Docking-based virtual screening of TβR1 inhibitors: evaluation of pose prediction and scoring functions

C ucumis melo compounds: A new avenue for ALR-2 inhibition in diabetes mellitus

Diabetes mellitus (DM) is a prominent contributor to morbidity and mortality in developed nations, primarily attributable to vascular complications such as atherothrombosis occurring in the coronary arteries. Aldose reductase (ALR2), the main enzyme in the polyol pathway, catalyzes the conversion of glucose to sorbitol, leading to a significant buildup of reactive oxygen species in different tissues. It is therefore a prime candidate for therapeutic targeting, and extensive study is currently underway to discover novel natural compounds that can inhibit it. Cucumis melo (C. melo) has a long history as a lipid-lowering ethanopharmaceutical plant. In this study, compounds derived from C. melo were computationally evaluated as possible lead candidates. Various computational filtering methods were employed to assess the drug-like properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiles of the compounds. The compounds were subsequently addressed to analysis of their interactions, molecular docking, and molecular dynamics simulation studies. When compared to the conventional therapeutic compounds, three compounds exhibited enhanced binding affinity and intra-molecular residue interactions, resulting in increased stability and specificity. Consequently, four potent inhibitors, namely PubChem CIDs 119205, 65373, 6184, and 332427, have been identified. These inhibitors exhibit promising potential as pharmacological targets for the advancement of novel ALR-2 inhibitors.

Identification of potentially high drug-like VEGFR2/c-Met dual-target type II kinase inhibitors with symmetric skeletons based on structural screening

Vascular endothelial growth factor receptor 2 (VEGFR2) and c-Mesenchymal epithelial transition factor (c-Met) are tyrosine kinase receptors associated with the occurrence of malignant tumors. Studies have shown that inhibition of VEGFR2 promotes a feedback increase in c-Met, a mechanism linked to the emergence of resistance to VEGFR2 inhibitors. Therefore, treatment targeting both VEGFR2 and c-Met will have better application prospects. In this study, hierarchical virtual screening was performed on ZINC15, Molport and Mcule-ULTIMATE databases to identify potential VEGFR2/c-Met dual inhibitors. Firstly, the best pharmacophore model for each target was used to cross-screen the three databases, and the compounds that could match the two pharmacophore models were then retained based on the Fit Value of the respective crystal ligands. Compounds ZINC, MOL, and MLB named after their database sources were retained by binding pattern analysis and docking assessment. ADMET predictions indicated that ZINC had significantly higher oral bioavailability compared to the approved drug cabozantinib. This is likely due to ZINC's unique symmetrical backbone with less structure complexity, which may reduce the occurrence of adverse effects. Molecular dynamics simulations and binding free energy analysis showed that all three hit compounds were able to stably bind at the active site, but only ZINC could form high occupancy of hydrogen bonds with both VEGFR2 and c-Met, and also only ZINC had a higher binding free energy than crystal ligands, suggesting that ZINC was the most likely potential VEGFR2/c-Met dual-target inhibitor. This finding provides a promising starting point for the development of VEGFR2/c-Met dual-target inhibitors.Communicated by Ramaswamy H. Sarma.

The Discovery of Indole-2-carboxylic Acid Derivatives as Novel HIV-1 Integrase Strand Transfer Inhibitors

As an important antiviral target, HIV-1 integrase plays a key role in the viral life cycle, and five integrase strand transfer inhibitors (INSTIs) have been approved for the treatment of HIV-1 infections so far. However, similar to other clinically used antiviral drugs, resistance-causing mutations have appeared, which have impaired the efficacy of INSTIs. In the current study, to identify novel integrase inhibitors, a set of molecular docking-based virtual screenings were performed, and indole-2-carboxylic acid was developed as a potent INSTI scaffold. Indole-2-carboxylic acid derivative 3 was proved to effectively inhibit the strand transfer of HIV-1 integrase, and binding conformation analysis showed that the indole core and C2 carboxyl group obviously chelated the two Mg2+ ions within the active site of integrase. Further structural optimizations on compound 3 provided the derivative 20a, which markedly increased the integrase inhibitory effect, with an IC50 value of 0.13 μM. Binding mode analysis revealed that the introduction of a long branch on C3 of the indole core improved the interaction with the hydrophobic cavity near the active site of integrase, indicating that indole-2-carboxylic acid is a promising scaffold for the development of integrase inhibitors.

Virtual screening for potential discoidin domain receptor 1 (DDR1) inhibitors based on structural assessment

Discoidin domain receptor 1 (DDR1) (EC Number 2.7.10.1) has recently been considered as a promising therapeutic target for idiopathic pulmonary fibrosis (IPF). However, none of the currently discovered DDR1 inhibitors have been included in clinical studies due to low target specificity or druggability limitations, necessitating various approaches to develop novel DDR1 inhibitors. In this study, to assure target specificity, a docking assessment of the DDR1 crystal structures was undertaken to find the well-differentiated crystal structure, and 4CKR was identified among many crystal structures. Then, using the best pharmacophore model and molecular docking, virtual screening of the ChEMBL database was done, and five potential molecules were identified as promising inhibitors of DDR1. Subsequently, all hit compound complex systems were validated using molecular dynamics simulations and MM/PBSA methods to assess the stability of the system after ligand binding to DDR1. Based on molecular dynamics simulations and hydrogen-bonding occupancy analysis, the DDR1-Cpd2, DDR1-Cpd17, and DDR1-Cpd18 complex systems exhibited superior stability compared to the DDR1-Cpd1 and DDR-Cpd33 complex systems. Meanwhile, when targeting DDR1, the descending order of the five hit molecules' binding free energies was Cpd17 (- 145.820 kJ/mol) > Cpd2 (- 131.818 kJ/mol) > Cpd18 (- 130.692 kJ/mol) > Cpd33 (- 129.175 kJ/mol) > Cpd1 (- 126.103 kJ/mol). Among them, Cpd2, Cpd17, and Cpd18 showed improved binding characteristics, indicating that they may be potential DDR1 inhibitors. In this research, we developed a high-hit rate, effective screening method that serves as a theoretical guide for finding DDR1 inhibitors for the development of IPF therapeutics.

Synthesis, molecular docking, and binding Gibbs free energy calculation of β-nitrostyrene derivatives: Potential inhibitors of SARS-CoV-2 3CL protease

The outbreak of novel coronavirus disease 2019 (COVID-19), caused by the novel coronavirus (SARS-CoV-2), has had a significant impact on human health and the economic development. SARS-CoV-2 3CL protease (3CLpro) is highly conserved and plays a key role in mediating the transcription of virus replication. It is an ideal target for the design and screening of anti-coronavirus drugs. In this work, seven β-nitrostyrene derivatives were synthesized by Henry reaction and β-dehydration reaction, and their inhibitory effects on SARS-CoV-2 3CL protease were identified by enzyme activity inhibition assay in vitro. Among them, 4-nitro-β-nitrostyrene (compound a) showed the lowest IC₅₀ values of 0.7297 μM. To investigate the key groups that determine the activity of β-nitrostyrene derivatives and their interaction mode with the receptor, the molecular docking using the CDOCKER protocol in Discovery Studio 2016 was performed. The results showed that the hydrogen bonds between β-NO₂ and receptor GLY-143 and the π-π stacking between the aryl ring of the ligand and the imidazole ring of receptor HIS-41 significantly contributed to the ligand activity. Furthermore, the ligand-receptor absolute binding Gibbs free energies were calculated using the Binding Affinity Tool (BAT.py) to verify its correlation with the activity of β-nitrostyrene 3CLpro inhibitors as a scoring function. The higher correlation(r²=0.6) indicates that the absolute binding Gibbs free energy based on molecular dynamics can be used to predict the activity of new β-nitrostyrene 3CLpro inhibitors. These results provide valuable insights for the functional group-based design, structure optimization and the discovery of high accuracy activity prediction means of anti-COVID-19 lead compounds.

Exploring the mechanism of active components from ginseng to manage diabetes mellitus based on network pharmacology and molecular docking

A large body of literature has shown that ginseng had a role in diabetes mellitus management. Ginsenosides are the main active components of ginseng. But what ginsenosides can manage in diabetic are not systematic. The targets of these ginsenosides are still incomplete. Our aim was to identify which ginsenosides can manage diabetes mellitus through network pharmacology and molecular docking. To identify the targets of these ginsenosides. In this work, we retrieved and screened ginsenosides and corresponding diabetes mellitus targets across multiple databases. PPI networks of the genes were constructed using STRING, and the core targets were screened out through topological analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed by using the R language. Finally, molecular docking was performed after bioinformatics analysis for verification. Our research results showed that 28 ginsenosides in ginseng might be against diabetes mellitus by modulating related proteins such as VEGFA, Caspase 3, and TNF-α. Among the 28 ginsenosides, 20(R)-Protopanaxatriol, 20(R)-Protopanaxadiol, and Ginsenoside Rg1 might play a significant role. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis showed that the management of diabetes mellitus by ginsenosides may be related to the positive regulation of reactive oxygen metabolic processes, associated with the insulin signaling pathway, TNF signaling pathway, and AMPK signaling pathway. Molecular docking results and molecular dynamics simulation showed that most ginsenosides could stably bind to the core target, mainly hydrogen bonding and hydrophobic bond. This study suggests the management of ginseng on diabetes mellitus. We believe that our results can contribute to the systematic study of the mechanism of ginsenosides for the management of diabetes mellitus. At the same time, it can provide a theoretical basis for subsequent studies on the management of ginsenosides in diabetes mellitus.

Synthesis of New Ester Derivatives of Salicylic Acid and Evaluation of Their COX Inhibitory Potential

Salicylic acid is an NSAID with serious side effects on the GIS. The side effects of salicylic acid on the GIS are slightly reduced by acetylating salicylic acid. 12 new ester analogs of salicylic acid were synthesized with high yields in this study. The chemical structures of the synthesized compounds were characterized by ¹ H-NMR, ¹³ C-NMR, and HRMS spectra. The inhibitory potential of the compounds was evaluated on COXs by in vitro and in silico studies. The COX2 inhibitory activity of the most potent inhibitor MEST1 (IC₅₀ : 0.048 μM) was found to be much higher than the COX2 inhibitory activity of aspirin (IC₅₀ : 2.60 μM). In docking studies, the strongest inhibitor among the compounds synthesized was predicted to be MEST1, with the lowest binding energy. Docking studies revealed that MEST1 extends from the hydrophobic channel to the top of the cyclooxygenase active site, forming various interactions with residues in the binding pocket.

LIGHTHOUSE illuminates therapeutics for a variety of diseases including COVID-19

One of the bottlenecks in the application of basic research findings to patients is the enormous cost, time, and effort required for high-throughput screening of potential drugs for given therapeutic targets. Here we have developed LIGHTHOUSE, a graph-based deep learning approach for discovery of the hidden principles underlying the association of small-molecule compounds with target proteins. Without any 3D structural information for proteins or chemicals, LIGHTHOUSE estimates protein-compound scores that incorporate known evolutionary relations and available experimental data. It identified therapeutics for cancer, lifestyle related disease, and bacterial infection. Moreover, LIGHTHOUSE predicted ethoxzolamide as a therapeutic for coronavirus disease 2019 (COVID-19), and this agent was indeed effective against alpha, beta, gamma, and delta variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are rampant worldwide. We envision that LIGHTHOUSE will help accelerate drug discovery and fill the gap between bench side and bedside.

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LIGHTHOUSE discovers therapeutics solely on the basis of the primary sequence

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The predictions of LIGHTHOUSE against multiple diseases were experimentally correct

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LIGHTHOUSE facilitates optimization of lead compounds as well

Aptamer against Aflatoxin B1 Obtained by SELEX and Applied in Detection

Aflatoxins, especially aflatoxin B1 (AFB1), are the most prevalent mycotoxins in nature. They contaminate various crops and cause global food and feed safety concerns. Therefore, a simple, rapid, sensitive, and specific AFB1 detection tool is urgently needed. Aptamers generated by SELEX technology can specifically bind the desired targets with high affinity. The broad range of targets expands the scope of applications for aptamers. We used an AFB1-immobilized magnetic nanoparticle for SELEX to select AFB1-specific aptamers. One aptamer, fl-2CS1, revealed a dissociation constant (Kd = 2.5 μM) with AFB1 determined by isothermal titration calorimetry. Furthermore, no interaction was shown with other toxins (AFB2, AFG1, AFG2, OTA, and FB1). According to structural prediction and analysis, we identified a short version of the AFB1-specific aptamer, fl-2CS1/core, with a minimum length of 39-mer used in the AFB1-aptasensor system by real-time qPCR. The aptasensor showed a broad range of detection from 50 ppt to 50 ppb with an accuracy of 90% in the spiked peanut extract samples. With the application of the AFB1-aptasensor we have constructed, a wide range detection tool with high accuracy might be developed as a point-of-care testing tool in agriculture.

Validation of structural-based virtual screening protocols with the PDB Code 3G0B and prediction of the activity of Tinospora crispa compounds as inhibitors of dipeptidyl-peptidase-IV

Introduction: Brotowali (Tinospora crispa) has been traditionally used as an antidiabetic drug. DPP-IV inhibitor as an antidiabetic will increase insulin secretion. It indirectly escalates incretin hormones, such as Glucagon-Like peptide-1 (GLP-1) which depends on glucose. This study predicts potential compounds from the Brotowali plants, such as DPP-IV inhibitors, using the Molegro Virtual Docker (MVD).

Materials and methods: Before the molecular docking simulation, internal validation and external validation are necessary. Internal validation was carried out by re-docking the native ligands in the DPP-IV enzyme crystal structure (PDB codes 3G0B, 3W2T, and 3BJM). The external validation was carried out by simultaneous docking of 59 active compounds and 1918 inactive compounds (decoys) from the A Directory of Useful Decoys (DUD) database with PDB code 3G0B on 16 combinations, four search algorithms, and four functions scoring.

Results and discussion: The molecular docking simulation was carried out on 50 compounds from the Brotowali plant and alogliptin as standard compounds with PDB code 3G0B. The best results of the docking method validation yielded the RMSD values of 0.43 and EF1% of 20.34 and EF20% of 3.1 (the combination of search algorithm Moldock optimizer and scoring function Moldock score). The re-rank score of 5 compounds from the Brotowali plant (Rumphioside C, Borapetoside E, Borapetoside F, Rumphioside I, and 6’-O-Lactoyl Borapetoside B) were -107.7 kcal/mol; -105.4 kcal/mol; -104.2 kcal/mol, and -102.8 kcal/mol. Alogliptin (standard ligands) had a re-rank score of -101.6 kcal/mol. The combination of search algorithms MolDock optimizer and scoring function MolDock score is a valid protocol with a good result. The similarity of the binding sites of Borapetoside E and 6’-O-Lactoyl Borapetoside B is 75% when compared to the alogliptin binding sites (Glu 205, Glu 206, Tyr 547).

Conclusion: Based on the re-rank score and binding sites similarity, Borapetoside E and 6’-O-Lactoyl Borapetoside B have potential as an antidiabetic drug with a mechanism of action of DPP-IV inhibitors.

Screening the components of Saussurea involucrata for novel targets for the treatment of NSCLC using network pharmacology

BACKGROUND

Saussurea involucrata (SAIN), also known as Snow lotus (SI), is mainly distributed in high-altitude areas such as Tibet and Xinjiang in China. To identify novel targets for the prevention or treatment of lung adenocarcinoma and lung squamous cell carcinoma (LUAD&LUSC), and to facilitate better alternative new drug discovery as well as clinical application services, the therapeutic effects of SAIN on LUAD&LUSC were evaluated by gene differential analysis of clinical samples, compound target molecular docking, and GROMACS molecular dynamics simulation.

RESULTS

Through data screening, alignment, analysis, and validation it was confirmed that three of the major active ingredients in SAIN, namely quercetin (Q), luteolin (L), and kaempferol (K), mainly act on six protein targets, which mainly regulate signaling pathways in cancer, transcriptional misregulation in cancer, EGFR tyrosine kinase inhibitor resistance, adherens junction, IL-17 signaling pathway, melanoma, and non-small cell lung cancer. In addition, microRNAs in cancer exert preventive or therapeutic effects on LUAD&LUSC. Molecular dynamics (MD) simulations of Q, L, or K in complex with EGFR, MET, MMP1, or MMP3 revealed the presence of Q in a very stable tertiary structure in the human body.

CONCLUSION

There are three active compounds of Q, L, and K in SAIN, which play a role in the treatment and prevention of non-small cell lung cancer (NSCLC) by directly or indirectly regulating the expression of genes such as MMP1, MMP3, and EGFR.

Computational Identification of Potential Anti-Inflammatory Natural Compounds Targeting the p38 Mitogen-Activated Protein Kinase (MAPK): Implications for COVID-19-Induced Cytokine Storm

Severely ill coronavirus disease 2019 (COVID-19) patients show elevated concentrations of pro-inflammatory cytokines, a situation commonly known as a cytokine storm. The p38 MAPK receptor is considered a plausible therapeutic target because of its involvement in the platelet activation processes leading to inflammation. This study aimed to identify potential natural product-derived inhibitory molecules against the p38α MAPK receptor to mitigate the eliciting of pro-inflammatory cytokines using computational techniques. The 3D X-ray structure of the receptor with PDB ID 3ZS5 was energy minimized using GROMACS and used for molecular docking via AutoDock Vina. The molecular docking was validated with an acceptable area under the curve (AUC) of 0.704, which was computed from the receiver operating characteristic (ROC) curve. A compendium of 38,271 natural products originating from Africa and China together with eleven known p38 MAPK inhibitors were screened against the receptor. Four potential lead compounds ZINC1691180, ZINC5519433, ZINC4520996 and ZINC5733756 were identified. The compounds formed strong intermolecular bonds with critical residues Val38, Ala51, Lys53, Thr106, Leu108, Met109 and Phe169. Additionally, they exhibited appreciably low binding energies which were corroborated via molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The compounds were also predicted to have plausible pharmacological profiles with insignificant toxicity. The molecules were also predicted to be anti-inflammatory, kinase inhibitors, antiviral, platelet aggregation inhibitors, and immunosuppressive, with probable activity (Pa) greater than probable inactivity (Pi). ZINC5733756 is structurally similar to estradiol with a Tanimoto coefficient value of 0.73, which exhibits anti-inflammatory activity by targeting the activation of Nrf2. Similarly, ZINC1691180 has been reported to elicit anti-inflammatory activity in vitro. The compounds may serve as scaffolds for the design of potential biotherapeutic molecules against the cytokine storm associated with COVID-19.

Discovery of the EL-0052 as a potential anesthetic drug

As a γ-aminobutyric acid A receptor (GABA_AR) inhibitor, etomidate fulfills several characteristics of an ideal anesthetic agent, such as rapid onset with rapid clearance and high potency, along with cardiovascular stability. Unfortunately, etomidate has been reported to inhibit CYP11B1 at hypnotic doses, which is associated with a marked increase in patient deaths due to this unexpected off-target effect. In this study, molecular docking was used to simulate the binding mode of etomidate with GABA_AR and CYP11B1. Based on the in-depth analysis of the binding mode, strong electron-withdrawing group on the C4 position of the imidazole ring was introduced to reduce the charge density of the nitrogen, which is beneficial in reducing the coordination bond between the imidazole nitrogen and heme iron in CYP11B1, as well as in reducing the adrenocortical suppression. Based on the results of ADMET property prediction, MEP analysis, and molecular docking simulation, 4-fluoroetomidate (EL-0052) was designed and synthesized. In vivo studies in rats and mice confirmed that EL-0052 had the efficacy similar to etomidate, but without adrenocortical suppression. These findings suggested that EL-0052 was superior to etomidate and support the continued development of EL-0052 as a preclinical candidate as an anesthetic.