Anti-nociceptive and Anti-inflammatory Activities of Asparacosin A Involve Selective Cyclooxygenase 2 and Inflammatory Cytokines Inhibition: An in-vitro, in-vivo, and in-silico Approach

Triterpenes possess anti-inflammatory and anti-nociceptive effects. In this study anti-inflammatory activities of Asparacosin A were evaluated' using in-vitro cyclooxygenases 1 and 2 (COX-1/2) inhibition assays. Moreover, anti-nociceptive activities were assessed in-vivo by carrageenan-induced paw edema test, xylene-induced ear edema tests, and acetic acid-induced writhing and formalin tests. Additionally molecular docking was conducted to elucidate the binding mechanism of the compound and to correlate the in-vitro findings with the in-silico data. Oral administration of Asparacosin A at the doses of 10, 20, and 40 mg/kg induced significant anti-inflammatory effects (*p < 0.05, **p < 0.01, and ***p < 0.001) in a dose-dependent manner in both models. Asparacosin A also inhibited the human recombinant COX-2 enzyme and caused a dose-dependent decrease in the levels of TNF-α, IL-1β, and PGE2 in the carrageenan-induced paws. Moreover, Asparacosin A displayed significant anti-nociceptive effects (*p < 0.05, **p < 0.01, ***p < 0.001) at the doses of 10, 20, and 40 mg/kg in acetic-acid induced writhing test. However, in formalin test, Asparacosin A (10–40 mg/kg, p.o) produced anti-nociceptive effects only in the late phase, similar to the effect observed with the reference drug celecoxib (50 mg/kg, p.o). Molecular docking was carried out on both COX-1 and COX-2 structures which revealed that Asparacosin A targets allosteric binding site similar to the binding mode of the selective COX inhibitor. In conclusion, Asparacosin A exhibits anti-inflammatory and peripheral anti-nociceptive activities which are likely mediated via inhibition of COX-2 enzyme and inflammatory cytokines. Furthermore, Asparacosin A can serve as a model to obtain new and more selective potent anti-inflammatory and anti-nociceptive drugs

In Silico Prediction of Novel Inhibitors of SARS-CoV-2 Main Protease through Structure-Based Virtual Screening and Molecular Dynamic Simulation

The unprecedented pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening global health. SARS-CoV-2 has caused severe disease with significant mortality since December 2019. The enzyme chymotrypsin-like protease (3CLpro) or main protease (Mpro) of the virus is considered to be a promising drug target due to its crucial role in viral replication and its genomic dissimilarity to human proteases. In this study, we implemented a structure-based virtual screening (VS) protocol in search of compounds that could inhibit the viral Mpro. A library of >eight hundred compounds was screened by molecular docking into multiple structures of Mpro, and the result was analyzed by consensus strategy. Those compounds that were ranked mutually in the ‘Top-100’ position in at least 50% of the structures were selected and their analogous binding modes predicted simultaneously in all the structures were considered as bioactive poses. Subsequently, based on the predicted physiological and pharmacokinetic behavior and interaction analysis, eleven compounds were identified as ‘Hits’ against SARS-CoV-2 Mpro. Those eleven compounds, along with the apo form of Mpro and one reference inhibitor (X77), were subjected to molecular dynamic simulation to explore the ligand-induced structural and dynamic behavior of Mpro. The MM-GBSA calculations reflect that eight out of eleven compounds specifically possess high to good binding affinities for Mpro. This study provides valuable insights to design more potent and selective inhibitors of SARS-CoV-2 Mpro

Rational Design of Novel Inhibitors of α-Glucosidase: An Application of Quantitative Structure Activity Relationship and Structure-Based Virtual Screening

α-Glucosidase is considered a prime drug target for Diabetes Mellitus and its inhibitors are used to delay carbohydrate digestion for the treatment of diabetes mellitus. With the aim to design α-glucosidase inhibitors with novel chemical scaffolds, three folds ligand and structure based virtual screening was applied. Initially linear quantitative structure activity relationship (QSAR) model was developed by a molecular operating environment (MOE) using a training set of thirty-two known inhibitors, which showed good correlation coefficient (r2 = 0.88), low root mean square error (RMSE = 0.23), and cross-validated correlation coefficient r2 (q2 = 0.71 and RMSE = 0.31). The model was validated by predicting the biological activities of the test set which depicted r2 value of 0.82, indicating the robustness of the model. For virtual screening, compounds were retrieved from zinc is not commercial (ZINC) database and screened by molecular docking. The best docked compounds were chosen to assess their pharmacokinetic behavior. Later, the α-glucosidase inhibitory potential of the selected compounds was predicted by their mode of binding interactions. The predicted pharmacokinetic profile, docking scores and protein-ligand interactions revealed that eight compounds preferentially target the catalytic site of α-glucosidase thus exhibit potential α-glucosidase inhibition in silico. The α-glucosidase inhibitory activities of those Hits were predicted by QSAR model, which reflect good inhibitory activities of these compounds. These results serve as a guidelines for the rational drug design and development of potential novel anti-diabetic agents

In-silico designing and characterization of binding modes of two novel inhibitors for CB1 receptor against obesity by classical 3D-QSAR approach

Obesity is the fifth primary hazard for mortality in the world; hence different therapeutic targets are explored to overcome this problem. Endocannabinoid is identified as the emerging target for the treatment of obesity as Cannabinoid 1 (CB1) receptor over-activation resulted in abdominal obesity. Potent antagonists or inverse agonists for CB1 receptor are the new strategies to develop anti-obesity drugs. Here, ligand-based 3D-QSAR studies was performed on 100 analogues belonging to a class of 1,2,4-tirazole containing diarylpyrazolylcarboxamide as CB1 receptor antagonists. We developed three CoMFA models using different charge schemes, AM1BCC, Gasteiger-Huckle and MMFF. These models produced almost similar statistical results (q2cv = 0.725, 0.692, 0.719 and r2ncv = 0.929, 0.924, 0.928 for AM1BCC, Gasteiger-Huckle and MMFF, respectively). The said models were validated through 20 external test set compounds which resulted in significant r2pred values (r2pred = 0.747, 0.743 and 0.745 for AM1BCC, Gasteiger-Huckle and MMFF, respectively). Comparatively, AM1BCC model provided slightly better statistics among all three tested charges scheme models, hence AM1BCC model was further utilized to generate CoMSIA models considering different field combinations. The best selected CoMSIA model also produced substantial q2cv = 0.788, r2ncv = 0.916 and r2pred = 0.836 values. Furthermore, two new molecules were designed by modifying the same scaffolds on the basis contour map analysis. The activities of newly designed molecules were predicted through obtained CoMFA model ranked as better than their parent molecules. Moreover, these newly designed compounds were successfully docked on the complex crystal structure of CB1 receptor (PDB ID: 5XRA). The docked conformation of these newly designed inhibitor interacted with Ser173, His178, Lys192, Thr197 and Ser383 mainly by hydrophobic and pi-pi stacking interactions. The obtained results signify the potential of the developed model; suggesting that the models can be useful to test and design potent novel CB1 receptor antagonists or inverse agonists prior to the synthesis

Attenuation of spatial memory in 5xFAD mice by targeting cholinesterases, oxidative stress and inflammatory signaling using 2-(hydroxyl-(2-nitrophenyl)methyl)cyclopentanone

Alzheimer's disease (AD) is classified pathologically as a progressive neurological disorder associated with memory decline. The study was designed to assess the underlying molecular signaling involved in the neuroprotective effect of the 2-(hydroxyl-(2-nitrophenyl)methyl)cyclopentanone (2NCP) as a novel therapeutic agent for AD. In this connection, in vitro cholinesterases inhibitory and antioxidant activities were investigated. In vivo studies were carried out on a well-known 5xFAD mice model in different behavioural models such as light/dark box,balance beam, rotarod, elevated plus maze (EPM),novel object recognition (NOR), paddling Y-maze, and Morris water maze (MWM) tests. Hippocampus (HC) and frontal cortex (FC) homogenates were examined for acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activities, 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radicals, glutathione S-transferase (GST), glutathione (GSH), and catalase. Further, we examined the expression of inflammatory cytokines and Nrf2 in the HC and FC through RT-PCR. Computational studies were conducted to predict the binding mode of the 2NCP with target sites of nuclear factor-κB (NF-κB) and cholinesterases. The findings of in vitro assays revealed that the IC50 values of the 2NCP against AChE and BChE were 17 and 23 µg/ml respectively. DPPH antioxidant assay displayed an IC50 value for the 2NCP was 62 µg/ml. Whereas, theex vivo study depicted that the activities of AChE and BChEwere significantly reduced. Moreover, free radicals load, GSH level, catalase and GST activities were significantly declined. Furthermore, in vivostudies showed that the 2NCP treated animals exhibited gradual memory improvement and improved motor functions. RT-PCR study revealed that mRNA levels of the inflammatory mediators (IL-1β, IL-6, TNF-α) were significantly reduced, while the expression of antioxidant Nrf2 was significantly increased.The molecular docking studies further confirmed that the 2NCP showed excellent binding affinities for NF-κB and cholinesterases. Taken together, the 2NCP improves spatial memory and learning, short- and long-term memory,markedly inhibits cholinesterases, reduced neuroinflammation, and mitigated oxidative stress in the 5xFAD mice; hence the 2NCP may be a potential candidate for the management of AD

3D Structure Prediction of Human β1-Adrenergic Receptor via Threading-Based Homology Modeling for Implications in Structure-Based Drug Designing

<div><p>Dilated cardiomyopathy is a disease of left ventricular dysfunction accompanied by impairment of the β₁-adrenergic receptor (β₁-AR) signal cascade. The disturbed β₁-AR function may be based on an elevated sympathetic tone observed in patients with heart failure. Prolonged adrenergic stimulation may induce metabolic and electrophysiological disturbances in the myocardium, resulting in tachyarrhythmia that leads to the development of heart failure in human and sudden death. Hence, β₁-AR is considered as a promising drug target but attempts to develop effective and specific drug against this tempting pharmaceutical target is slowed down due to the lack of 3D structure of <i>Homo sapiens</i> β₁-AR (<i>hs</i>βADR1). This study encompasses elucidation of 3D structural and physicochemical properties of <i>hs</i>βADR1 <i>via</i> threading-based homology modeling. Furthermore, the docking performance of several docking programs including Surflex-Dock, FRED, and GOLD were validated by re-docking and cross-docking experiments. GOLD and Surflex-Dock performed best in re-docking and cross docking experiments, respectively. Consequently, Surflex-Dock was used to predict the binding modes of four <i>hs</i>βADR1 agonists. This study provides clear understanding of <i>hs</i>βADR1 structure and its binding mechanism, thus help in providing the remedial solutions of cardiovascular, effective treatment of asthma and other diseases caused by malfunctioning of the target protein.</p></div

Structure-based small inhibitors search combined with molecular dynamics driven energies for human programmed cell death-1 (PD-1) protein

Human immune system is specialized in distinguishing normal cells from foreign particles mainly through proteins expressed on immune cells called ‘checkpoints’. Immune checkpoints work as a switch to activate and deactivate immune responses. T cells express one of the immune checkpoint, human programmed cell death-1 (PD-1), which normally operates as an off-switch function to protect the normal cell from T-cell attack. Binding of PD-1 to its ligand, the programmed cell death ligand (PD-L1/2) expressed on myeloid/cancer cells, induce downstream inhibitory signals, leading to tumor immune evasion. Targeting PD-1 or PD-L1 can boost the immune response against cancer cells. To design novel small molecule inhibitors for the PD-1, in silico structure-based screening on pharmacophoric points and molecular docking were performed. Based on the docking score and significant binding interaction with the crucial residues of PD-1 (Thr59, Glu61, Ser62, Glu84, Arg86 and Ala132), compounds were selected from the ZINC20 database, and their dynamic behavior and conformational stability were examined through molecular dynamic simulations. Besides, the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method was used to calculate the binding strength of each selected inhibitor complexed with PD-1. The binding energy calculations revealed that these selected inhibitors show a considerable affinity for PD-1. The selected novel inhibitors exhibit excellent drug-like and pharmacokinetic properties (absorption, distribution, metabolism, excretion and toxicity). In conclusion, the identified novel compounds (ZINC1443480030, ZINC1002854123, ZINC988238128, ZINC1481242350, ZINC1001739421, ZINC1220816434 and ZINC1167786692) from the current study can be validated in-vitro as potential PD-1 inhibitors and for discovery of novel drugs against PD-1 in the future