In Silico Pharmacology最新文献

Head and Neck Squamous Cell Carcinoma (HNSCC) is one of the most common form of cancer worldwide. It has high incidence and mortality rate making it one of the top causes of cancer related deaths. Tremendous efforts have being made towards treatment of HNSCC but still the overall survival rate hasn't improved much. Unregulated activation of Rho GTPase Ras-related C3 botulinum toxin substrate 1 or Rac1 has been reported in various tumor such as HNSCC, breast cancer, pancreatic cancer, etc. Rac1 is significant in activation and regulation of multiple signaling pathways and it's aberrant activation leads to uncontrolled proliferation, invasion and metastasis which contributes to the hallmarks of cancer. Therefore for treating proliferative disorders such as cancer, inhibition of Rac1 could be a viable approach. Rho GTPases were earlier considered "undruggable" due to their picomolar binding affinity for their guanine nucleotides. In addition presence of high micromolar concentrations of GDP (> 30 μm) and GTP (> 300 μm) in the cell, led to unsuccessful attempts in identification of potent or selective nucleotide competitive GTPase inhibitors. Therefore we identified small molecule inhibitors that target the GEF binding site of the Rho GTPase instead of nucleotide binding site by performing high throughput screening, molecular dynamics simulations, free energy calculations and protein-ligand interaction studies. As a result of this study, we identified four potential inhibitors against RAC1. This study provides a significant in-depth understanding of the Rho GTPases and can prove beneficial in the development of potential therapeutics against HNSCC.

Meclizine is antihistamine and is used in combination with pyridoxine to treat motion sickness. The in-silico study of meclizine prediction studied showed that meclizine has anti-eczema activity with possible activity 95. This research aimed to explore the anti-eczema activity of meclizine. Therefore, five formulations of meclizine ointment have been prepared using different bases (white base, simple ointment base, hydrophilic petrolatum base, hydrophilic, and emulsifying ointment bases). The efficiency of meclizine ointment has been evaluated by testing the physical compatibility and stability, homogeneity and irritant effect, absorbance and spreadability, chemical identification, calibration curve, drug content (assay), and dissolution test. This is followed by evaluating the ointment's effectiveness on volunteers and molecular docking. Five creams trials have been prepared, and two formulas (F3, and F5) have been selected for further evaluation. The formulas three and five (F3, F5) have passed the physical and chemical tests and showed compatibility, homogenous, absorbed, non-irritant, and stable with calibration curve (R = 0.9999). Then, the F3 formula was selected by testing them on seven volunteers after evaluating the irritant test. Four of the volunteers showed excellent recovery, and three of the volunteers suffered from uncomforting feelings and the formation of new pills. Therefore, F5 has been tested by eight volunteers that contain high oleaginous activity; five showed an excellent recovery, while three of the volunteers showed no difference. According to that, F5 is more efficient for eczema patients than F3, and Meclizine showed promising activity as an anti-eczema that requires further evaluation in the future.

Shen Qi Wan (SQW) prescription has been used to treat type 2 diabetes mellitus (T2DM) for thousands of years, but its pharmacological mechanism is still unclear. The network pharmacology method was used to reveal the potential pharmacological mechanism of SQW in the treatment of T2DM in this study. Nine core targets were identified through protein-protein interaction (PPI) network analysis and KEGG pathway enrichment analysis, which were AKT1, INSR, SLC2A1, EGFR, PPARG, PPARA, GCK, NOS3, and PTPN1. Besides, this study found that SQW treated the T2DM through insulin resistance (has04931), insulin signaling pathway (has04910), adipocytokine signaling pathway (has04920), AMPK signaling pathway (has04152) and FoxO signaling pathway (has04068) via ingredient-hub target-pathway network analysis. Finally, molecular docking was used to verify the drug-target interaction network in this research. This study provides a certain explanation for treating T2DM by SQW prescription, and provides a certain angle and method for researchers to study the mechanism of TCM in the treatment of complex diseases.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-022-00124-2.

Proline specific serine protease enzyme, dipeptidyl peptidase IV (DPP-4) has become a promising target for diabetes, as it stops glucagon-like peptide 1 (GLP-1) from becoming inactive, resulting in higher levels of active GLP-1. This lowers glucose levels by increasing insulin secretion and decreasing glucagon secretion. DPP-4 is also linked to a higher BMI and a 0.7 to 1% reduction in HbA1c. Currently available DPP-4 inhibitor drugs showed less promising anti-diabetic activity as this class associated with many side effects due to non-selectivity and therefore searching on more potent DPP-4 inhibitors are still ongoing. In our present study, we investigate the inhibition of DPP-4 through a series of antibiotic compounds which were previously reported to be used in diabetic foot infections and compared with existing DPP-4 inhibitors. To obtain this objective, three-dimensional crystal structure of DPP-4 was retrieved from the protein data bank (PDB id: 1 × 70). A systematic computational method combining molecular docking, MM-GBSA binding energy calculation, MD simulations, MM-PBSA binding free energy calculations and ADME were used to find best DPP-4 inhibitor. Molecular docking results revealed that clindamycin has a higher affinity towards the catalytic sides of DPP-4 and built solid hydrophobic and polar interactions with the amino acids involved in the binding region of DPP-4, such as S1 subsite, S2 subsite and S2 extensive subsite. MD simulations results showed clindamycin as potent virtual hit and suggested that it binds with DPP-4 in competitive manner, which virtually indicate that besides antibiotic activity clindamycin has anti-diabetic activity.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-021-00118-6.

Prostate cancer (CaP) is one of the most frequent malignancies amongst men. Enzalutamide is the second-generation potent androgen receptor (AR) antagonist used against metastatic and non-metastatic CaP. Unfortunately, the development of chemoresistance in cancer cells reduces the effectiveness of Enzalutamide. Lupeol is a pentacyclic triterpene found in different fruits, vegetables, and medicinal plants and possesses anti-inflammatory and anti-cancer properties. Here, we report in silico and in vitro studies of Lupeol and Enzalutamide against the β-CATENIN, c-FLIP_L, and c-MYC, which play a significant role in chemoresistance. We observed that Lupeol significantly inhibits the cell growth of chemoresistant Du145 cells and cancer stem cells (CSCs) either alone or in combination with Enzalutamide. Lupeol and Enzalutamide were also found to dock with β-CATENIN, c-FLIP_L, and c-MYC. The following MD simulation data showed both compounds exerting structural changes in these proteins. Finally, they significantly inhibit the transcriptional activity of all these genes, as observed by luciferase assay. Thus, we infer that Lupeol chemosensitizes the CaP cells for Enzalutamide-resistant CaP cells.

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One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-cancer drugs are often not selective and cause damage to healthy cells, leading to serious side effects for patients. For this reason more targeted therapeutics and drug delivery methods are being developed. The effectiveness of new treatments is initially determined via in vitro cell viability assays, which determine the ${\mathrm{IC}}_{50}$  of the drug. However, these assays are known to result in estimates of ${\mathrm{IC}}_{50}$  that depend on the measurement time, possibly resulting in over- or under-estimation of the ${\mathrm{IC}}_{50}$ . Here, we test the possibility of using cell growth curves and fitting of mathematical models to determine the ${\mathrm{IC}}_{50}$  as well as the maximum efficacy of a drug ( ${\epsilon }_{\max }$ ). We measured cell growth of MCF-7 and HeLa cells in the presence of different concentrations of doxorubicin and fit the data with a logistic growth model that incorporates the effect of the drug. This method leads to measurement time-independent estimates of ${\mathrm{IC}}_{50}$  and ${\epsilon }_{\max }$ , but we find that ${\epsilon }_{\max }$  is not identifiable. Further refinement of this methodology is needed to produce uniquely identifiable parameter estimates.

Glucokinase (GK) is an enzyme involved in synthesising glucose into glucose-6 phosphate and serves a crucial function in glucose sensing. Therefore, agents that induce GK activation could be used to treat T2DM. The present work has been carried out to investigate the GK activation potential of phytoconstituents of Enicostemma littorale through molecular docking. All the phytoconstituents have been screened through the Lipinski rule of 5, Veber's rule, and ADMET properties. From these initial screening, only Apigenin, Ferulic acid, Genkwanin, p-coumaric acid, Protocatechuic acid, Syringic acid, and Vanillic acid have been selected to perform molecular docking studies. The binding free energy and binding mode of the native ligand in the allosteric site of the enzyme have been considered the reference for the other molecules' validation. The native ligand has exhibited - 7.2 kcal/mol binding free energy, whereas; it has formed four hydrogen bonds with THR-228, LYS-169, ASP-78, and GLY-81. Based on these findings, the interactions of phytoconstituents have been justified. Apigenin, genkwanin, and swertiamarin exhibited - 8.7, - 7.5, and - 8.3 kcal/mol binding free energy, respectively, which indicates better enzyme activation than the native ligand. Swertiamarin has formed 08 hydrogen bonds with allosteric amino acid residues, which confirms the excellent enzyme activation by these phytoconstituents. We concluded that if we can isolate and consume the exact active phytoconstituents (GK activators) from this plant, we can use them effectively to treat T2DM. More GK activators can be developed by considering them as a natural lead moiety.

Objective of the present investigation comprised of the application of in silico methods to discover novel natural product (NP) based potential inhibitors for carbohydrate mediated diseases. Structure based drug design studies (molecular docking and structure based pharmacophore analysis)  were carried out on a series of natural product compounds to identify significant bioactive molecules to inhibit α-mannosidase (I and II) and β-galactosidase enzymes. Furthermore, protein ligand interaction fingerprint analysis, molecular dynamics simulations and molecular access system (MACCS) fingerprint analysis were performed to understand the binding behaviors of the studied molecules. The results derived from these analyses showed that the identified compounds exhibit significant binding interactions with the active site residues. The compounds, NP-51, NP-81 and NP-165 have shown significant docking score against the studied enzymes (α-mannosidases-I, α-mannosidases-II and β-galactosidases). The fingerprint studies showed that the presence of rings (aromatic or aliphatic) with sulfur atoms, nitrogen atoms, methyl groups, etc. have favorable effects on the α-mannosidase II inhibitory activity. However, the presence of halogen atoms substituted in the molecules have reduced inhibitory ability against α-mannosidase II. The compound, NP-165 has significant activity against both enzymes (α-mannosidases and β-galactosidases). These studies accomplished that the compounds identified through in silico methodologies can be used to develop semisynthetic derivatives of the glycosidase inhibitors and can be screened for the treatment of different carbohydrate mediated diseases.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-021-00115-9.

COVID-19 is a new communicable disease with a widespread outbreak that affects all populations worldwide triggering a rush of scientific interest in coronavirus research globally. In silico molecular docking experiment was utilized to determine interactions of available compounds with SARS-CoV-2 and angiotensin-converting enzyme 2 (ACE2) complex. Chimera and AutoDock Vina were used for protein-ligand interaction structural analysis. Ligands were chosen based on the known characteristics and indications of the drugs as ACE inhibitors (captopril, enalapril, quinapril, moexipril, benazepril, ramipril, perindopril, zofenopril, fosinopril), as ACE2 blockers (losartan, olmesartan), as blood thinning agent (clopidogrel), as cholesterol-lowering prescriptions (simvastatin, atorvastatin), repurposed medications (dexamethasone, hydroxychloroquine, chloroquine), and as investigational drug (remdesivir). Experimental ACE/ACE2 inhibitors are also included: Sigma ACEI, N-(2-aminoethyl)-1-aziridine-ethanamine (NAAE), nicotianamine (NAM), and MLN-4760 (ACE2 inhibitor). The best docked conformations were all located in the ACE2 protein, 50% docked at the interface with lower scores and only clopidogrel and hydroxychloroquine docked at the spike protein. Captopril, moexipril, benazepril, fosinopril, losartan, remdesivir, Sigma ACEI, NAA, and NAM interacted and docked at the interface of ACE2 and SARS-CoV-2 spike protein complex. This may have significant implication in enhancing our understanding of the mechanism to hinder viral entry into the host organism during infection.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-021-00114-w.

Pharmacophore modelling studies have been performed for a series of 2,4-disubstituted-pyrimidines derivatives as EGFR L858R/T790M tyrosine kinase inhibitors. The high scoring AARR.15 hypothesis was selected as the best pharmacophore model with the highest survival score of 3.436 having two hydrogen bond acceptors and two aromatic ring features. Pharmacophore-based virtual screening followed by structure-based yielded the six molecules (ZINC17013227, ZINC17013215, ZINC9573324, ZINC9573445, ZINC24023331 and ZINC17013503) from the ZINC database with significant in silico predicted activity and strong binding affinity towords the EGFR L858R/T790M tyrosine kinase. In silico toxicity and cytochrome profiling indicates that all the 06 virtually screened compounds were substrate/inhibitors of the CYP-3A4 metabolizing enzyme and were non-carcinogenic and devoid of Ames mutagenesis. Density functional theory (DFT) and molecular dynamic (MD) simulation further validated the obtained hits.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-021-00113-x.