A Practical Guide to Molecular Docking and Homology Modelling for Medicinal Chemists

Identification and analysis of oncogenic non-synonymous single nucleotide polymorphisms in the human NRAS gene: An exclusive in silico study

BACKGROUND

N-ras protein is encoded by the NRAS gene and operates as GDP-GTP-controlled on/off switching. N-ras interacts with cellular signaling networks that regulate various cellular activities including cell proliferation and survival. The nonsynonymous single nucleotide polymorphism (nsSNPs)-mediated alteration can substantially disrupt the structure and activity of the corresponding protein. N-ras has been reported to be associated with numerous diseases including cancers due to the nsSNPs. A comprehensive study on the NRAS gene to unveil the potentially damaging and oncogenic nsSNPs is yet to be accomplished. Hence, this extensive in silico study is intended to identify the disease-associated, specifically oncogenic nsSNPs of the NRAS gene.

RESULTS

Out of 140 missense variants, 7 nsSNPs (I55R, G60E, G60R, Y64D, L79F, D119G, and V152F) were identified to be damaging utilizing 10 computational tools that works based on different algorithms with high accuracy. Among those, G60E, G60R, and D119G variants were further filtered considering their location in the highly conserved region and later identified as oncogenic variants. Interestingly, G60E and G60R variants were revealed to be particularly associated with lung adenocarcinoma, rhabdomyosarcoma, and prostate adenocarcinoma. Therefore, D119G could be subjected to detailed investigation for identifying its association with specific cancer.

CONCLUSION

This in silico study identified the deleterious and oncogenic missense variants of the human NRAS gene that could be utilized for designing further experimental investigation. The outcomes of this study would be worthwhile in future research for developing personalized medicine.

Potential mechanisms of traditional Chinese medicine in treating insomnia: A network pharmacology, GEO validation, and molecular-docking study

The purpose of this study is to investigate the potential mechanisms of Chinese herbs for the treatment of insomnia using a combination of data mining, network pharmacology, and molecular-docking validation. All the prescriptions for insomnia treated by the academician Qi Wang from 2020 to 2022 were collected. The Ancient and Modern Medical Case Cloud Platform v2.3 was used to identify high-frequency Chinese medicinal herbs and the core prescription. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were utilized to predict the effective active components and targets of the core herbs. Insomnia-related targets were collected from 4 databases. The intersecting targets were utilized to build a protein-protein interaction network and conduct gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the STRING database, Cytoscape software, and clusterProfiler package. Gene chip data (GSE208668) were obtained from the Gene Expression Omnibus database. The limma package was applied to identify differentially expressed genes (DEGs) between insomnia patients and healthy controls. To create a "transcription factor (TF)-miRNA-mRNA" network, the differentially expressed miRNAs were entered into the TransmiR, FunRich, Targetscan, and miRDB databases. Subsequently, the overlapping targets were validated using the DEGs, and further validations were conducted through molecular docking and molecular dynamics simulations. Among the 117 prescriptions, 65 herbs and a core prescription were identified. Network pharmacology and bioinformatics analysis revealed that active components such as β-sitosterol, stigmasterol, and canadine acted on hub targets, including interleukin-6, caspase-3, and hypoxia-inducible factor-1α. In GSE208668, 6417 DEGs and 7 differentially expressed miRNAs were identified. A "TF-miRNA-mRNA" network was constructed by 4 "TF-miRNA" interaction pairs and 66 "miRNA-mRNA" interaction pairs. Downstream mRNAs exert therapeutic effects on insomnia by regulating circadian rhythm. Molecular-docking analyses demonstrated good docking between core components and hub targets. Molecular dynamics simulation displayed the strong stability of the complex formed by small molecule and target. The core prescription by the academician Qi Wang for treating insomnia, which involves multiple components, targets, and pathways, showed the potential to improve sleep, providing a basis for clinical treatment of insomnia.

Design, synthesis, and evaluation of thiazolecarboxamide derivatives as stimulator of interferon gene inhibitors

Stimulator of interferon gene (STING) plays critical roles in the cytoplasmic DNA-sensing pathway and in the induction of inflammatory response. Aberrant cytoplasmic DNA accumulation and STING activation are implicated in numerous inflammatory and autoimmune diseases. Here, we reported the discovery of a series of thiazolecarboxamide-based STING inhibitors through a molecular planarity/symmetry disruption strategy. The privileged compound 15b significantly inhibited STING signaling and suppressed immune-inflammatory cytokine levels in both human and murine cells. In vivo experiments demonstrated 15b effectively ameliorated immune-inflammatory cytokines upregulation in MSA-2-stimulated and Trex1-D18N mice. Furthermore, compound 15b exhibited enhanced efficacy in suppressing interferon-stimulated gene 15 (ISG15), a critical positive feedback regulator of STING. Overall, compound 15b deserves further development for the treatment of STING-associated inflammatory and autoimmune diseases.

Synthesis, molecular docking analysis, drug-likeness evaluation, and inhibition potency of new pyrazole-3,4-dicarboxamides incorporating sulfonamide moiety as carbonic anhydrase inhibitors

A series of novel pyrazole-dicarboxamides were synthesized from pyrazole-3,4-dicarboxylic acid chloride and various primary and secondary sulfonamides. The structures of the new compounds were confirmed by FT-IR, 1H-NMR, 13C-NMR, and HRMS. Then the inhibition effects of newly synthesized molecules on human erythrocyte hCA I and hCA II isoenzymes were investigated. Ki values of the compounds were in the range of 0.024-0.496 µM for hCA I and 0.006-5.441 µM for hCA II. Compounds 7a and 7i showed nanomolar level of inhibition of hCA II, and these compounds exhibited high selectivity for this isoenzyme. Molecular docking studies were performed between the most active compounds 7a, 7b, 7i, and the reference inhibitor AAZ and the hCAI and hCAII to investigate the binding mechanisms between the compounds and the isozymes. These compounds showed better interactions than the AAZ. ADMET and drug-likeness analyses for the compounds have shown that the compounds can be used pharmacologically in living organisms.

Pseudolaric acid B exerts an antifungal effect and targets SIRT1 to ameliorate inflammation by regulating Nrf2/NF-κB pathways in fungal keratitis

Fungal keratitis (FK) is a vision-threatening infection. We aimed to explore the antifungal and anti-inflammatory effects of pseudolaric acid B (PAB) on FK and the underlying mechanisms involved. Network pharmacology utilized to acquire the potential target genes, and silent information regulator 1 (SIRT1) was consistently downregulated in Gene Expression Omnibus dataset and clinical samples. Molecular docking analysis showed that PAB and SIRT1 had good binding activity. No toxicity was observed in vivo and in vitro with a PAB concentration below 0.3 μM. PAB exerted its antifungal activity by destroying the integrity of hyphae, and alleviated the severity of FK in rats by decreasing clinical scores, fungal burden and inhibiting inflammatory cell infiltration. PAB increased SIRT1 to regulate the crosstalk between nuclear factor erythroid 2-related factor 2 (Nrf2) and nuclear factor kappa-B (NF-κB), decreasing the levels of inflammatory cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6; and pattern recognition receptors, C-type lectin domain containing 7A (Dectin-1), lectin-like oxidized low-density lipoprotein receptor 1 (LOX-1), toll like receptor (TLR)-2, and TLR4 both in vivo and in vitro. However, this anti-inflammatory effect of PAB was abolished by the SIRT1 inhibitor EX527. This study provides new evidence that PAB has antifungal and anti-inflammatory effects in FK and may provide a novel therapeutic strategy for the treatment of FK.

5-chloro-3-(2-(2,4-dinitrophenyl) hydrazono)indolin-2-one: synthesis, characterization, biochemical and computational screening against SARS-CoV-2

Chemical prototypes with broad-spectrum antiviral activity are important toward developing new therapies that can act on both existing and emerging viruses. Binding of the SARS-CoV-2 spike protein to the host angiotensin-converting enzyme 2 (ACE2) receptor is required for cellular entry of SARS-CoV-2. Toward identifying new chemical leads that can disrupt this interaction, including in the presence of SARS-CoV-2 adaptive mutations found in variants like omicron that can circumvent vaccine, immune, and therapeutic antibody responses, we synthesized 5-chloro-3-(2-(2,4-dinitrophenyl)hydrazono)indolin-2-one (H2L) from the condensation reaction of 5-chloroisatin and 2,4-dinitrophenylhydrazine in good yield. H2L was characterised by elemental and spectral (IR, electronic, Mass) analyses. The NMR spectrum of H2L indicated a keto-enol tautomerism, with the keto form being more abundant in solution. H2L was found to selectively interfere with binding of the SARS-CoV-2 spike receptor-binding domain (RBD) to the host angiotensin-converting enzyme 2 receptor with a 50% inhibitory concentration (IC50) of 0.26 μM, compared to an unrelated PD-1/PD-L1 ligand-receptor-binding pair with an IC50 of 2.06 μM in vitro (Selectivity index = 7.9). Molecular docking studies revealed that the synthesized ligand preferentially binds within the ACE2 receptor-binding site in a region distinct from where spike mutations in SARS-CoV-2 variants occur. Consistent with these models, H2L was able to disrupt ACE2 interactions with the RBDs from beta, delta, lambda, and omicron variants with similar activities. These studies indicate that H2L-derived compounds are potential inhibitors of multiple SARS-CoV-2 variants, including those capable of circumventing vaccine and immune responses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11696-023-03274-5.

Drugging the entire human proteome: Are we there yet?

Each of the ∼20,000 proteins in the human proteome is a potential target for compounds that bind to it and modify its function. The 3D structures of most of these proteins are now available. Here, we discuss the prospects for using these structures to perform proteome-wide virtual HTS (VHTS). We compare physics-based (docking) and AI VHTS approaches, some of which are now being applied with large databases of compounds to thousands of targets. Although preliminary proteome-wide screens are now within our grasp, further methodological developments are expected to improve the accuracy of the results.

Inhibition of Uridine 5'-diphospho-glucuronosyltransferases A10 and B7 by vitamins: insights from in silico and in vitro studies

Uridine 5'-diphospho-glucuronosyltransferases (UGTs) have been considered as a family of enzymes responsible for the glucuronidation process, a crucial phase II detoxification reaction. Among the various UGT isoforms, UGTs A10 and B7 have garnered significant attention due to their broad substrate specificity and involvement in the metabolism of numerous compounds. Recent studies have suggested that certain vitamins may exert inhibitory effects on UGT activity, thereby influencing the metabolism of drugs, environmental toxins, and endogenous substances, ultimately impacting their biological activities. In the present study, the inhibition potential of vitamins (A, B1, B2, B3, B5, B6, B7, B9, D3, E, and C) on UGT1A10 and UGT2B7 was determined using in silico and in vitro approaches. A 3-dimensional model of UGT1A10 and UGT2B7 enzymes was built using Swiss Model, ITASSER, and ROSETTA and verified using Ramachandran plot and SAVES tools. Molecular docking studies revealed that vitamins interact with UGT1A10 and UGT2B7 enzymes by binding within the active site pocket and interacting with residues. Among all vitamins, the highest binding affinity predicted by molecular docking was - 8.61 kcal/mol with vitamin B1. The in vitro studies results demonstrated the inhibition of the glucuronidation activity of UGTs by vitamins A, B1, B2, B6, B9, C, D, and E, with IC50 values of 3.28 ± 1.07 µg/mL, 24.21 ± 1.11 µg/mL, 3.69 ± 1.02 µg/mL, 23.60 ± 1.08 µg/mL, 6.77 ± 1.08 µg/mL, 83.95 ± 1.09 µg/ml, 3.27 ± 1.13 µg/mL and 3.89 ± 1.12 µg/mL, respectively. These studies provided the valuable insights into the mechanisms underlying drug-vitamins interactions and have the potential to guide personalized medicine approaches, optimizing therapeutic outcomes, and ensuring patient safety. Indeed, further research in the area of UGT (UDP-glucuronosyltransferase) inhibition by vitamins is essential to fully understand the clinical relevance and implications of these interactions. UGTs play a crucial role in the metabolism and elimination of various drugs, toxins, and endogenous compounds in the body. Therefore, any factors that can modulate UGT activity, including vitamins, can have implications for drug metabolism, drug-drug interactions, and overall health.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00182-0.

Ursolic acid alleviates chronic prostatitis via regulating NLRP3 inflammasome-mediated Caspase-1/GSDMD pyroptosis pathway

Ursolic acid (UA) is a naturally occurring pentacyclic triterpenoid widely found in fruits and vegetables. It has been reported that UA has anti-inflammatory effects. However, its efficacy and mechanism of action in the treatment of chronic prostatitis (CP) remain unclear. This study aimed to investigate the efficacy of UA treatment in CP and further explore the underlying mechanism. CP rat and pyroptosis cell models were established in vivo and in vitro, respectively. The efficacy of UA in inhibiting CP was evaluated via haematoxylin-eosin (HE) staining and measurement of inflammatory cytokines. RNA sequencing and molecular docking were used to predict the therapeutic targets of UA in CP. The expression of pyroptosis-related proteins was examined using various techniques, including immunohistochemistry, immunofluorescence, and flow cytometry. UA significantly ameliorated pathological damage and reduced the levels of proinflammatory cytokines in the CP model rats. RNA sequencing analysis and molecular docking suggested that NLRP3, Caspase-1, and GSDMD may be key targets. We also found that UA decreased ROS levels, alleviated oxidative stress, and inhibited p-NF-κB protein expression both in vivo and in vitro. UA improved pyroptosis morphology as indicated by electron microscope and inhibited the expression of the pyroptosis-related proteins NLRP3, Caspase-1, ASC, and GSDMD, reversed the levels of IL-1β, IL-18, and lactate dehydrogenase in vivo and in vitro. UA can mitigate CP by regulating the NLRP3 inflammasome-mediated Caspase-1/GSDMD pathway. Therefore, UA may be a potential for the treatment of CP.

A Strategy based on Bioinformatics and Machine Learning Algorithms Reveals Potential Mechanisms of Shelian Capsule against Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a prevalent and life-threatening form of cancer, with Shelian Capsule (SLC), a traditional Chinese medicine (TCM) formulation, being recommended for clinical treatment. However, the mechanisms underlying its efficacy remain elusive. This study sought to uncover the potential mechanisms of SLC in HCC treatment using bioinformatics methods.

METHODS

Bioactive components of SLC were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and HCC-related microarray chip data were sourced from the Gene Expression Omnibus (GEO) database. The selection criteria for components included OB ≧ 30% and DL ≧ 0.18. By integrating the results of differential expression analysis and weighted gene co-expression network analysis (WGCNA), disease-related genes were identified. Therapeutic targets were determined as shared items between candidate targets and disease genes. Protein-protein interaction (PPI) network analysis was conducted for concatenated genes, with core protein clusters identified using the MCODE plugin. Machine learning algorithms were applied to identify signature genes within therapeutic targets. Subsequently, immune cell infiltration analysis, single-cell RNA sequencing (sc-RNA seq) analysis, molecular docking, and ADME analysis were performed for the screened genes.

RESULTS

A total of 153 SLC ingredients and 170 candidate targets were identified, along with 494 HCCrelated disease genes. Overlapping items between disease genes and drug candidates represented therapeutic genes, and PPI network analysis was conducted using concatenated genes. MCODE1 and MCODE2 cluster genes underwent Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Four signature genes (TOP2A, CYP1A2, CYP2B6, and IGFBP3) were identified from 28 therapeutic genes using 3 machine learning algorithms, with ROC curves plotted. Molecular docking validated the interaction modes and binding abilities between signature genes and corresponding compounds, with free binding energy all <-7 kcal/mol. Finally, ADME analysis revealed similarities between certain SLC components and the clinical drugs Sorafenib and Lenvatinib.

CONCLUSION

In summary, our study revealed that the mechanism underlying the anti-HCC effects of SLC involves interactions at three levels: components (quercetin, beta-sitosterol, kaempferol, baicalein, stigmasterol, and luteolin), pathways (PI3K-Akt signaling pathway, TNF signaling pathway, and IL-17 signaling pathway), and targets (TOP2A, CYP1A2, CYP2B6, and IGFBP3). This study provides preliminary insights into the potential pharmacological mechanisms of SLC in HCC treatment, aiming to support its clinical application and serve as a reference for future laboratory investigations.

Computational methods in glaucoma research: Current status and future outlook

Advancements in computational techniques have transformed glaucoma research, providing a deeper understanding of genetics, disease mechanisms, and potential therapeutic targets. Systems genetics integrates genomic and clinical data, aiding in identifying drug targets, comprehending disease mechanisms, and personalizing treatment strategies for glaucoma. Molecular dynamics simulations offer valuable molecular-level insights into glaucoma-related biomolecule behavior and drug interactions, guiding experimental studies and drug discovery efforts. Artificial intelligence (AI) technologies hold promise in revolutionizing glaucoma research, enhancing disease diagnosis, target identification, and drug candidate selection. The generalized protocols for systems genetics, MD simulations, and AI model development are included as a guide for glaucoma researchers. These computational methods, however, are not separate and work harmoniously together to discover novel ways to combat glaucoma. Ongoing research and progresses in genomics technologies, MD simulations, and AI methodologies project computational methods to become an integral part of glaucoma research in the future.

Combining single-cell RNA sequencing data and transcriptomic data to unravel potential mechanisms and signature genes of the progression of idiopathic pulmonary fibrosis to lung adenocarcinoma and predict therapeutic agents

Patients with idiopathic pulmonary fibrosis (IPF) have a significantly higher prevalence of lung adenocarcinoma (LUAD) than normal subjects, although the underlying association is unclear. The raw data involved were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis were used to screen for differentially expressed genes (DEGs) and modular signature genes (MSGs). Genes intersecting DEGs and MSGs were considered hub genes for IPF and LUAD. Machine learning algorithms were applied to capture epithelial cell-derived signature genes (EDSGs) shared. External cohort data were exploited to validate the robustness of EDSGs. Immunohistochemical staining and K-M plots were used to denote the prognostic value of EDSGs in LUAD. Based on EDSGs, we constructed a TF-gene-miRNA regulatory network. Molecular docking can validate the strength of action between candidate drugs and EDSGs. Epithelial cells, 650 DEGs, and 1773 MSGs were shared by IPF and LUAD. As for 379 hub genes, we performed pathway and functional enrichment analysis. By analyzing sc-RNA seq data, we identified 1234 marker genes of IPF epithelial cell-derived and 1481 of LUAD. And these genes shared 8 items with 379 hub genes. Through the machine learning algorithms, we further fished TRIM2, S100A14, CYP4B1, LMO7, and SFN. The ROC curves emphasized the significance of EDSGs in predicting the onset of LUAD and IPF. The TF-gene-miRNA network revealed regulatory relationships behind EDSGs. Finally, we predicted appropriate therapeutic agents. Our study preliminarily identified potential mechanisms between IPF and LUAD, which will inform subsequent studies.

Analysis of Zinc and Stromal Immunity in Disuse Osteoporosis: Mendelian Randomization and Transcriptomic Analysis

OBJECTIVE

Disuse osteoporosis is known to be primarily caused by a lack of exercise. However, the causal relationships between zinc and immunity and disuse osteoporosis remain unknown. This study investigated these relationships and their potential mechanisms.

METHODS

This study was an integrative study combining genome-wide association studies and transcriptomics. Two-sample Mendelian randomization analysis (MR) was used to analyze the causal relationships between exposures (zinc, immunity, physical activity) and the outcome (osteoporosis) with the aid of single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs). Four models, MR-Egger, inverse variance weighted, weighted median and MR-Pleiotrophy RESidual Sum and Outlier (MRPRESSO), were used to calculate odds ratio values. Sensitivity and heterogeneity analyses were also performed using MRPRESSO and MR-Egger methods. The mRNA transcriptomic analysis was subsequently conducted. Zinc metabolism scores were acquired through single-sample Gene Set Enrichment Analysis algorithms. Stromal scores were obtained using the R Package "estimate" algorithms. Important Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathways were also derived through gene set variation analysis. Cytoscape software helped construct the transcription factor (TF)-mRNA-microRNA (miRNA) network. Virtual screening and molecular docking were performed. Polymerase chain reaction validation was also carried out in vivo.

RESULTS

Causal relationships were demonstrated between zinc and exercise (95% confidence interval [CI] = 1.30-2.95, p = 0.001), exercise and immunity (95% CI = 0.36-0.80, p = 0.002), exercise and osteoporosis (95% CI = 0.97-0.99, p = 0.0007), and immunity disorder and osteoporosis (95% CI = 1.30-2.03, p = 0.00002). One hundred and seventy-nine mRNAs in important modules were screened. Combining the differential expressional genes (DEGs) and the Boruta selection, six DEGs were screened (AHNAK, CSF2, ADAMTS12, SRA1, RUNX2, and SLC39A14). TF HOXC10 and miRNA hsa-miR-204 were predicted. Then, the TF-mRNA-miRNA network was successfully constructed. RUNX2 and SLC39A14 were identified as hub mRNAs in the TF-mRNA-miRNA network. Eventually, the novel small drug C6O4NH5 was designed according to the pharmacophore structure of SLC39A14. The docking energy for the novel drug was -5.83 kcal/mol. SLC39A14 and RUNX2 were downregulated (of statistical significance p-value < 0.05) in our animal experiment.

CONCLUSION

This study revealed that zinc had a protective causal relationship with disuse osteoporosis by promoting exercise and immunity. SLC39A14 and RUNX2 mRNA participated in this zinc-related mechanism.

Adaptive laboratory evolution of Rhodococcus rhodochrous DSM6263 for chlorophenol degradation under hypersaline condition

BACKGROUND

Normally, a salt amount greater than 3.5% (w/v) is defined as hypersaline. Large amounts of hypersaline wastewater containing organic pollutants need to be treated before it can be discharged into the environment. The most critical aspect of the biological treatment of saline wastewater is the inhibitory/toxic effect exerted on bacterial metabolism by high salt concentrations. Although efforts have been dedicated to improving the performance through the use of salt-tolerant or halophilic bacteria, the diversities of the strains and the range of substrate spectrum remain limited, especially in chlorophenol wastewater treatment.

RESULTS

In this study, a salt-tolerant chlorophenol-degrading strain was generated from Rhodococcus rhodochrous DSM6263, an original aniline degrader, by adaptive laboratory evolution. The evolved strain R. rhodochrous CP-8 could tolerant 8% NaCl with 4-chlorophenol degradation capacity. The synonymous mutation in phosphodiesterase of strain CP-8 may retard the hydrolysis of cyclic adenosine monophosphate (cAMP), which is a key factor reported in the osmoregulation. The experimentally verified up-regulation of intracellular cAMP level in the evolved strain CP-8 contributes to the improvement of growth phenotype under high osmotic condition. Additionally, a point mutant of the catechol 1,2-dioxygenase, CatAN211S, was revealed to show the 1.9-fold increment on activity, which the mechanism was well explained by molecular docking analysis.

CONCLUSIONS

This study developed one chlorophenol-degrading strain with extraordinary capacity of salt tolerance, which showed great application potential in hypersaline chlorophenol wastewater treatment. The synonymous mutation in phosphodiesterase resulted in the change of intracellular cAMP concentration and then increase the osmotic tolerance in the evolved strain. The catechol 1,2-dioxygenase mutant with improved activity also facilitated chlorophenol removal since it is the key enzyme in the degradation pathway.

Selectivity Mechanism of Pyrrolopyridone Analogues Targeting Bromodomain 2 of Bromodomain-Containing Protein 4 from Molecular Dynamics Simulations

Bromodomain and extra-terminal domain (BET) proteins play an important role in epigenetic regulation and are linked to several diseases; therefore, they are interesting targets. BET has two bromodomains: bromodomain 1 (BD1) and BD2. Selective targeting of BD1 or BD2 may produce different activities and greater effects than pan-BD inhibitors. However, the selective mechanism of the specific core must be studied at the atomic level. This study determined the effectiveness of pyrrolopyridone analogues to selectively inhibit BD2 using a pan-BD inhibitor (ABBV-075) and a selective-BD2 inhibitor (ABBV-744). Molecular dynamics simulations and calculations of binding free energies were used to systematically study the selectivity of BD2 inhibition by the pyrrolopyridone analogues. Overall, the pyrrolopyridone analogue inhibitors targeting BD2 interacted mainly with the following amino acid pairs between bromodomain-containing protein 4 (BRD4)-BD1 and BRD4-BD2 complexes: I146/V439, N140/N433, D144/H437, P82/P375, V87/V380, D88/D381, and Y139/Y432. The pyrrolopyridone analogues targeting BRD4-BD2 were divided into five regions based on selectivity mechanism. These results suggest that the R3 and R5 regions of pyrrolopyridone analogues can be modified to improve the selectivity between BRD4-BD1 and BRD4-BD2. The selectivity of BD2 inhibition by pyrrolopyridone analogues can be used to design novel BD2 inhibitors based on a pyrrolopyridone core.

Differential immunotoxicity effects of triclosan and triclocarban on larval zebrafish based on RNA-Seq and bioinformatics analysis

Herein, we demonstrated that sublethal-dose exposure to triclosan (TCS) and triclocarban (TCC) triggered larval zebrafish immunotoxicity. Acute exposure to TCS induced significant increases in larval neutrophils and macrophages and a prominent decrease in thymic T cells. In contrast, three kinds of cells (neutrophils, macrophages, and thymic T cells) were significantly reduced under TCC exposure, suggesting that both TCS and TCC suppress thymus development and mature T-cell differentiation. TCC was confirmed to have more severe immunotoxicity than TCS. Using Illumina RNA-Seq, 581 and 738 differentially expressed genes (DEGs) were identified in the TCS and TCC treatments, respectively. GO function and KEGG pathway enrichment analyses revealed that the DEGs were not identical in terms of biological processes, cellular components and molecular functions, but were primarily involved in immune response. KEGG analysis showed that approximately 47% and 11% of DEGs were mainly enriched in the immune system of the TCC and TCS treatments, respectively. Protein-protein interaction (PPI) network analysis confirmed that the hub genes enriched in the immune-related pathways differed between TCS and TCC exposure. The hub genes were fynb, mapk12b, scarb1, pik3r2, prkg3, srfa, arhgef2, cldn15la, and cldn15lb in the TCS treatment, and plg, serping1, masp2, fgg, vtnb, mmp9, serpine1, il1b, sb:cb37 and stat3 in the TCC treatment. Molecular docking simulation demonstrated that both TCS and TCC were stably docked with their target hub genes, and that their target molecules for inducing immunotoxicity were different. The differential target molecules and action pathways induced by TCS and TCC exposure provide us with diagnostic targets and toxicological endpoints.

Polygoni Multiflori Radix Praeparata and Acori Tatarinowii Rhizoma ameliorate scopolamine-induced cognitive impairment by regulating the cholinergic and synaptic associated proteins

ETHNOPHARMACOLOGICAL RELEVANCE

The combination of Polygoni Multiflori Radix Praeparata (PMRP) and Acori Tatarinowii Rhizoma (ATR) is often used in traditional Chinese medicine to prevent and treat Alzheimer's disease (AD). However, it is not clear whether the effects and mechanisms of the decoction prepared by traditional decocting method (PA) is different from that prepared by modern decocting method (P + A).

AIM OF THE STUDY

The present study aimed to investigate the differences in the protective effects of PA and P + A on scopolamine induced cognitive impairment, and to explore its potential mechanism.

MATERIALS AND METHODS

To assess the protective effect of PA and P + A on cognitive dysfunction, the mice were orally administrated with PA (1.56, 6.24 g kg^-1•day^-1) and P + A (1.56, 6.24 g kg^-1•day^-1) for 26 days before co-treatment with scopolamine (4 mg kg^-1•day^-1, i.p.). The learning and memory abilities of mice were examined by Morris water maze test, and the expressions of proteins related to cholinergic system and synaptic function were detected by the methods of ELISA, real-time PCR and Western blotting. Then, molecular docking technique was used to verify the effect of active compounds in plasma after PA administration on Acetylcholinesterase (AChE) protein. Finally, the Ellman method was used to evaluate the effects of different concentrations of PA, P + A (1 μg/mL-100 mg/mL) and the compounds (1-100 μM) on AChE activity in vitro.

RESULTS

On one hand, in the scopolamine-induced cognitive impairment mouse model, both of PA and P + A could improve the cognitive impairment, while the effect of PA on cognitive amelioration was better than that of P + A. Moreover, PA regulated the cholinergic and synaptic functions by enhancing the concentration of acetylcholine (ACh), the mRNA levels of CHT1, Syn, GAP-43 and PSD-95, and the related proteins (CHT1, VACHT, Syn, GAP-43 and PSD-95), and significantly inhibiting the expression of AChE protein. Meanwhile, P + A only up-regulated the mRNA levels of GAP-43 and PSD-95, increased the expressions of CHT1, VACHT, Syn, GAP-43 and PSD-95 proteins, and inhibited the expression of AChE protein. On the other hand, the in vitro study showed that some compounds including emodin-8-o-β-d-Glucopyranoside, THSG and α-Asarone inhibited AChE protein activity with the IC₅₀ values 3.65 μM, 5.42 μM and 9.43 μM, respectively.

CONCLUSIONS

These findings demonstrate that both of PA and P + A can ameliorate the cognitive deficits by enhancing cholinergic and synaptic related proteins, while PA has the stronger improvement effect on the cholinergic function, which may be attributed to the compounds including THSG, emodin, emodin-8-O-β-D-glucopyranoside and α-asarone. The present study indicated that PA has more therapeutic potential in the treatment of neurodegenerative diseases such as AD. The results provide the experimental basis for the clinical use of PA.

Combinational study with network pharmacology, molecular docking and preliminary experiments on exploring common mechanisms underlying the effects of weijing decoction on various pulmonary diseases

Objective

'Homotherapy for heteropathy' is a theory by which different diseases with similar pathogenesis can be treated with one Chinese formula. We aimed to explore the key components and core targets of Weijing decoction (WJD) in treating various lung diseases, namely, pneumonia, chronic obstructive pulmonary disease (COPD), acute lung injury (ALI), pulmonary fibrosis, pulmonary tuberculosis and non-small cell lung cancer (NSCLC), via network pharmacology, molecular docking and some experiments.

Significance

This is the first study on the mechanism of WJD in treating various lung diseases by 'homotherapy for heteropathy'. This study is helpful for the transformation of TCM formula and development of new drugs.

Methods

Active components and therapeutic targets of WJD were obtained via TCMSP and UniProt databases. Targets of the six pulmonary diseases were harvested from the GeneCards TTD, DisGeNet, UniProt and OMIM databases. Drug-disease intersection targets, corresponding Venn diagrams, herb-component-target networks and protein-protein interaction networks were established. Furthermore, GO biological function and KEGG enrichment analysis were completed. Moreover, the binding activity between main compounds and core targets was measured through molecular docking. Finally, the xenograft NSCLC mouse model was established. Immune responses were evaluated by flow cytometry and mRNA expression levels of critical targets were measured by real-time PCR.

Results

JUN, CASP3 and PTGS2 were the most critical targets in six pulmonary diseases. The active compounds beta-sitosterol, tricin and stigmasterol stably bound to many active sites on target proteins. WJD had extensive pharmacological regulation, involving pathways related to cancer, inflammation, infection, hypoxia, immunity and so on.

Conclusions

Effects of WJD against various lung diseases involve lots of compounds, targets and pathways. These findings will facilitate further research as well as clinical application of WJD.

Anti-inflammatory potential of selective small compounds by targeting TNF-α & NF-kB signaling: a comprehensive molecular docking and simulation study

Tumor necrosis factor alpha (TNF-α) is the major cause of inflammation in autoimmune diseases like rheumatoid arthritis (RA). It's mechanisms of signal transduction through nuclear factor kappa B (NF-kB) pathway via small molecules such as metabolite crosstalk are still elusive. In this study, we have targeted TNF-α and NF-kB through metabolites of RA, to inhibit TNF-α activity and deter NF-kB signaling pathways, thereby mitigating the disease severity of RA. TNF-α and NF-kB structure was obtained from PDB database and metabolites of RA were selected from literature survey. In-silico studies were carried out by molecular docking using AutoDock Vina software and further, known TNF-α and NF-kB inhibitors were compared and revealed metabolite's capacity to targets the respective proteins. Most suitable metabolite was then validated by MD simulation to verify its efficiency against TNF-α. Total 56 known differential metabolites of RA were docked with TNF-α and NF-kB compared to their corresponding inhibitor compounds. Four metabolites such as Chenodeoxycholic acid, 2-Hydroxyestrone, 2-Hydroxyestradiol (2-OHE2), and 16-Hydroxyestradiol were identified as a common TNF-α inhibitor's having binding energies ranging from -8.3 to -8.6 kcal/mol, followed by docking with NF-kB. Further, 2-OHE2 was selected because of having binding energy -8.5 kcal/mol, found to inhibit inflammation and the effectiveness was validated by root mean square fluctuation, radius of gyration and molecular mechanics with generalized born and surface area solvation against TNF-α. Thus 2-OHE2, an estrogen metabolite was identified as the potential inhibitor, attenuated inflammatory activation and can be utilized as a therapeutic target to disseminate severity of RA.

Designing of thiazolidinones against chicken pox, monkey pox, and hepatitis viruses: A computational approach

Computational designing of four different series (D-G) of thiazolidinone was done starting from different amines which was further condensed with various aldehydes. These underwent in silico molecular investigations for density functional theory (DFT), molecular docking, and absorption, distribution metabolism, excretion, and toxicity (ADMET) studies. The different electrochemical parameters of the compounds are predicted using quantum mechanical modeling approach with Gaussian. The docking software was used to dock the compounds against choosing PDB file for chickenpox, human immunodeficiency, hepatitis, and monkeypox virus as 1OSN, 1VZV, 6VLK, 1RTD, 3I7H, 3TYV, 4JU3, and 4QWO, respectively. The molecular interactions were visualized with discovery studio and maximum binding affinity was observed with D8 compounds against 4QWO (-13.383 kcal/mol) while for compound D5 against 1VZV which was -12.713 kcal/mol. Swiss ADME web tool was used to assess the drug-likeness of the designed compounds under consideration, and it is concluded that these molecules had a drug-like structure with almost zero violations.

Bioinformatics-based construction of prognosis-related methylation prediction model for pancreatic cancer patients and its application value

Objective: Pancreatic adenocarcinoma (PAAD) is a highly malignant gastrointestinal tumor with almost similar morbidity and mortality. In this study, based on bioinformatics, we investigated the role of gene methylation in PAAD, evaluated relevant factors affecting patient prognosis, screened potential anti-cancer small molecule drugs, and constructed a prediction model to assess the prognosis of PAAD.

Methods: Clinical and genomic data of PAAD were collected from the Tumor Genome Atlas Project (TCGA) database and gene expression profiles were obtained from the GTEX database. Analysis of differentially methylated genes (DMGs) and significantly differentially expressed genes (DEGs) was performed on tumorous samples with KRAS wild-type and normal samples using the “limma” package and combined analysis. We selected factors significantly associated with survival from the significantly differentially methylated and expressed genes (DMEGs), and their fitting into a relatively streamlined prognostic model was validated separately from the internal training and test sets and the external ICGC database to show the robustness of the model.

Results: In the TCGA database, 2,630 DMGs were identified, with the largest gap between DMGs in the gene body and TSS200 region. 318 DEGs were screened, and the enrichment analysis of DMGs and DEGs was taken to intersect DMEGs, showing that the DMEGs were mainly related to Olfactory transduction, natural killer cell mediated cytotoxicity pathway, and Cytokine -cytokine receptor interaction. DMEGs were able to distinguish well between PAAD and paraneoplastic tissues. Through techniques such as drug database and molecular docking, we screened a total of 10 potential oncogenic small molecule compounds, among which felbamate was the most likely target drug for PAAD. We constructed a risk model through combining three DMEGs (S100P, LY6D, and WFDC13) with clinical factors significantly associated with prognosis, and confirmed the model robustness using external and internal validation.

Conclusion: The classification model based on DMEGs was able to accurately separate normal samples from tumor samples and find potential anti-PAAD drugs by performing gene-drug interactions on DrugBank.

Prednisone acetate modulates Th1/Th2 and Th17/Treg cell homeostasis in experimental autoimmune uveitis via orchestrating the Notch signaling pathway

Uveitis is an immune eye disease that can seriously impair vision. Glucocorticoids (GC_S) have been extensively used to treat uveitis, though the mechanisms have not been fully elucidated. In this study, we investigated the regulatory effects of prednisone acetate (PA) on the Th1/Th2 and Th17/Treg balance in experimental autoimmune uveitis (EAU) through modulating the Notch signaling pathway. Briefly, Lewis rats were randomly divided into the normal control (NC), EAU, and EAU + PA groups. Rats in EAU and EAU + PA groups were induced EAU, while those in the EAU + PA group were treated with PA. Clinical and histopathological scores were employed to assess the progression of EAU. The expression levels of Notch signaling-related molecules (Notch1, Notch2, Dll3, Dll4, and Rbpj) and Th-associated cytokines (IFN-γ, IL-4, IL-10, and IL-17) were assessed via quantitative PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA). In addition, the frequencies of Th1, Th2, Th17 and Treg cells were detected by flow cytometry. These experimental results indicated that activation of the Notch signaling pathway occurred in EAU rats and resulted in a severe imbalance of the Th17/Treg and Th1/Th2 ratios. PA treatment significantly alleviated ocular inflammation, inhibited activation of the Notch signaling pathway, and declined Th1, and Th17 cell differentiation, thereby restoring the Th1/Th2 and Th17/Treg balance. Collectively, PA can positively enhance the systemic immune response and improve the intraocular microenvironmental homeostasis by inhibiting activation of the Notch signaling pathway and by restoring Th1/Th2 and Th17/Treg balance, thus achieving the goal of treating uveitis.

Molecular docking analysis of peptide-based antiviral agents against SARS-CoV-2 main protease: an approach towards drug repurposing

Aim: Utilizing the therapeutic potentials of previously approved medications against a new target or pharmacological response is known as drug repurposing. The health and scientific communities are under continual pressure to discover new compounds with antiviral potential due to the rising reports of viral resistance and the occurrence and re-emergence of viral outbreaks. The use of antiviral peptides has emerged as an intriguing option in this search. Here, this article includes the current United States Food and Drug Administration (FDA)-approved antiviral peptides that might be enforced for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and carried out docking study of the viral protease inhibitors. Methods: In silico techniques like molecular docking was carried out using Autodock Vina software. Results: The molecular docking studies of peptide-based antiviral agents against SARS-CoV-2 [Protein Data Bank (PDB) ID: 7P35] using docking software AutoDockTools 1.5.6. Among all the docked ligands, compound velpatasvir showed interaction with residues ILE213, GLN256, LEU141, GLN189, GLU166, HIS41, CYS145, and ASN142, and displayed the highest docking score of –8.2 kcal/mol. This medication could be a novel treatment lead or candidate for treating SARS-CoV-2. Conclusions: To conclude, a docking study of peptide based antiviral compounds for their binding mode in the catalytic domain of SARS-CoV-2 receptor is reported. On molecular docking, the compounds have showed remarkable binding affinity with the amino acids of receptor chain A. The compounds occupied the same binding cavity as the reference compound maintaining the interactions with conserved amino acid residues essential for significant inhibitory potential, especially for compound velpatasvir with binding score of –8.2 kcal/mol.

Antiplasmodial activity of coumarins isolated from Polygala boliviensis: in vitro and in silico studies

Polygala boliviensis is found in the Brazilian semiarid region. This specie is little chemically and biologically studied. Polygala spp. have different metabolites, especially coumarins. Studies indicate that coumarins have antimalarial potential, denoting the importance of researching new active compounds from plants, since the resistance of Plasmodium strains to conventional therapy has increased. The present study aimed to evaluate the antiplasmodial activity of auraptene and poligalen against a chloroquine-resistant strain of Plasmodium falciparum. Coumarins were isolated from P. boliviensis by open column chromatography and identified by Nuclear Magnetic Resonance Spectroscopy. A cytotoxicity assay was carried out using MTT test, and the in vitro antiplasmodial activity was evaluated using the W2 strain. The antiplasmodial activity results found were IC50=0.171 ± 0.016 for auraptene and 0.164 ± 0.012 for poligalen; the selectivity indexes were 78.71 and 609.76, respectively. Inverse virtual screening in the BRAMMT database by OCTOPUS 1.2 was applied to coumarins to find potential P. falciparum targets and showed higher affinity energy of auraptene for purine nucleoside phosphorylase (PfPNP) and of poligalen for dihydroorotate dehydrogenase (PfDHODH). Molecular Dynamics studies (MD and MM-GBSA) approach were applied to calculate binding energies against selected P. falciparum targets and showed that all coumarins were stable at the binding site during simulations. Furthermore, energies were favorable for complexation. This is the first report of auraptene in P. boliviensis species and of in vitro antiplasmodial activity of auraptene and poligalen. In silico studies indicated that the mechanism of action of coumarins is the inhibition of PfPNP and PfDHODH.Communicated by Ramaswamy H. Sarma.

Network pharmacology study of the mechanism underlying the therapeutic effect of Zhujing pill and its main component oleanolic acid against diabetic retinopathy

Diabetic retinopathy (DR) is the leading cause of blindness in the working population worldwide, with few effective drugs available for its treatment in the early stages. The Zhujing pill (ZJP) is well-established to enhance the early symptoms of DR, but the mechanism underlying its therapeutic effect remains unclear. In the present study, we used systems biology and multidirectional pharmacology to screen the main active ingredients of ZJP and retrieved DrugBank and Genecards databases to obtain 'drug-disease' common targets. Using bioinformatics analysis, we obtained the core targets, and potential mechanisms of action of ZJP and its main components for the treatment of DR. Molecular docking was used to predict the binding sites and the binding affinity of the main active ingredients to the core targets. The predicted mechanism was verified in animal experiments. We found that the main active ingredient of ZJP was oleanolic acid, and 63 common 'drug-disease' targets were identified. Topological analysis and cluster analysis based on the protein-protein interaction network of the Metascape database screened the core targets as PRKCA, etc. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these core targets were significantly enriched in the pro-angiogenic pathway of the VEGF signaling pathway. Molecular docking and surface plasmon resonance revealed that ZJP and its main active component, oleanolic acid had the highest binding affinity with PKC-α, the core target of the VEGF signaling pathway. Animal experiments validated that ZJP and oleanolic acid could improve DR.

Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs

Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based methods. Ligand-based methods encompass techniques including pharmacophore modelling and quantitative structure activity relationships (QSARs), which use the relationship between biological activity and chemical structure to ascertain suitable lead molecules. In contrast, structure-based methods use information about the binding site architecture from an established protein structure to select suitable molecules for further investigation. In recent years, deep learning techniques have been applied in drug design and present an exciting addition to CADD workflows. Despite the difficulties associated with CNS drug discovery, advances towards new pharmaceutical treatments continue to be made, and CADD has supported these findings. This review explores various CADD techniques and discusses applications in CNS drug discovery from 2018 to November 2022.

Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence

Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.

Structure based Drug Designing Approaches in SARS-CoV-2 Spike Inhibitor Design

The COVID-19 outbreak and the pandemic situation have hastened the research community to design a novel drug and vaccine against its causative organism, the SARS-CoV-2. The spike glycoprotein present on the surface of this pathogenic organism plays an immense role in viral entry and antigenicity. Hence, it is considered an important drug target in COVID-19 drug design. Several three-dimensional crystal structures of this SARS-CoV-2 spike protein have been identified and deposited in the Protein DataBank during the pandemic period. This accelerated the research in computer- aided drug designing, especially in the field of structure-based drug designing. This review summarizes various structure-based drug design approaches applied to this SARS-CoV-2 spike protein and its findings. Specifically, it is focused on different structure-based approaches such as molecular docking, high-throughput virtual screening, molecular dynamics simulation, drug repurposing, and target-based pharmacophore modelling and screening. These structural approaches have been applied to different ligands and datasets such as FDA-approved drugs, small molecular chemical compounds, chemical libraries, chemical databases, structural analogs, and natural compounds, which resulted in the prediction of spike inhibitors, spike-ACE-2 interface inhibitors, and allosteric inhibitors.

Insights into the Binding Interaction of Catechol 1,2-Dioxygenase with Catechol in Achromobacter xylosoxidans DN002

Microbial remediation has become one of the promising ways to eliminate polycyclic aromatic hydrocarbons (PAHs) pollution due to its efficient enzyme metabolism system. Catechol 1,2-dioxygenase (C12O) is a crucial rate-limiting enzyme in the degradation pathway of PAHs in Achromobacter xylosoxidans DN002 that opens the benzene ring through the ortho-cleavage pathway. However, little attention has been given to explore the interaction mechanism of relevant enzyme-substrate. This study aims to investigate the binding interaction between C12O of strain DN002 and catechol by means of a molecular biological approach combined with homology modeling, molecular docking, and multiple spectroscopies. The removal rate of catechol in the mutant strain of cat A deletion was only 12.03%, compared to the wild-type strain (54.21%). A Ramachandran plot of active site regions of the primary amino acid sequences in the native enzyme showed that 93.5% sequences were in the most favored regions on account of the results of homology modeling, while an additional 6.2% amino acid sequences were found in conditionally allowed regions, and 0.4% in generously allowed regions. The binding pocket of C12O with catechol was analyzed to obtain that the catalytic trimeric group of Tyr164-His224-His226 was proven to be great vital for the ring-opening reaction of catechol by molecular docking. In the native enzyme, binding complexes were spontaneously formed by hydrophobic interactions. Binding constants and thermodynamic potentials from fluorescence spectra indicated that catechol effectively quenched the intrinsic fluorescence of C12O in the C12O/catechol complex via conventional static and dynamic quenching mechanisms of C12O. The results of ultraviolet and visible (UV) spectra, synchronous fluorescence, and circular dichroism (CD) spectra revealed conspicuous changes in the local conformation, and site-directed mutagenesis confirmed the role of predicted key residues during catalysis, wherein His₂₂₆ had a significant effect on catechol utilization by C12O. This is the first report to reveal interactions of C12O with substrate from the molecular docking results, providing the mechanistic understanding of representative dioxygenases involved in aromatic compound degradation, and a solid foundation for further site modifications as well as strategies for the directed evolution of this enzyme.

Molecular Dynamics Methods for Antibody Design

Complex and coordinated dynamics are closely connected with protein functions, including the binding of antibodies to antigens. Knowledge of such dynamics could improve the design of antibodies. Molecular dynamics (MD) simulations provide a "computational microscope" that can resolve atomic motions and inform antibody design efforts.

In-silico identification of novel inhibitors for human Aurora kinase B form the ZINC database using molecular docking-based virtual screening

Introduction: Aurora kinase enzymes play critical functions in mammals. Aurora kinases are mitotic regulators that are involved in a variety of processes during cell division. The overexpression of these enzymes is associated with tumour formation and is symptomatic of clinical circumstances in cancer patients who have been diagnosed.

Materials and methods: The current study reports an in-silico virtual screening (VS) and molecular docking analysis of 2500 compounds retrieved from the ZINC database and five current clinical trial compounds against Aurora Kinase B using AutoDock Vina to identify potential inhibitors.

Results and discussion: The top six compounds that resulted from the screening were ZINC00190959, ZINC07889110, ZINC0088285, ZINC01404326, ZINC00882846 and ZINC08813187, which showed lower free energy of binding (FEB) against the target protein binding pocket. The FEB were as follows: -11.92, -11.85, -11.46, -11.33, -11.21 and -11.1 kcal/mol, using AutoDock, and -11.7, -11.5, -11.2, -11.0, -10.8 and -10.6 kcal/mol for AutoDock Vina, respectively. These findings were superior to those obtained with the co-crystallized ligand VX-680, with a -7.5 kcal/mol and the current clinical trial drug. Finally, using a VS and molecular docking approach, novel Aurora kinase B inhibitors were effectively identified from the ZINC database fulfilling the Lipinski rule of five with low FEB and functional molecular interactions with the target protein.

Conclusion: The findings suggest that the six compounds could be used as a potential agent for cancer treatments.

Graphical abstract

Effective natural inhibitors targeting granzyme B in rheumatoid arthritis by computational study

Background

Rheumatoid arthritis (RA) is an autoimmune disease characterized by erosive arthritis, and current treatments for RA fall short of the outcomes expected by clinicians and patients.

Objectives

This study aimed to identify novel therapeutic and prognostic targets in RA at the genomic level and to screen desirable compounds with potential inhibitory effects on GZMB.

Methods

We performed differential gene analysis on GSE55235 and GSE55457 from Gene Expression Omnibus (GEO) and then obtained the intersection of the two differentially expressed genes (DEGs) lists by drawing Venn diagrams. Then we performed protein-protein interaction (PPI) network analysis, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis on the DEGs of the intersection. Next, we downloaded the crystal structure of Granzyme B (GZMB). Molecular docking technology was used to screen potential inhibitors of GZMB in subsequent experiments, and we then analyzed the toxicity and water solubility of these potential inhibitors for future drug experiments. Finally, whether the docking of these small molecules with GZMB is stable is tested by molecular dynamics.

Results

A total of 352 mutual DEGs were identified. Twenty hub genes were obtained according to PPI network analysis, among which the GZMB gene attracted the attention of our research. Three potent natural compounds, ZINC000004557101, ZINC000012495776, and ZINC000038143593, bound to GZMB, show better binding affinity. Furthermore, they are predicted to own low Ames mutagenicity, developmental toxicity potential, rodent carcinogenicity, and high tolerance to cytochrome P4502D6. Molecular dynamics simulations show that ZINC000004557101 and GZMB have more advantageous potential energy and can exist stably in a natural environment. Moreover, we finally verified the inhibitory effect of ZINC000004557101 on granzyme B by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and Western blotting experiment.

Conclusion

RA patients showed increased GZMB expression. ZINC000004557101 is a potential drug targeting GZMB for treating RA.

Discovery of pulmonary fibrosis inhibitor targeting TGF-β RI in Polygonum cuspidatum by high resolution mass spectrometry with in silico strategy

Pulmonary fibrosis (PF) is an irreversible lung disease that is characterized by excessive scar tissue with a poor median survival rate of 2-3 years. The inhibition of transforming growth factor-β receptor type-I (TGF-β RI) by an appropriate drug may provide a promising strategy for the treatment of this disease. Polygonum cuspidatum (PC) is a well-known traditional Chinese herbal medicine which has an anti-PF effect. Accordingly, a combination of high resolution mass spectrometry with an in silico strategy was developed as a new method to search for potential chemical ingredients of PC that target the TGF-β RI. Based on this strategy, a total of 24 ingredients were identified. Then, absorption, distribution, metabolism, and excretion (ADME)-related properties were subsequently predicted to exclude compounds with potentially undesirable pharmacokinetics behaviour. Molecular docking studies on TGF-β RI were adopted to discover new PF inhibitors. Eventually, a compound that exists in PC known as resveratrol was proven to have excellent biological activity on TGF-β RI, with an IC₅₀ of 2.211 μM in vitro. Furthermore, the complex formed through molecular docking was tested via molecular dynamics simulations, which revealed that resveratrol had strong interactions with residues of TGF-β RI. This study revealed that resveratrol has significant potential as a treatment for PF due to its ability to target TGF-β RI. In addition, this research demonstrated the exploration of natural products with excellent biological activities toward specific targets via high resolution mass spectrometry in combination with in silico technology is a promising strategy for the discovery of novel drugs.

Dexamethasone and potassium canrenoate alleviate hyperalgesia by competitively regulating IL-6/JAK2/STAT3 signaling pathway during inflammatory pain in vivo and in vitro

Background

Dexamethasone (Dexa) and potassium canrenoate (Cane) modulate nociceptive behavior via glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) by two mechanisms (genomic and nongenomic pathways). This study was designed to investigate the Dexa‐ or Cane‐mediated nongenomic and genomic effects on mechanical nociception and inflammation‐induced changes in interleukin‐6 (IL‐6) mediated signaling pathway in rats.

Methods

Freund's complete adjuvant (FCA) was used to trigger an inflammation of the right hind paw in male Sprague–Dawley rats. First, the mechanical nociceptive behavioral changes were examined following intraplantar administration of GR agonist Dexa and/or MR antagonist Cane in vivo. Subsequently, the protein levels of IL‐6, IL‐6Rα, JAK2, pJAK2, STAT3, pSTAT3^Ser727, migration inhibitory factor, and cyclooxygenase‐2 were assessed by Western blot following intraplantar injection of Dexa or Cane or the combination. Moreover, the molecular docking studies determined the interaction between Dexa, Cane, and IL‐6. The competition binding assay was carried out using enzyme‐linked immunosorbent assays (ELISA).

Results

Administration of Dexa and Cane dose‐dependently attenuated FCA‐induced inflammatory pain. The sub‐additive effect of Dexa/Cane combination was elucidated by isobologram analysis, accompanied by decrease in the spinal levels of IL‐6, pJAK2, and pSTAT3^Ser727. The molecular docking study demonstrated that both Dexa and Cane displayed a firm interaction with THR¹³⁸ binding site of IL‐6 via a strong hydrogen bond. ELISA revealed that Dexa has a higher affinity to IL‐6 than Cane.

Conclusions

There was no additive or negative effect of Dexa and Cane, and they modulate the IL‐6/JAK2/STAT3 signaling pathway through competitive binding with IL‐6 and relieves hypersensitivity during inflammatory pain.

Exploring the underlying mechanism of oleanolic acid treating glioma by transcriptome and molecular docking

OBJECTIVE

Oleanolic acid is a promising drug for treating gliomas, but its underlying mechanism is unclear. This study aimed to determine the potential effect of oleanolic acid on glioma and its mechanism.

METHODS

Firstly, the effects of oleanolic acid on the proliferation, invasion, and apoptosis of glioma U251 cells were detected by in vitro experiments such as MTT assay, cell cloning, and flow cytometry. The transcriptome data of U251 cells treated with oleanolic acid and untreated were sequenced by mRNA, and then the differentially expressed genes were analyzed by gene ontology (GO), genomic encyclopedia (KEGG) pathway enrichment analysis, and protein interaction topology analysis. The underlying mechanism of oleanolic acid was predicted, and the related protein interaction network was constructed. Finally, Western blotting and molecular docking techniques verified the mRNA sequencing results.

RESULTS

Oleanolic acid could effectively inhibit the proliferation, colony formation, and invasion of U251 cells and induce apoptosis. A total of 446 differentially expressed genes were detected by mRNA sequencing, of which 96 genes were up-regulated and 350 down-regulated. Oleanolic acid induces the TNF signal pathway and NOD-like receptor signal pathway at the intracellular level. In addition, OAS2, OASL, IFIT3, RSAD2, and IRF1 may be the core targets of oleanolic acid in treating glioma.

CONCLUSION

Transcriptome combined with molecular docking technique is used to predict the possible mechanism of oleanolic acid in the treatment of glioma, which provides new ideas and insights for developing and researching antitumor drugs.

Network pharmacology and molecular docking reveal zedoary turmeric-trisomes in Inflammatory bowel disease with intestinal fibrosis

BACKGROUND

Inflammatory bowel disease (IBD) is a complex chronic IBD that is closely associated with risk factors such as environment, diet, medications and lifestyle that may influence the host microbiome or immune response to antigens. At present, with the increasing incidence of IBD worldwide, it is of great significance to further study the pathogenesis of IBD and seek new therapeutic targets. Traditional Chinese medicine (TCM) treatment of diseases is characterized by multiple approaches and multiple targets and has a long history of clinical application in China. The mechanism underlying the effect of zedoary turmeric-trisomes on inducing mucosal healing in IBD is not clear.

AIM

To explore the effective components and potential mechanism of zedoary turmeric-trisomes in the treatment of IBD with intestinal fibrosis using network pharmacology and molecular docking techniques.

METHODS

The chemical constituents and targets of Rhizoma zedoary and Rhizoma sanarum were screened using the TCMSP database. The GeneCards database was searched to identify targets associated with intestinal fibrosis in IBD. The intersection of chemical component targets and disease targets was obtained using the Venny 2.1 online analysis platform, and the common targets were imported into the STRING 11.0 database to construct a protein interaction regulatory network. A “zedoary turmeric-trisomes-chemical composition-target-disease” network diagram was subsequently constructed using Cytoscape 3.7.2 software, and the topological properties of the network were analyzed using the “Network Analysis” plug-in. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the common targets were performed using the DAVID 6.8 database to elucidate the mechanism of zedoary turmeric-trisomes in the treatment of IBD. Subsequently, molecular docking of the compounds and targets with the highest intermediate values in the “zedoary turmeric-trisomes-chemical composition-target-disease” network was performed using Sybyl-x 2.1.1 software.

RESULTS

A total of 5 chemical components with 60 targets were identified, as well as 3153 targets related to IBD and 44 common targets. The protein-protein interaction network showed that the core therapeutic targets included JUN, MAPK14, CASP3, AR, and PTGS2. The GO enrichment analysis identified 759 items, and the KEGG enrichment analysis yielded 52 items, including the cancer pathway, neuroactive ligand-receptor interaction, hepatitis B, and the calcium signaling pathway, reflecting the complex biological processes of the multicomponent, multitarget and multipathway treatment of diseases with zedoary turmeric-trisomes. Molecular docking showed that the compound bonded with the target through hydrogen bond interactions and exhibited good docking activity.

CONCLUSION

This study identified the potential mechanism of action of zedoary turmeric-trisomes in the treatment of inflammatory bowel fibrosis using network pharmacology and molecular docking technology, providing a scientific basis for further expansion of their clinical use.

Identification of Molecular Targets and Potential Mechanisms of Yinchen Wuling San Against Head and Neck Squamous Cell Carcinoma by Network Pharmacology and Molecular Docking

Head and neck squamous cell carcinoma (HNSCC) represents one of the most malignant and heterogeneous tumors, and the patients have low 5-year survival. Traditional Chinese medicine (TCM) has been demonstrated as an effective complementary and/or alternative therapy for advanced malignancies including HNSCC. It has been noted that several herbs that are used for preparing Yinchen Wuling San (YWLS) have anti-tumor activities, whereas their mechanisms of action remain elusive. In this study, network pharmacology and molecular docking studies were employed to explore the underlying mechanisms of action of YWLS against HNSCC. The 58 active ingredients from six herbs used for YWLS and their 506 potential targets were screened from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and SwissTargetPrediction database. A total of 2,173 targets associated with HNSCC were mainly identified from the DisGeNET and GeneCards databases. An active components-targets-disease network was constructed in the Cytoscape. Top 20 hub targets, such as AKT1, EGFR, TNF, ESR1, SRC, HSP90AA1, MAPK3, ERBB2, and CCND1, were identified by a degree in the protein–protein interaction (PPI) network. Gene functional enrichment analysis showed that PI3K-AKT, MAPK, Ras, TNF, and EGFR were the main signaling pathways of YWLS in treating HNSCC. There were 48 intersected targets such as EGFR, AKT1, and TNF that were associated with patients’ outcomes by the univariate Cox analysis, and most of them had increased expression in the tumor as compared to normal tissues. The area under curves of receiver operating characteristic indicated their diagnostic potential. Inhibition of these survival-related targets and/or combination with EGFR or AKT inhibitors were promising therapeutic options in HNSCC. The partial active components of YWLS exhibited good binding with the hub targets, and ADME analysis further evaluated the drug-likeness of the active components. These compounds and targets identified in this study might provide novel treatment strategies for HNSCC patients, and the subsequent work is essential to verify the underlying mechanisms of YWLS against HNSCC.

Assessment of pulmonary infectious disease treatment with Mongolian medicine formulae based on data mining, network pharmacology and molecular docking

Objective

Methods

Results

Conclusion

Prediction and validation of potential molecular targets for the combination of Astragalus membranaceus and Angelica sinensis in the treatment of atherosclerosis based on network pharmacology

Since the 20th century, mortality rate due to cardiovascular diseases has increased, posing a substantial economic burden on society. Atherosclerosis is a common cardiovascular disease that requires urgent and careful attention. This study was conducted to predict and validate the potential molecular targets and pathways of Astragalus membranaceus and Angelica sinensis (A&A) in the treatment of atherosclerosis using network pharmacology. The active ingredients of A&A were obtained using the TCMSP database, while the target genes of atherosclerosis were acquired using 2 databases, namely GeneCards and DrugBank. The disease-target-component model map and the core network were obtained using Cytoscape 3.8.2 and MCODE plug-in, respectively. The core network was then imported into the STRING database to obtain the protein-protein interaction (PPI) network diagram. Moreover, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed using the HIPLOT online website. Finally, the small molecules related to key signaling pathways were molecularly docked and visualized. Under the screening conditions of oral bioavailability ≥ 30% and drug-likeness ≥ 0.18, 22 active ingredients were identified from A&A, and 174 relevant targets were obtained. Additionally, 54 active ingredients were found in the extracted core network. Interleukin (IL)-17 signaling pathway, tumor necrosis factor (TNF) signaling pathway, and Toll-like receptor (TLR) signaling pathway were selected as the main subjects through KEGG enrichment analysis. Core targets (RELA, IKBKB, CHUK, and MMP3) and active ingredients (kaempferol, quercetin, and isorhamnetin) were selected and validated using molecular docking. This study identified multiple molecular targets and pathways for A&A in the treatment of atherosclerosis. A&A has the potential to treat atherosclerosis through an antiinflammatory approach.

Insights into the Pharmacological Effects of Flavonoids: The Systematic Review of Computer Modeling

Computer modeling is a method that is widely used in scientific investigations to predict the biological activity, toxicity, pharmacokinetics, and synthesis strategy of compounds based on the structure of the molecule. This work is a systematic review of articles performed in accordance with the recommendations of PRISMA and contains information on computer modeling of the interaction of classical flavonoids with different biological targets. The review of used computational approaches is presented. Furthermore, the affinities of flavonoids to different targets that are associated with the infection, cardiovascular, and oncological diseases are discussed. Additionally, the methodology of bias risks in molecular docking research based on principles of evidentiary medicine was suggested and discussed. Based on this data, the most active groups of flavonoids and lead compounds for different targets were determined. It was concluded that flavonoids are a promising object for drug development and further research of pharmacology by in vitro, ex vivo, and in vivo models is required.

Computational identification of Shenshao Ningxin Yin as an effective treatment for novel coronavirus infection (COVID-19) with myocarditis

BACKGROUND

The newly identified betacoronavirus SARS-CoV-2 is the causative pathogen of the 2019 coronavirus disease (COVID-19), which has killed more than 4.5 million people. SARS-CoV-2 causes severe respiratory distress syndrome by targeting the lungs and also induces myocardial damage. Shenshao Ningxin Yin (SNY) has been used for more than 700 years to treat influenza. Previous randomized controlled trials (RCTs) have demonstrated that SNY can improve the clinical symptoms of viral myocarditis, reverse arrhythmia, and reduce the level of myocardial damage markers.

METHODS

This work uses a rational computational strategy to identify existing drug molecules that target host pathways for the treatment of COVID-19 with myocarditis. Disease and drug targets were input into the STRING database to construct proteinɃprotein interaction networks. The Metascape database was used for GO and KEGG enrichment analysis.

RESULTS

SNY signaling modulated the pathways of coronavirus disease, including COVID-19, Ras signaling, viral myocarditis, and TNF signaling pathways. Tumor necrosis factor (TNF), cellular tumor antigen p53 (TP53), mitogen-activated protein kinase 1 (MAPK1), and the signal transducer and activator of transcription 3 (STAT3) were the pivotal targets of SNY. The components of SNY bound well with the pivotal targets, indicating there were potential biological activities.

CONCLUSION

Our findings reveal the pharmacological role and molecular mechanism of SNY for the treatment of COVID-19 with myocarditis. We also, for the first time, demonstrate that SNY displays multi-component, multi-target, and multi-pathway characteristics with a complex mechanism of action.

Generative machine learning for de novo drug discovery: A systematic review

Recent research on artificial intelligence indicates that machine learning algorithms can auto-generate novel drug-like molecules. Generative models have revolutionized de novo drug discovery, rendering the explorative process more efficient. Several model frameworks and input formats have been proposed to enhance the performance of intelligent algorithms in generative molecular design. In this systematic literature review of experimental articles and reviews over the last five years, machine learning models, challenges associated with computational molecule design along with proposed solutions, and molecular encoding methods are discussed. A query-based search of the PubMed, ScienceDirect, Springer, Wiley Online Library, arXiv, MDPI, bioRxiv, and IEEE Xplore databases yielded 87 studies. Twelve additional studies were identified via citation searching. Of the articles in which machine learning was implemented, six prominent algorithms were identified: long short-term memory recurrent neural networks (LSTM-RNNs), variational autoencoders (VAEs), generative adversarial networks (GANs), adversarial autoencoders (AAEs), evolutionary algorithms, and gated recurrent unit (GRU-RNNs). Furthermore, eight central challenges were designated: homogeneity of generated molecular libraries, deficient synthesizability, limited assay data, model interpretability, incapacity for multi-property optimization, incomparability, restricted molecule size, and uncertainty in model evaluation. Molecules were encoded either as strings, which were occasionally augmented using randomization, as 2D graphs, or as 3D graphs. Statistical analysis and visualization are performed to illustrate how approaches to machine learning in de novo drug design have evolved over the past five years. Finally, future opportunities and reservations are discussed.

Molecular Docking as a Therapeutic Approach for Targeting Cancer Stem Cell Metabolic Processes

Cancer stem cells (CSCs) are subpopulation of cells which have been demonstrated in a variety of cancer models and involved in cancer initiation, progression, and development. Indeed, CSCs which seem to form a small percentage of tumor cells, display resembling characteristics to natural stem cells such as self-renewal, survival, differentiation, proliferation, and quiescence. Moreover, they have some characteristics that eventually can demonstrate the heterogeneity of cancer cells and tumor progression. On the other hand, another aspect of CSCs that has been recognized as a central concern facing cancer patients is resistance to mainstays of cancer treatment such as chemotherapy and radiation. Owing to these details and the stated stemness capabilities, these immature progenitors of cancerous cells can constantly persist after different therapies and cause tumor regrowth or metastasis. Further, in both normal development and malignancy, cellular metabolism and stemness are intricately linked and CSCs dominant metabolic phenotype changes across tumor entities, patients, and tumor subclones. Hence, CSCs can be determined as one of the factors that correlate to the failure of common therapeutic approaches in cancer treatment. In this context, researchers are searching out new alternative or complementary therapies such as targeted methods to fight against cancer. Molecular docking is one of the computational modeling methods that has a new promise in cancer cell targeting through drug designing and discovering programs. In a simple definition, molecular docking methods are used to determine the metabolic interaction between two molecules and find the best orientation of a ligand to its molecular target with minimal free energy in the formation of a stable complex. As a comprehensive approach, this computational drug design method can be thought more cost-effective and time-saving compare to other conventional methods in cancer treatment. In addition, increasing productivity and quality in pharmaceutical research can be another advantage of this molecular modeling method. Therefore, in recent years, it can be concluded that molecular docking can be considered as one of the novel strategies at the forefront of the cancer battle via targeting cancer stem cell metabolic processes.

Selected by bioinformatics and molecular docking analysis, Dhea and 2–14,15-Eg are effective against cholangiocarcinoma

Object

To identify novel targets for the diagnosis, treatment and prognosis of cholangiocarcinoma, we screen ideal lead compounds and preclinical drug candidates with MYC inhibitory effect from the ZINC database, and verify the therapeutic effect of Dhea and 2–14,15-Eg on cholangiocarcinoma.

Methods

The gene expression profiles of GSE132305, GSE89749, and GSE45001 were obtained respectively from the Gene Expression Omnibus database. The DEGs were identified by comparing the gene expression profiles of cholangiocarcinoma and normal tissues. GO, KEGG analysis and PPI network analyses were performed. LibDock, ADME and toxicity prediction, molecular docking and molecular dynamics simulations were used to identify potential inhibitors of MYC. Moreover, in vitro, MTT assay, colony-forming assay, the scratch assay and Western blotting were performed to verify the therapeutic effect of Dhea and 2–14,15-Eg.

Results

PPI network analysis showed that ALB, MYC, APOB, IGF1 and KNG1 were hub genes, of which MYC was mainly studied in this study. A battery of computer-aided virtual techniques showed that Dhea and 2–14,15-Eg have lower rodent carcinogenicity, Ames mutagenicity, developmental toxicity potential, and high tolerance to cytochrome P4502D6, as well as could exist stably in natural circumstances. In vitro assays showed that Dhea and 2–14,15-Eg inhibited cholangiocarcinoma cellular viability, proliferation, and migration inhibiting expression of MYC.

Conclusion

This study suggested that Dhea and 2–14,15-Eg were novel potential inhibitors of MYC targeting, as well as are a promising drug in dealing with cholangiocarcinoma and have a perspective application.

Exogenous Iron Induces NADPH Oxidases-Dependent Ferroptosis in the Conidia of Aspergillus flavus

Aspergillus flavus is saprophytic soil fungus that contaminates seed crops with the carcinogenic secondary metabolite aflatoxin, posing a significant threat to humans and animals. Ferrous sulfate is a common iron supplement that is used to the treatment of iron-deficiency anemia. Here, we identified an unexpected inhibitory role of ferrous sulfate on A. flavus. With specific fluorescent dyes, we detected several conidial ferroptosis hallmarks in conidia under the treatment of 1 mM Fe²⁺, including nonapoptosis necrosis, iron-dependent, lipid peroxide accumulation, and ROS burst. However, unlike traditional ferroptosis in mammals, Fe²⁺ triggered conidial ferroptosis in A. flavus was regulated by NADPH oxidase (NOXs) activation instead of Fenton reaction. Transcriptomic and some other bioinformatics analyses showed that NoxA in A. flavus might be a potential target of Fe²⁺, and thus led to the occurrence of conidial ferroptosis. Furthermore, noxA deletion mutant was constructed, and both ROS generation and conidial ferroptosis in ΔnoxA was reduced when exposed to Fe²⁺. Taken together, our study revealed an exogenous Fe²⁺-triggered conidial ferroptosis pathway mediated by NoxA of A. flavus, which greatly contributes to the development of an alternative strategy to control this pathogen.

Evaluation of Effects of Ractopamine on Cardiovascular, Respiratory, and Locomotory Physiology in Animal Model Zebrafish Larvae

Ractopamine (RAC) is a beta-adrenoceptor agonist that is used to promote lean and increased food conversion efficiency in livestock. This compound has been considered to be causing behavioral and physiological alterations in livestock like pig. Few studies have addressed the potential non-target effect of RAC in aquatic animals. In this study, we aimed to explore the potential physiological response after acute RAC exposure in zebrafish by evaluating multiple endpoints like locomotor activity, oxygen consumption, and cardiovascular performance. Zebrafish larvae were subjected to waterborne RAC exposure at 0.1, 1, 2, 4, or 8 ppm for 24 h, and the corresponding cardiovascular, respiratory, and locomotion activities were monitored and quantified. In addition, we also performed in silico molecular docking for RAC with 10 zebrafish endogenous β-adrenergic receptors to elucidate the potential acting mechanism of RAC. Results show RAC administration can significantly boost locomotor activity, cardiac performance, oxygen consumption, and blood flow rate, but without affecting the cardiac rhythm regularity in zebrafish embryos. Based on structure-based flexible molecular docking, RAC display similar binding affinity to all ten subtypes of endogenous β-adrenergic receptors, from adra1aa to adra2db, which are equivalent to the human one. This result suggests RAC might act as high potency and broad spectrum β-adrenergic receptors agonist on boosting the locomotor activity, cardiac performance, and oxygen consumption in zebrafish. To validate our results, we co-incubated a well-known β-blocker of propranolol (PROP) with RAC. PROP exposure tends to minimize the locomotor hyperactivity, high oxygen consumption, and cardiac rate in zebrafish larvae. In silico structure-based molecular simulation and binding affinity tests show PROP has an overall lower binding affinity than RAC. Taken together, our studies provide solid in vivo evidence to support that RAC plays crucial roles on modulating cardiovascular, respiratory, and locomotory physiology in zebrafish for the first time. In addition, the versatile functions of RAC as β-agonist possibly mediated via receptor competition with PROP as β-antagonist.