug-induced liver injury (DILI) remains unknown. Objective: The purpose of this work was to elucidate the active components, core genes, and molecular mechanism of frankincense in DILI through network pharmacology and molecular docking approaches. Methods: The active components of frankincense and its target genes were obtained from the BATMAN-TCM database, and the DILI target genes were obtained from the GeneCards and Drug- Bank databases. Cytoscape was used to create the compound-shared gene target network. STRING and DAVID software were used to analyze key targets and pathway enrichment. Autodock Vina software was used for molecular docking. Results: Network analysis identified 16 compounds in frankincense and 103 target genes highly related to DILI. The core genes in the protein-protein interaction network are INS, IL6, TP53, TNF, SRC, PTGS2, IL1B, CAT, IL10, and IGF1. Furthermore, GO and KEGG pathway enrichment analyses indicated that the effect of frankincense on DILI is related to positive regulation of transcription from RNA polymerase II promoter and inflammatory response. Core pathways such as the HIF-1, TNF, FoxO, PI3K-Akt, and the sphingolipid signaling pathway are closely related to DILI. Conclusion: This study revealed the chemical constituents and pharmacological effects of frankincense and unveiled potential DILI healing targets. This study could provide insights for further development of drugs that specifically target DILI.

Background: Parkinson’s Disease (PD) is characterized by the aggregation of α- synuclein, formation of Lewy bodies and the selective loss of dopaminergic neurons of mesencephalic substantia nigra pars compacta (SNC) with the debilitating motor symptoms. Introduction: The available treatment for PD provides symptomatic relief with no control over the progression of the disease. The treatment is also associated with several side effects. As neurodegeneration in PD is also associated with oxidative stress, antioxidants from plants could play an important role in reducing PD symptoms. With this aim, we decided to study the effect of Lemongrass extract (LGE) on the transgenic Drosophila model of PD expressing human alpha synuclein in the neurons. Methods: The PD flies were allowed to feed on different doses of LGE established in diet for 24 days and then assayed for climbing ability and oxidative stress markers. The molecular docking study was also performed for citral (the component of the extract) and human α-synuclein. Results and discussion: A dose dependent significant improvement in the climbing ability and reduction in oxidative stress was observed in the PD flies exposed to LGE. In our earlier study on LGE, citral was found to be the main component of the extract by GC-MS analysis. The docking results also support the positive interaction between citral and human α-synuclein. Conclusion: The results suggest that LGE is potent in reducing the PD symptoms being mimicked in transgenic Drosophila.

Background: The frequent use of antimicrobial agents to treat infections in diabetic patients make them more drug resistant than non-diabetic patients, which accounts for a higher mortality rate of diabetic patients. Therefore, it is a necessity today to synthesize new drugs with dual modes of action as antidiabetic and antibacterial agents. In the present work, new derivatives containing thiazolidinedione and 1,3,4-oxadiaozle have been synthesized and screened for PPAR-γ and antibacterial activities. Methods: Compounds 5-12 have been synthesized from 2-methoxy benzaldehyde and thiazolidinedione and characterized using different spectroscopic techniques such as IR, NMR, and mass spectrometry. These compounds were tested for in vitro PPAR-γ transactivation, PPAR-γ gene expression, and antibacterial activities. Finally, molecular docking was carried out to see the binding interactions of molecules with the target protein. Results: All the compounds follow the Lipinski rule suggesting the synthesized derivatives have good drug-likeness properties. Compounds 11 and 12 exhibited promising PPAR-γ transactivation with 73.69% and 76.50%, respectively, as well as showed significant antibacterial activity with comparable MIC of 3.12 μg/disc to standard drug amoxicillin. The docking result was found to be consistent with the in vitro PPAR-γ transactivation results. Conclusion: Compounds 11 and 12 can be further investigated as lead molecules for the development of new and effective antidiabetic and antibacterial agents.

Background: Cancer is a multifactorial disease with multiple complications involving multiple proteins. Breast cancer is the most prevalent form of cancer among women. The pathophysiology of this cancer form has implicated several genetic alterations in its hallmark. Two of the most studied breast cancer molecular pathways are the cell cycle protein kinases and P13/AKT signaling pathway. Objective: Thus, this study identified novel inhibitors through computational screening of a library of medicinal plant compounds against cyclin-dependent kinase 2 (CDK2), phosphoinositide-3-kinase A (PI3Ka) and protein kinase B (AKT1). Methods: Rigid protein docking via Glide algorithm was applied to identify the hits from 3000 plant compounds screened against three drug targets involved in breast cancer pathogenesis. A more accurate and reliable ligand-protein docking called induced fit docking was adopted to extensively improve the scoring function by ranking favourable binding as top-scoring one. Results: Nine hit compounds were identified and found to interact with essential residues at the proteins’ binding sites. Subsequently, the hits pharmacokinetic parameters and toxicity were predicted to determine their potential as drug candidates and minimise toxic effects. The hit compounds were found to be non-carcinogenic, and five of them showed a desirable drug-like property. The built predictive QSAR models with an R2 value of 0.7684, 0.7973 and 0.5649 for CDK2, AKT1 and PI3Ka, respectively, were adopted to determine the hits inhibitory activity (pIC50) against the screened proteins; and the predictions revealed compounds with significant activity. Prediction of the hit compounds druglikeness, pharmacokinetic and toxicity properties by online web servers showed that the compounds are non-carcinogenic and showed moderate indices for ADMET parameters. The constructed QSAR models with reliable R2 coefficient value were used to predict the pIC50 of the selected compounds. The results revealed potent compounds with significant activity. Conclusion: This study thus provides insight into multi-target protein compounds which could be explored as chemotherapeutic alternatives in breast cancer treatment.