Computer-aided identification of natural lead compounds as cyclooxygenase-2 inhibitors using virtual screening and molecular dynamic simulation

Insights into Metabolites Profiling and Pharmacological Investigation of Aconitum heterophyllum wall ex. Royle Stem through Experimental and Bioinformatics Techniques

The Aconitum genus is a leading source of a wide range of structurally diverse metabolites with significant pharmacological implications. The present study investigated metabolite profiling, pharmacological investigation, anticancer potential, and molecular docking analysis of the stem part of Aconitum heterophyllum (AHS). The metabolite profiling of the AHS extract was experimentally examined using LC-MS/MS-orbitrap in both modes (ESI+/ESI-) and GC-MS in EI mode. The in vitro MTT model was used to study the anticancer potential, while the in vivo animal model was used to study the anti-inflammatory and antinociceptive activities. The MOE software was used for the molecular docking study. A total of 118 novel and previously known metabolites, among 44 metabolites (26 in ESI+ positive mode and 18 in ESI- negative mode) in the MeOH extract, while 74 metabolites (46 in ESI+ and 28 in ESI- mode) were identified in the n-hexane extract via LCMS/MS. The identified metabolites include 24 phenolic compounds, 18 alkaloids, 10 flavonoids, 24 terpenoids, 2 coumarins, 2 lignans, and 38 other fatty acids and organic compounds. The major bioactive metabolites identified were hordenine, hernagine, formononetin, chrysin, N-methylhernagine, guineesine, shogaol, kauralexin, colneleate, zerumbone, medicarpin, boldine, miraxinthin-v, and lariciresinol-4-O-glucoside. Furthermore, the GC-MS study helped in the identification of volatile and nonvolatile chemical constituents based on the mass spectrum and retention indices. The methanol extract significantly inhibited tumor progression in H9c2 and MDCK cancer cells with IC50 values of 186.39 and 199.63 μg/mL. In comparison, the positive control aconitine exhibited potent IC50 values (132.32 and 141.58 μg/mL) against H9c2 and MDCK cell lines. The anti-inflammatory (carrageenan-induced hind paw edema) and antinociceptive (acetic acid-induced writhing) effects were significantly dose-dependent, (p < 0.001) and (p < 0.05), respectively. In addition, a molecular docking study was conducted on identified ligands against the anti-inflammatory enzyme (COX-2) (PDB ID: 5JVZ) and the cancer enzyme ADAM10 (PDB ID: 6BDZ) which confirmed the anti-inflammatory and anticancer effects in an in silico model. Among all ligands, L2, L3, and L7 exhibit the most potent potential for inhibiting COX-2 inflammation with binding energies of -7.3424, -7.0427, and -8.3562 kcal/mol. Conversely, against ADAM10 cancer protein, ligands L1, L4, L6, and L7, with binding energies of -8.0650, -7.7276, -7.0454, and -7.2080 kcal/mol, demonstrated notable effectiveness. Overall, the identified metabolites revealed in this AHS research study hold promise for discovering novel possibilities in the disciplines of chemotaxonomy and pharmacology.

Molecular docking, 3D-QSAR and simulation studies for identifying pharmacophoric features of indole derivatives as 17β-hydroxysteroid dehydrogenase type 5 (17β-HSD5) inhibitors

Excess of androgens leads to various diseases such as Poly-Cystic Ovarian Syndrome, Prostate Cancer, Hirsutism, Obesity and Acne. 17β-Hydroxysteroid Dehydrogenase type 5 (17β-HSD5) converts androstenedione into testosterone peripherally, thereby significantly contributing to the development of these diseases. Indole-bearing scaffolds are reported as potential 17β-HSD5 inhibitors for the manifestation of diseases arising due to androgen excess. In the present work, we have extensively performed a combination of molecular docking, Gaussian field-based 3D-QSAR, Pharmacophore mapping and MD-simulation studies (100 ns) to identify the pharmacophoric features of indole-based compounds as potent 17β-HSD5 inhibitors. Molecular simulation studies of the most potent compound in the binding pocket of enzyme revealed that the compound 11 was stable in the binding pocket and showed good binding affinity through interactions with various residues of active site pocket. The Molecular mechanics Generalized Born surface area continuum solvation (MM/GBSA) and Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations revealed that the compound 11 possessed a free binding energy of -36.36 kcal/mol and -7.00 kcal/mol, respectively, which was better as compared to reference compound Desmethyl indomethacin (DES). The developed pharmacophore will be helpful to design novel indole-based molecules as potent 17β-HSD5 inhibitors for the treatment of various androgenic disorders.Communicated by Ramaswamy H. Sarma.

Comparison of various methods for validity evaluation of QSAR models

BACKGROUND

Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature.

METHODS

In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed.

RESULTS

The findings revealed that employing the coefficient of determination (r²) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies.

CONCLUSION

This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.

Molecular dynamics and 3D-QSAR studies on indazole derivatives as HIF-1α inhibitors

Hypoxia-inducible factor (HIF) is a transcriptional factor which plays a crucial role in tumour metastasis thereby responsible for development of various forms of cancers. Indazole derivatives have been reported in the literature as potent HIF-1α inhibitor via interaction with key residues of the HIF-1α active site. Taking into consideration the role HIF-1α in cancer and potency of indazole derivative against HIF-1α; it was considered of interest to correlate structural features of known indazole derivatives with specified HIF-1α inhibitory activity to map pharmacophoric features through Three-dimensional quantitative structural activity relationship (3D-QSAR) and pharmacophore mapping. Field and Gaussian based 3D-QSAR studies were performed to realize the variables influencing the inhibitory potency of HIF-1α inhibitors. Field and Gaussian- based 3D-QSAR models were validated through various statistical measures generated by partial least square (PLS). The steric and electrostatic maps generated for both 3D-QSAR provide a structural framework for designing new inhibitors. Further; 3D-maps were also helpful in understanding variability in the activity of the compounds. Pharmacophore mapping also generates a common five-point pharmacophore hypothesis (A₁D₂R₃R₄R₅_4) which can be employed in combination with 3D-contour maps to design potent HIF-1α inhibitors. Molecular docking and molecular dynamics (MD) simulation of the most potent compound 39 showed good binding efficiency and was found to be quite stable in the active site of the HIF-1α protein. The developed 3D-QSAR models; pharmacophore modelling; molecular docking studies along with the MD simulation analysis may be employed to design lead molecule as selective HIF-1α inhibitors for the treatment of Cancer.

Synthesis of novel 3,5,6-trisubstituted 2-pyridone derivatives and evaluation for their anti-inflammatory activity

The inflammatory response is the reaction of living tissue to an injury of a foreign nature, such as infection and irritants, and occurs as part of the body's natural defence response. Compounds capable of inhibiting cyclooxygenase (COX) enzymes, especially COX-2, have great potential as anti-inflammatory agents. Herein we present the regioselective synthesis of 49 novel compounds based on the 2-pyridone nucleus. The topical anti-inflammatory activity of seventeen compounds was evaluated in mice by croton oil (CO) induced ear edema assay. Most of the compounds exhibited a high level of in vivo anti-inflammatory activity, reducing ear edema and myeloperoxidase (MPO) activity. The most active compounds (2a and 7a) were inhibitors of COX enzymes. Compound 2a selectively inhibited the COX-2, while 7a was nonselective. Further, the compound 2a showed effective binding at the active site of COX-2 co-crystal by docking molecular study.

Pharmacophore development, drug-likeness analysis, molecular docking, and molecular dynamics simulations for identification of new CK2 inhibitors

Protein kinase 2 (CK2), an essential serine/threonine casein kinase, is considered an interesting target for cancer treatments. Different molecular modeling approaches such as pharmacophore modeling, molecular docking, and molecular dynamics simulations have been used to develop new CK2 inhibitors. This study presents a pharmacophore model that was generated by combining and merging the structure-based and ligand-based pharmacophore features and validated using receiver operating characteristic (ROC). Based on validation results revealing good predictive ability, this pharmacophore model was used as a three-dimensional query in a virtual screening simulation. Several compounds with different chemical scaffolds were retrieved as hits, which were further analyzed and refined using several molecular property filters. The obtained compounds were then filtered and compared to the crystallographic ligand on the basis of their predicted docking energies, binding mode, and interactions with CK2 active site residues. This step resulted in a compound with a high pharmacophore fit value and better docking energy. Molecular dynamics simulation indicated stable binding of the predicted compound to CK2 protein, characterized by root mean square deviation (RMSD) and root mean square fluctuation (RMSF) and hydrogen bond. Graphical abstract.

Identification of new potential cyclooxygenase-2 inhibitors: insight from high throughput virtual screening of 18 million compounds combined with molecular dynamic simulation and quantum mechanics

The cyclooxygenase isoenzymes (COX-1 and COX-2) have a critical role in inflammation, fever, and pain. In contrary to COX-1, COX-2 is specifically expressed in inflamed tissues. Because of the subtle difference between both enzyme active sites, targeting COX-2 represents an efficient strategy for the development of novel inhibitors against inflammation with fewer side effects. In order to identify potential inhibitors of COX-2, more than 18,000,000 small molecules were retrieved from the ZINC database and virtually screened against it with a gradual increase in the precision through combined multistep docking. The results were sorted according to the rank-by-rank, induced-fit docking, and MM-GBSA evaluation. Subsequently from the final hit list, two top hits along with an approved selective inhibitor (celecoxib) were further investigated by the molecular dynamics (MD) simulations. The results were indicated that ZINC16934653 and ZINC40484701 demonstrate the highest affinity for the COX-2 binding pocket. Both ligands were bound to the important active-site residues, which are necessary for the correct orientation of inhibitors inside the binding cavity. Their binding free energies were comparable to celecoxib. 100 ns MD simulation is revealed that ZINC40484701 is more preferred in comparison with ZINC16934653 and celecoxib. In addition, non-covalent interactions between the compounds and key residues located in 6 Å distance from the COX-2 binding site show similar patterns of bonding by the reduced density gradient and the independent gradient model. Therefore, ZINC40484701 can be a potential candidate for further in vitro and in vivo analysis after lead-optimization efforts.Communicated by Ramaswamy H. Sarma.

QSAR Classification-Based Virtual Screening Followed by Molecular Docking Identification of Potential COX-2 Inhibitors in a Natural Product Library

Developments of natural inhibitors to prevent the function of cyclooxygenase-2 (COX-2) protein, responsible for a variety of inflammations and cancers, are a major challenge in the scientific community. In this study, robust QSAR classification models for predicting COX-2 inhibitor were developed, by which the self-organizing feature map neural network and random forest (RF) were adopted to improve the prediction of classification model ability. The F-score-based criterion combined with RF was used for feature selection, and good performance for COX-2 inhibitor prediction in overall accuracy was demonstrated. We used this model as a virtual screening tool for identifying the potential COX-2 inhibitor from a natural product library and found potential hit compounds. This compound further screened by applying molecular docking simulation identified five potential hits such as osthole, kavain, vanillyl acetone, myristicin, and psoralen, having a comparable binding affinity to COX-2 protein. However, in cell experiment, three hit compounds revealed COX-2 inhibitory activity in mRNA and protein level such as osthole, kavain, and psoralen.