ADVERPred-Web Service for Prediction of Adverse Effects of Drugs

Identification of potential dipeptidyl peptidase IV inhibitors from the ConMedNP library by virtual screening, and molecular dynamics methods

In this study, we screened novel dipeptidyl peptidase IV (DPP4) inhibitors from the ConMedNP library consisting of 3507 molecules. Interestingly, molecular docking, ADMET, and the anti-diabetic activity predictions suggest that three molecules, namely OTH_UD_XX06_1, GB19, and BMC_000104, have a high binding affinity toward DPP4. The molecular dynamics (MD) simulation results suggest that these hit molecules have a stable binding pose and occupy the binding pockets throughout the 200 ns simulation. The presence of intermolecular H-bonding between the ligands and DPP4 was observed throughout the simulation period. Thus, docking and MD results, predicted that the three compounds were the most potent DPP4 inhibitors that could putatively bind to the DPP4 active site via both conventional H-bonding and hydrophobic interactions. These results could aid the discovery of new drugs to treat type 2 diabetes.

From petals to healing: consolidated network pharmacology and molecular docking investigations of the mechanisms underpinning Rhododendron arboreum flower's anti-NAFLD effects

Rhododendron arboreum: Sm., also known as Burans is traditionally used as an anti-inflammatory, anti-diabetic, hepatoprotective, adaptogenic, and anti-oxidative agent. It has been used since ancient times in Indian traditional medicine for various liver disorders. However, the exact mechanism behind its activity against NAFLD is not known. The aim of the present study is to investigate the molecular mechanism of Rhododendron arboreum flower (RAF) in the treatment of NAFLD using network pharmacology and molecular docking methods. Bioactives were also predicted for their drug-likeness score, probable side effects and ADMET profile. Protein-protein interaction (PPI) data was obtained using the STRING platform. For the visualisation of GO analysis, a bioinformatics server was employed. Through molecular docking, the binding affinity between potential targets and active compounds were assessed. A total of five active compounds of RAF and 30 target proteins were selected. The targets with higher degrees were identified through the PPI network. GO analysis indicated that the NAFLD treatment with RAF primarily entails a response to the fatty acid biosynthetic process, lipid metabolic process, regulation of cell death, regulation of stress response, and cellular response to a chemical stimulus. Molecular docking and molecular dynamic simulation exhibited that rutin has best binding affinity among active compounds and selected targets as indicated by the binding energy, RMSD, and RMSF data. The findings comprehensively elucidated toxicity data, potential targets of bioactives and molecular mechanisms of RAF against NAFLD, providing a promising novel strategy for future research on NAFLD treatment.

Inhibition and kinetic studies of phytochemical constituents of Goniothalamus wynaadensis and their isoxazoline derivatives on α-glucosidase

α-Glucosidase, an enzyme involved in post-prandial hyperglycaemia, was used as a target to study the effect of compound(s) isolated from Goniothalamus wynaadensis and its isoxazoline derivatives. Among thirteen compounds screened, compounds 1, 3a and 3j exhibited significant inhibition with IC50 values of 63.42, 61.36 and 58.89 µg/mL, respectively, outperforming acarbose (71.72 µg/mL). Kinetic studies revealed competitive binding for compound 1 and uncompetitive/non-competitive binding for 3a and 3j. Fluorescence quenching showed a linear relationship between I0/I at different inhibitor concentrations. The binding sites in α-glucosidase were ≤ 1. The binding constants 3a (0.7307) > 3j (0.6563) > 1 (0.5415) displayed strong interactions. Docking study revealed binding affinities; 3j (-8.9) > 3a (-7.7) > 1 (-7), and acarbose, 1, 3a and 3j had ARG-312, PHE-157 interactions in common to α-glucosidase. The toxicity profile showed compounds fell in classes IV and V. Overall, the results indicate that compounds 1, 3a and 3j are effective against α-glucosidase.

Identification of Helicobacter pylori-carcinogenic TNF-alpha-inducing protein inhibitors via daidzein derivatives through computational approaches

Gastric cancer is considered a class 1 carcinogen that is closely linked to infection with Helicobacter pylori (H. pylori), which affects over 1 million people each year. However, the major challenge to fight against H. pylori and its associated gastric cancer due to drug resistance. This research gap had led our research team to investigate a potential drug candidate targeting the Helicobacter pylori-carcinogenic TNF-alpha-inducing protein. In this study, a total of 45 daidzein derivatives were investigated and the best 10 molecules were comprehensively investigated using in silico approaches for drug development, namely pass prediction, quantum calculations, molecular docking, molecular dynamics simulations, Lipinski rule evaluation, and prediction of pharmacokinetics. The molecular docking study was performed to evaluate the binding affinity between the target protein and the ligands. In addition, the stability of ligand-protein complexes was investigated by molecular dynamics simulations. Various parameters were analysed, including root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), hydrogen bond analysis, principal component analysis (PCA) and dynamic cross-correlation matrix (DCCM). The results has confirmed that the ligand-protein complex CID: 129661094 (07) and 129664277 (08) formed stable interactions with the target protein. It was also found that CID: 129661094 (07) has greater hydrogen bond occupancy and stability, while the ligand-protein complex CID 129664277 (08) has greater conformational flexibility. Principal component analysis revealed that the ligand-protein complex CID: 129661094 (07) is more compact and stable. Hydrogen bond analysis revealed favourable interactions with the reported amino acid residues. Overall, this study suggests that daidzein derivatives in particular show promise as potential inhibitors of H. pylori.

Computational pharmacology profiling of borapetoside C against melanoma

Melanoma,also known as a 'black tumor', begins in the melanocytes when cells (that produce pigment) grows out of control. Immunological dysregulation, which raises the risk for multiple illnesses, including melanoma, may be influenced by stress tiggered through viral infection, long term effects of ultraviolet radiation, environmental pollutants etc. Borapetoside C is one of the phytoconstituents from Tinospora crispa, and its biological source has been reported for its antistress property. Network pharmacology and KEGG pathway analysis of borapetoside C-regulated proteins were conducted to identify the hub genes involved in melanoma development. Further, a molecular docking was performed between borapetoside C and targets involved in melanoma. Further, the top 3 complexes were selected based on the binding energy to conduct molecular dynamics simulations to evaluate the stability of ligand-protein complex followed by principal component analysis and dynamic cross-correlation matrix. In addition, borapetoside C was also screened for its pharmacokinetics and toxicity profile. Network Pharmacology studies and KEGG pathway analysis revealed 8 targets involved in melanoma. Molecular docking between borapetoside C and targets involved in melanoma identified 3 complexes with minimum binding i.e. borapetoside C- MAP2K1, MMP9, and EGFR. Further, molecular dynamics simulations showed a stable complex of borapetoside C with MMP9 and EGFR. The present study suggested that borapetoside C may target MMP9 and EGFR to possess an anti-melanoma property. This finding can be useful in developing a novel therapeutic agent against melanoma from a natural source.Communicated by Ramaswamy H. Sarma.

Comparative Analysis of the Structure and Pharmacological Properties of Some Piperidines and Host-Guest Complexes of β-Cyclodextrin

Pain and anesthesia are a problem for all physicians. Scientists from different countries are constantly searching for new anesthetic agents and methods of general anesthesia. In anesthesiology, the role and importance of local anesthesia always remain topical. In the present work, a comparative analysis of the results of pharmacological studies on models of the conduction and terminal anesthesia, as well as acute toxicity studies of the inclusion complex of 1-methyl-4-ethynyl-4-hydroxypiperidine (MEP) with β-cyclodextrin, was carried out. A virtual screening and comparative analysis of pharmacological activity were also performed on a number of the prepared piperidine derivatives and their host-guest complexes of β-cyclodextrin to identify the structure-activity relationship. Various programs were used to study biological activity in silico. For comparative analysis of chemical and pharmacological properties, data from previous works were used. For some piperidine derivatives, new dosage forms were prepared as beta-cyclodextrin host-guest complexes. Some compounds were recognized as promising local anesthetics. Pharmacological studies have shown that KFCD-7 is more active than reference drugs in terms of local anesthetic activity and acute toxicity but is less active than host-guest complexes, based on other piperidines. This fact is in good agreement with the predicted results of biological activity.

Structure based virtual screening and molecular dynamics of natural anti-biofilm compounds against SagS response regulator/sensor kinase in Pseudomonas aeruginosa

SagS sensor regulator plays a vital role in biofilm development of Pseudomonas aeruginosa which subsequently makes the cells more tolerant to various antimicrobials. The multidrug resistance (MDR) issue has risen substantially in recent years and is considered a global threat. Therefore, alternative compounds should be unearthed immediately to address the issues related to P. aeruginosa drug resistance for which SagS could be a candidate. The present study is an attempt to screen natural anti-biofilm compounds as the potent inhibitors of SagS. Twenty natural anti-biofilm/quorum sensing inhibiting compounds were retrieved from various literatures with significant inhibitory effects against P. aeruginosa biofilm from in-vitro experiments which were screened using various pharmacokinetic parameters. The screened and three standard drugs were docked against SagS-HisKA using AutoDock 4.2 tool, which were further analysed by MD simulations to understand the binding mode of compounds and dynamic behaviour of the complexes. Two potential anti-biofilm natural compounds, pinocembrin with binding affinity (-7.19 kcal/mol), vestitol (-7.18 kcal/mol) and the standard drug ceftazidime (-8.89 kcal/mol) were selected based on filtered parameters and better binding affinity. The trajectory analysis of MD simulations reflected Pinocembrin in stabilizing the system compared to ceftazidime. The existing reports state that the natural products represent promising source of therapy with least or almost nil adverse effect compared to synthetic drugs which is well collated with our in-silico findings. This investigation can save both time and cost required for in-vitro and in-vivo analysis for designing of a novel anti-biofilm agent against P. aeruginosa biofilm-associated infections.Communicated by Ramaswamy H. Sarma.

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

Aim: The purpose of this study was to establish a mode of action for diosgenin against breast cancer employing a range of system biology tools and to corroborate its results with experimental facts. Methodology: The diosgenin-regulated domains implicated in breast cancer were enriched in the Kyoto Encyclopedia of Genes and Genomes database to establish diosgenin-protein(s)-pathway(s) associations. Later, molecular docking and the lead complexes were considered for molecular dynamics simulations, MMPBSA, principal component, and dynamics cross-correlation matrix analysis using GROMACS v2021. Furthermore, survival analysis was carried out for the diosgenin-regulated proteins that were anticipated to be involved in breast cancer. For gene expression analyses, the top three targets with the highest binding affinity for diosgenin and tumor expression were examined. Furthermore, the effect of diosgenin on cell proliferation, cytotoxicity, and the partial Warburg effect was tested to validate the computational findings using functional outputs of the lead targets. Results: The protein-protein interaction had 57 edges, an average node degree of 5.43, and a p-value of 3.83e-14. Furthermore, enrichment analysis showed 36 KEGG pathways, 12 cellular components, 27 molecular functions, and 307 biological processes. In network analysis, three hub proteins were notably modulated: IGF1R, MDM2, and SRC, diosgenin with the highest binding affinity with IGF1R (binding energy -8.6 kcal/mol). Furthermore, during the 150 ns molecular dynamics (MD) projection run, diosgenin exhibited robust intermolecular interactions and had the least free binding energy with IGF1R (-35.143 kcal/mol) compared to MDM2 (-34.619 kcal/mol), and SRC (-17.944 kcal/mol). Diosgenin exhibited the highest cytotoxicity against MCF7 cell lines (IC₅₀ 12.05 ± 1.33) µg/ml. Furthermore, in H₂O₂-induced oxidative stress, the inhibitory constant (IC₅₀ 7.68 ± 0.51) µg/ml of diosgenin was lowest in MCF7 cell lines. However, the reversal of the Warburg effect by diosgenin seemed to be maximum in non-cancer Vero cell lines (EC₅₀ 15.27 ± 0.95) µg/ml compared to the rest. Furthermore, diosgenin inhibited cell proliferation in SKBR3 cell lines more though. Conclusion: The current study demonstrated that diosgenin impacts a series of signaling pathways, involved in the advancement of breast cancer, including FoxO, PI3K-Akt, p53, Ras, and MAPK signaling. Additionally, diosgenin established a persistent diosgenin-protein complex and had a significant binding affinity towards IGF1R, MDM2, and SRC. It is possible that this slowed down cell growth, countered the Warburg phenomenon, and showed the cytotoxicity towards breast cancer cells.

Identification of novel mycocompounds as inhibitors of PI3K/AKT/mTOR pathway against RCC

PI3K/AKT/mTOR pathway is one of the frequently disrupted signaling pathways in renal cell carcinoma (RCC) that plays a significant role in tumor formation, disease progression and therapeutic resistance. Therefore, novel natural molecules targeting the critical proteins of this pathway will provide the best alternative to existing drugs, which are toxic and develops resistance. Recent studies have recognized the anti-cancer therapeutic potential of mycocompounds. The current study is focused on screening various mycocompounds from Astraeus hygrometricus against key cancer signaling proteins phosphoinositide 3-kinase (PI3K), protein kinase B, PKB (AKT1) and mammalian target of rapamycin (mTOR). We also studied in-silico cancer cells cytotoxicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) profiles to elucidate the molecular mechanism against RCC and also to uncover the pharmacokinetic profile of these compounds. Astrakurkurone and Ergosta-4,6, 8-(14) 22-tetraene-3-one were the two most efficacious compounds with highest interaction scores and bonding. These compounds were both active against RCC4 and VMRC-RCZ cell lines of RCC. The ADME profiles of both were satisfactory based on druglikeness and bioavailability score criteria. Thus, this proposed study identified astrakurkurone and ergosta-4,6, 8-(14) 22-tetraene-3-one as potential anticancer drug candidates, and provides comparative structural insight into their binding to the 3 protein kinases.

Isonicotinic acid N-oxide, from isoniazid biotransformation by Aspergillus niger, as an InhA inhibitor antituberculous agent against multiple and extensively resistant strains supported by in silico docking and ADME prediction

Biotransformation of isoniazid produced isonicotinic acid (1), isonicotinic acid N-oxide (2), and isonicotinamide (3) which were isolated by column chromatography using silica gel and Sephadex LH 20 and elucidated using various spectroscopies. This is the first report for isolation of 2_. Antituberculosis activity was evaluated against Mycobacterium tuberculosis strains: drug sensitive (DS), multiple drug resistant (MDR) and extensively drug resistant (XDR). 1-3 and isoniazid showed MICs of 63.49, 0.22, 15.98 and 0.88 µM, respectively, against the DS strain. For the MDR strain, 2 and 3 exhibited MICs of 28.06 and > 1000 µM, respectively, while 1 was inactive. Moreover, 2 had an MIC of 56.19 µM against XDR strain, while 1 and 3 were inactive. Docking simulation using enoyl ACP reductase (InhA) revealed favorable protein-ligand interactions. In silico study of pharmacokinetics and hepatotoxicity predicted 1-3 to have good oral bioavailability and 2 to have a lower hepatoxicity probability than isoniazid.

GLUT-2 mediated glucose uptake analysis of Duranta repens: In-silico and In-vitro approach

Background

Type-2 diabetes mellitus is a common metabolic disorder characterized by insulin resistance, a relative impairment in insulin secretion, and a certain degree of genetic predisposition. The rapid rise in the prevalence of diabetes mellitus around the world has assisted in the development of new pharmacologically active compounds. The current study was aimed to investigate and validate the anti-diabetic activity of wild-grown plant Duranta repens L.

Material and methods

In-silico molecular docking via AutoDock tools 4.2 and in-vitro glucose uptake assay using yeast cells was performed to investigate the anti-diabetic property of plant Duranta repens. Further, mRNA-based gene ontology enrichment analysis was performed to predict the imitated ontology by the bio-actives from Duranta repens.

Results

The in-silico study results reveal that among the 9 active phytoconstituents docked against GLUT-2 protein, α-onocerin possessed the highest binding affinity of -10.23 kcal/mol with no predicted adverse effects and also complies with Lipinski's rule of five. Also, in-vitro studies reflected in a 5 mM glucose solution, hydro-alcoholic extract of Duranta repens at different concentrations enhanced glucose uptake in yeast cells.

Conclusion

Duranta repens extract enhanced the glucose uptake in yeast cells which may be due to the presence of α-onocerin; possessed the better interaction. Also, no adverse effects were predicted for α-onocerin. Thus, it can be speculated  that Duranta repens may possess anti-diabetic activity which may be due to α-onocerin and other related bioactives; needs to be further confirmed vi a  experimental studies.

Ficus benghalensis promotes the glucose uptake- Evidence with in silico and in vitro

Background

Ficus benghalensis L. is traditionally used to manage diabetes; also used in various herbal formulations, and is indicated as an insulin sensitizer. Hence, present work attempted in identifying the probable lead hits to promote glucose uptake via computational approach followed by experimental evaluation of hydroalcoholic extract of Ficus benghalensis L. bark in yeast cells.

Methods

The in vitro assay for glucose uptake was performed in the baker yeast whereas in-silico study involved retrieving the phytoconstituents from open sources, and predicting for probable targets of diabetes followed by drug-likeness score, probable side effects, and ADMET profile. Homology modeling was performed to construct the target protein glucose transporter-2. In addition, the binding affinity of each ligand with glucose transporter was predicted using AutoDock 4.2.

Results

A total of 17 phytoconstituents from F. benghalensis were identified to possess the anti-diabetic effects. Among them, 4-methoxybenzoic acid scored the highest drug-likeness score and lupeol acetate had the maximum binding affinity of -8.02 kcal/mol with 9 pi-interactions via Tyr324, Phe323, Ile319, Ile200, Ile28, Phe24, and Ala451. Similarly, the extract showed the highest glucose uptake efficacy in yeast cells at 500 µg/mL.

Conclusion

Herein the present study reflected the probable activity of the phytoconstituents from F. benghalensis in promoting the glucose uptake via the in silico and in vitro approaches.

Network pharmacology and in vitro testing of Theobroma cacao extract's antioxidative activity and its effects on cancer cell survival

Theobroma cacao L. is a commercially important food/beverage and is used as traditional medicine worldwide against a variety of ailments. In the present study, computational biology approaches were implemented to elucidate the possible role of cocoa in cancer therapy. Bioactives of cocoa were retrieved from the PubChem database and queried for targets involved in cancer pathogenesis using BindingDB (similarity index ≥0.7). Later, the protein-protein interactions network was investigated using STRING and compound-protein via Cytoscape. In addition, intermolecular interactions were investigated via molecular docking. Also, the stability of the representative complex Hirsutrin-epidermal growth factor receptor (EGFR) complex was explored using molecular dynamics simulations. Crude extract metabolite profile was carried out by LC-MS. Further, anti-oxidant and cytotoxicity studies were performed in Chinese hamster ovary (normal) and Ehrlich ascites carcinoma (cancer) cell lines. Herein, the gene set enrichment and network analysis revealed 34 bioactives in cocoa targeting 50 proteins regulating 21 pathways involved in cancer and oxidative stress in humans. EGFR scored the highest edge count amongst 50 targets modulating 21 key pathways. Hence, it was selected as a promising anticancer target in this study. Structural refinement of EGFR was performed via all-atom molecular dynamics simulations in explicit solvent. A complex EGFR-Hirsutrin showed the least binding energy (-7.2 kcal/mol) and conserved non-bonded contacts with binding pocket residues. A stable complex formation of EGFR-Hirsutrin was observed during 100 ns MD simulation. In vitro studies corroborated antioxidant activity for cocoa extract and showed a significantly higher cytotoxic effect on cancer cells compared to normal cells. Our study virtually predicts anti-cancer activity for cocoa affected by hirsutrin inhibiting EGFR. Further wet-lab studies are needed to establish cocoa extract against cancer and oxidative stress.

System biology-based investigation of Silymarin to trace hepatoprotective effect

Silymarin is used as a hepatoprotective agent since ancient times which could be via its potent anti-oxidant effect. However, the mode of silymarin for the hepatoprotective effect has not been established with the targets involved in hepatic cirrhosis. The present study investigated the multiple interactions of the flavonolignans from Silybum marianum with targets involved in hepatic cirrhosis using a series of system biology approaches. Chemo-informative tools and databases i.e. DIGEP-Pred and DisGeNET were used to predict the targets of flavonolignans and proteins involved in liver cirrhosis respectively. Further, STRING was used to enrich the protein-protein interaction for the flavonolignans-modulated targets. Similarly, molecular docking was performed using AutoDock Vina. Additionally, molecular dynamics simulation and MM-PBSA calculations were carried out for the lead-hit complexes by GROMACS. Thirteen flavonolignans were identified from S. marianum, in which silymonin exhibited the highest drug-likeness score i.e. 1.09. Similarly, CTNNB1 was found to be regulated by the 12 different flavonolignans and was majorly expressed within the compound(s)-protein(s)-pathway(s) network. Further, silymonin had the highest binding affinity; binding energy -9.2 kcal/mol with the CTNNB1 and formed very stable hydrogen bond interactions with Arg332, Ser336, Lys371, and Arg475 throughout 100 ns molecular dynamic production run. The binding free energy of CTNNB1-silymonin complex was found to be -15.83 ± 2.71 kcal/mol. The hepatoprotective property of S. marianum may be due to the presence of silymonin and silychristin; this could majorly modulate CTNNB1, HMOX1, and CASP8 in combination with other flavonolignans. Our findings further suggest designing the in-vitro and in-vivo studies to validate the interaction of flavonolignans with identified targets to strengthen present findings of S. marianum as a hepatoprotective..

Hepatitis C Virus NS3/4A Inhibition and Host Immunomodulation by Tannins from Terminalia chebula: A Structural Perspective

Terminalia chebula Retz. forms a key component of traditional folk medicine and is also reported to possess antihepatitis C virus (HCV) and immunomodulatory activities. However, information on the intermolecular interactions of phytochemicals from this plant with HCV and human proteins are yet to be established. Thus, by this current study, we investigated the HCV NS3/4A inhibitory and host immune-modulatory activity of phytocompounds from T. chebula through in silico strategies involving network pharmacology and structural bioinformatics techniques. To start with, the phytochemical dataset of T. chebula was curated from biological databases and the published literature. Further, the target ability of the phytocompounds was predicted using BindingDB for both HCV NS3/4A and other probable host targets involved in the immune system. Further, the identified targets were docked to the phytochemical dataset using AutoDock Vina executed through the POAP pipeline. The resultant docked complexes with significant binding energy were subjected to 50 ns molecular dynamics (MD) simulation in order to infer the stability of complex formation. During network pharmacology analysis, the gene set pathway enrichment of host targets was performed using the STRING and Reactome pathway databases. Further, the biological network among compounds, proteins, and pathways was constructed using Cytoscape 3.6.1. Furthermore, the druglikeness, side effects, and toxicity of the phytocompounds were also predicted using the MolSoft, ADVERpred, and PreADMET methods, respectively. Out of 41 selected compounds, 10 were predicted to target HCV NS3/4A and also to possess druglike and nontoxic properties. Among these 10 molecules, Chebulagic acid and 1,2,3,4,6-Pentagalloyl glucose exhibited potent HCV NS3/4A inhibitory activity, as these scored a lowest binding energy (BE) of −8.6 kcal/mol and −7.7 kcal/mol with 11 and 20 intermolecular interactions with active site residues, respectively. These findings are highly comparable with Asunaprevir (known inhibitor of HCV NS3/4A), which scored a BE of −7.4 kcal/mol with 20 key intermolecular interactions. MD studies also strongly suggest that chebulagic acid and 1,2,3,4,6-Pentagalloyl glucose as promising leads, as these molecules showed stable binding during 50 ns of production run. Further, the gene set enrichment and network analysis of 18 protein targets prioritized 10 compounds and were predicted to potentially modulate the host immune system, hemostasis, cytokine levels, interleukins signaling pathways, and platelet aggregation. On overall analysis, this present study predicts that tannins from T. chebula have a potential HCV NS3/4A inhibitory and host immune-modulatory activity. However, further experimental studies are required to confirm the efficacies.

Identification of medicinal compounds as potential inhibitors for mutated isocitrate dehydrogenases against chondrosarcoma

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Virtual screening of 5000 novel medicinal compounds procured two compounds (5-galloylquinic acid and artocarpetin) capable of establishing interaction with both mutated IDH1 and IDH2 proteins implicated in chondrosarcoma.

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Cell lining prediction studies revealed that both 5-galloylquinic acid and artocarpetin sensitizes chondrosarcoma cell lines and has good cytotoxic influence on CHSA8926 and CHSA0011 cells.

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These compounds possess high acute toxicity values to incite adverse reaction and organ damage in rodents.

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ITGAV, CAPRIN-1, CCL5 COG5 and TNFRSF10B gene are successfully downregulated that are involved in the metastasis inflammation and chondrogenesis by these compounds.

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TP53 expression enhancer, free radical scavenger, MAP kinase stimulant, MM9 expression inhibitor and chemo preventive agent were some biological properties predicted by Prediction of Activity Spectra for substances (PASS) database.

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Artocarpetin had good ADME and druglikness properties as compared to 5-galloylquinic acid, as this compound had low bioavailability score and one lipinski violation for druglikness.

Chondrosarcoma is the third most common cartilaginous bone tumour that is insusceptible to radio- and chemotherapy and it is inclined to metastasis. These resistant qualities are facilitated by mutant variants of isocitrate dehydrogenases (IDH) 1–2 enzyme. These mutant enzymes promote oncogenesis of chondrocytes by changing their epigenetic wardrobe leading to tumour formation. Presently, there are lack of drugs available to be exploited as a remedy for this disease. On the other hand, majority of chemotherapeutic drugs induce cytotoxicity in the cancer cells at the cost of harming surrounding healthy cells, jeopardizing human life. The current study is focused on screening various medicinal compounds against IDH1 and IDH2 combined with insilico gene expression, cancer cells cytotoxicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) studies to elucidate the molecular mechanism against chondrosarcoma and also to uncover pharmacokinetic profile of these compounds. Screening of 5000+ compounds filtered two efficacious compounds (Artocarpetin and 5-Galloylquinic acid) capable of establishing hydrogen bond connections with both IDH variants. Other studies showed that these compounds downregulate ITGAV, CARPIN1, CCL5 and COG5 and TNFRSF10B gene that reduces chondrogenesis and inflammation, Artocarpetin and 5-galloylquinic acid are TP53 expression enhancer and inhibit MM9 expression that promote immunomodulation and apoptosis in these cancers. These compounds are both active against CHSA8926 and CHSA011 cell line of chondrosarcoma. However, the ADME profile of 5-galloylquinic acid is slightly unsatisfactory based on druglikness and bioavailability score criteria as compared to artocarpetin. Both of these compounds are class-5 chemicals and require high doses to elicit adverse response. Our results suggest that artocarpetin and 5-galloylquinic acid are efficacious drug candidates and could be further exploited to validate these findings in vitro.

Molecular modelling and de novo fragment-based design of potential inhibitors of beta-tubulin gene of Necator americanus from natural products

The emergence of drug resistance against the known hookworm drugs namely albendazole and mebendazole and their reduced efficacies necessitate the need for new drugs. Chemically diverse natural products present plausible templates to augment hookworm drug discovery. The present work utilized pharmacoinformatics techniques to predict African natural compounds ZINC95486082, ZINC95486052 and euphohelionon as potential inhibitory molecules of the hookworm Necator americanus β tubulin gene. A library of 3390 compounds was screened against a homology-modelled structure of β tubulin. The docking results obtained from AutoDock Vina was validated with an acceptable area under the curve (AUC) of 0.714 computed from the receiver operating characteristic (ROC) curve. The three selected compounds had favourable binding affinities and were predicted to form no interactions with the resistance-associated mutations Phe167, Glu198 and Phe200. The compounds were predicted as anthelmintics using a Bayesian-based technique and were pharmacologically profiled to be druglike. Further molecular dynamics simulations and MM-PBSA calculations showed the compounds as promising anthelmintic drug leads. Novel critical residues comprising Leu246, Asn247 and Asn256 were also predicted for binding. Euphohelionon was selected as a template for the de novo fragment-based design of five compounds labelled A1, A2, A3, A4 and A5; with four of them having SAscore values below 6, denoting easy synthesis. All the five de novo molecules docked firmly in the binding pocket of the β tubulin with no binding interactions with the three known resistance mutation residues. Binding energies of −8.2, −7.6, −7.3, −7.2 and −6.8 kcal/mol were obtained for A1, A2, A3, A4 and A5, respectively. The identified compounds can serve as treasure troves from which future potent anthelmintics can be designed. The current study strives to assuage the hookworm disease burden, especially making available molecules with the potential to circumvent the chemoresistance.

Gene ontology enrichment analysis of PPAR-γ modulators from Cassia glauca in diabetes mellitus

BACKGROUND

PPAR-γ has an integrative role in the management of insulin resistance; ligands of this receptor have emerged as potent insulin sensitizers and may modulate proteins involved in the pathogenesis of diabetes mellitus. Hence the present study is aimed to identify PPAR-γ modulators from the plant Cassia glauca and predict the ontology enrichment analysis utilizing various in-silico tools.

METHODS

ChEBI database was used to mine the phytoconstituents present in the plant C. glauca, SwissTargetPrediction database was used to identify the targets, and scrutinizing of phytoconstituents modulating PPAR-γ was performed. Autodock4.0 was used to dock phytoconstituent ligands with the target PPAR-γ. Multiple open-source databases and in-silico tools were utilized to predict the drug-likeness characters and predict side effects of the phytoconstituents modulating PPAR-γ and STRING database was used to construct a network between the modulated genes.

RESULTS

Twenty-four phytoconstituents were identified from the plant Cassia glauca from which four were found to modulate PPAR-γ, sennoside was predicted to have the greatest drug-likeness score and a significantly less side effect whereas diphenyl sulfone was predicted to show hepatotoxicity with the greatest pharmacological activity of 0.815. [epicatechin-(4beta- > 8)]5-epicatechin showed the lowest binding affinity with target PPAR-γ i.e. -8.6 kcal/mol and possessing a positive drug-likeness score with no side effect data.

CONCLUSION

Bioctives were found free from probable side effects leaving out diphenyl sulfone having a prediction of hepatotoxicity, the anti-diabetic property of the plant may be due to the presence of [epicatechin-(4beta- > 8)]5-epicatechin which needs further validation by in-vitro and in-vivo protocols.

Exploring Aromatic Medicinal Compounds for the Treatment of Amyotrophic Lateral Sclerosis

Purpose: Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative condition, in which motor neurons start to degenerate due to the accumulation of protein aggregates in the neuron cytoplasm. The formation of aggregates causes neurotoxicity, facilitated by the N-terminal domain (NTD) of the transactive response DNA-binding protein-43 (TDP-43). Therapies used to treat ALS manage secondary symptoms, but do not stop the activity of the rogue NTD domain of TDP-43. Therefore, new drug candidates should be designed to deal efficiently with this disease by inhibiting the domains involved in the development of ALS. This study determined the chemical affinity of aromatic medicinal compounds with NTD. Screening of 1323 medicinal compounds was conducted with PYRX 0.9 software against NTD. Compounds obtained from this analysis were further used to predict absorption, distribution, metabolism, excretion, and toxic (ADMET) properties and their effect on major gene targets of ALS. Results: From 1300 + compounds, acetovanillone showed binding affinity for NTD and had good ADMET and drug likeness attributes. This compound reduced the expression of CXCL2, NOP56, and SOD1 genes implicated in ALS pathogenesis. Conclusion: These results concluded that acetovanillone is a candidate drug for in vitro and clinical studies into the exploitation of drugs within ALS therapeutics.

Liver Injury with Ulipristal Acetate: Exploring the Underlying Pharmacological Basis

Introduction

The European Medicines Agency has suspended the use of ulipristal acetate (UPA) in the treatment of uterine fibroids and is reassessing its association with a risk of liver injury.

Objectives

Our objectives were to characterize the post-marketing reporting of drug-induced liver injury (DILI) with UPA and investigate the underlying pharmacological basis.

Methods

We queried the worldwide FDA Adverse Event Reporting System and performed a disproportionality analysis, selecting only hepatic designated medical events (DMEs) where UPA was reported as suspect. The reporting odds ratios (RORs) were calculated, and we considered a lower limit of the 95% confidence interval (LL95% CI) > 1 as significant. Physiochemical/pharmacokinetic features were extracted to assess the risk of hepatotoxicity by applying predictive DILI risk models. Mifepristone and leuprolide were selected as comparators.

Results

A significantly higher proportion of liver disorders was reported for UPA than for mifepristone (2.9 vs. 0.8%; p < 0.00001) and leuprolide (2.9 vs. 1.6%; p = 0.015). As regards hepatic DMEs, statistically significant RORs were found for autoimmune hepatitis (N = 5; LL95% CI 16.8), DILI (n = 5; LL95% CI 5.9), and acute hepatic failure (N = 5; LL95% CI 9.3). No signals of DILI emerged for mifepristone and leuprolide acetate. UPA and mifepristone showed high lipophilicity and hepatic metabolism (predicted intermediate DILI risk). Leuprolide exhibited contrasting features, resulting in no DILI concern. Inhibition of different liver transporters and the presence of a reactive metabolite were also recognised for UPA.

Conclusion

Different drug properties previously linked to the occurrence of DILI may partially explain the reporting pattern observed with UPA. Our “bedside-to-bench” approach may support regulators in the risk–benefit assessment of UPA.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00975-8) contains supplementary material, which is available to authorized users.

Identification of α-amylase inhibitors from flavonoid fraction of Feronia elephantum and its integration with in-silico studies

Postprandial hyperglycemia is associated with an increase in blood glucose levels after a meal, which is further associated with various risk factors like cardiovascular diseases. α-amylase is a digestive enzyme and secreted by the salivary glands and pancreas, which helps to catalyze the hydrolysis of the internal α-1,4-glycosidic linkages in starch breaking them into smaller units. Hence, the present study is aimed to identify flavonoids from the fruit pulp of Feronia elephantum as α-amylase inhibitors via in-silico and in-vitro protocols. In-silico tools like ADVERPred, PubChem, MolSoft, Discovery studio 2019, and Autodock 4.0 were used to predict the information related to phytoconstituents, drug-likeness character, and probable side effects. In-vitro α-amylase inhibitory activity was performed with five different concentrations of flavonoid fraction of hydroalcoholic extract of the fruit pulp of Feronia elephantum using 1% starch solution and DNS reagent. Four flavonoids were identified from 25 bio-actives present in the fruit pulp of Feronia elephantum. Three bio-actives were predicted to possess a positive drug-likeness score, from which 5,4-dihydroxy3-3(3-methyl-but2-enyl)3,5,6-trimethoxy-flavone-7-O-β-d-Glucopyranoside was predicted to possess the highest drug-likeness score of 0.70. Vitexin and 5,4-dihydroxy3-3(3-methyl-but2-enyl)3,5,6-trimethoxy-flavone-7-O-β-d-Glucopyranoside were predicted to possess nephrotoxicity as an adverse effect. The percent inhibition of α-amylase by a flavonoid-rich fraction at 100 μg/ml was found to be 45.95% as compared to standard acarbose with 74.79% inhibition at 100 μg/ml. Further, docking studies predicted that vitexin possessed the highest binding affinity (binding energy - 7.98 kcal/mol) as compared to standard acarbose with binding energy - 5.24 kcal/mol. There were no significant side effects predicted, in-vitro α-amylase inhibitory activity of the flavonoid-rich fraction may be due to the presence of vitexin, predicted via in-silico molecular docking; further, which needs to be further validated via in-vivo protocols.

Dual inhibition of COVID-19 spike glycoprotein and main protease 3CLpro by Withanone from Withania somnifera

Objective

To identify the safe and effective natural inhibitors of spike glycoprotein and main protease 3CLpro using potential natural antiviral compounds which are studied under various animal models and viral cell lines.

Methods

First, compounds were retrieved from the PubChem database and predicted for their druggability using the MolSoft web server, and compounds having drug-like property were predicted for major adverse drug reactions like cardiotoxicity, hepatotoxicity, arrhythmia, myocardial infarction, and nephrotoxicity using ADVERpred. Docking of nontoxic antiviral compounds with spike glycoprotein and main protease 3CLpro was performed using AutoDock vina by PyRx 0.8 version. The stability of compound-protein interactions was checked by molecular dynamic (MD) simulation using Schrodinger Desmond software.

Results

Based on the druggable and nontoxic profile, nine compounds were selected. Among them, Withanone from Withania somnifera showed the highest binding affinity and best fit at active sites 1 of spike glycoprotein (glycosylation site) and main protease 3CLpro via interacting with active site amino acid residues before and after MD simulation at 50 ns. Withanone, which may reduce the glycosylation of SARS-CoV-2 via interacting with Asn343 and inhibit viral replication.

Conclusion

The current study reports Withanone as a non-toxic antiviral against SARS-CoV-2 and serve as a potential lead hit for further experimental validation.

Gene set enrichment analysis of PPAR-γ regulators from Murraya odorata Blanco

BACKGROUND

Peroxisome proliferator-activated receptor gamma (PPAR-γ) is reported to regulate insulin sensitivity and progression of Type 2 diabetes mellitus (T2DM). Hence the present study is aimed to identify PPAR-γ regulators from Murraya odorata Blanco and predict their role to manage T2DM.

METHODS

Multiple in-silico tools and databases like SwissTargetPrediction, ADVERPred, PubChem, and MolSoft, were used to retrieve the information related to bioactives, targets, druglikeness character, and probable side effects as applicable. Similarly, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to identify the regulated pathways. Further, the bioactives-protein-pathways network interaction was constructed using Cytoscape. Finally, molecular docking was performed using Autodock4.

RESULTS

Twenty-five bioactives were shortlisted in which six were predicted as PPAR-γ modulators. Among them, stigmasterol was predicted to possess the best binding affinity towards PPAR-γ and possessed no side effects. Similarly, n-hexadecanoic acid was predicted to modulate the highest number of proteins, and protein CD14 was targeted by the highest number of bioactives. Further, the PI3K-Akt pathway was predicted as the maximum modulated genes.

CONCLUSIONS

The anti-diabetic property of the Murraya odorata Blanco of fruit pulp may be due to the presence of n-hexadecanoic acid and stigmasterol; may also involve in the regulation of the PI3K-Akt pathway which needs further investigated by in-vitro and in-vivo protocols.

Identification of PTP1B regulators from Cymbopogon citratus and its enrichment analysis for diabetes mellitus

PTP1B is identified as the insulin signaling pathway downregulator; involved in pancreatic β-cell apoptosis. Further, it associates in regulating multiple pathways in diabetes mellitus; kindled us to identify the binding affinity of bioactives from Cymbopogon citratus by targeting PTP1B and identify the probably associated with it; further identifying the probable pathways involved in diabetes mellitus. In this regard, ChEBI database was used to retrieve bio-actives from C. citrates and 3D structures for the same were obtained from the PubChem database. The energy of bioactives was minimized and converted into ligand and the docking was carried using autodock 4.0 against PTP1B. Further, multiple characters of bio-actives like drug-likeness score, ADMET profile, probable adverse effects, and boiled egg model for bioavailability were also studied. Swertiajaponin was predicted for the highest drug-likeness score i.e. 0.26. However, swertiajaponin was predicted with the highest probable side effect of nephrotoxicity with pharmacological activity of 0.478. Similarly, swertiajaponin was predicted for the highest binding affinity with PTP1B with the binding energy of - 8.3 kcal/mol. Likewise, KEGG identified 80 pathways associated with PTP1B modulation in which 7 pathways were involved in diabetes mellitus in which FoxO signaling pathway was predicted to have the least false discovery rate by modulating 7 genes. Swertiajaponin could act as the potent inhibitor of PTP1B; scored highest druglikeness score but possessed minimum GIT absorptivity; further, PTP1B was identified to be linked with multiple pathways that are concerned with diabetes mellitus.

Computer-Aided Estimation of Biological Activity Profiles of Drug-Like Compounds Taking into Account Their Metabolism in Human Body

Most pharmaceutical substances interact with several or even many molecular targets in the organism, determining the complex profiles of their biological activity. Moreover, due to biotransformation in the human body, they form one or several metabolites with different biological activity profiles. Therefore, the development and rational use of novel drugs requires the analysis of their biological activity profiles, taking into account metabolism in the human body. In silico methods are currently widely used for estimating new drug-like compounds' interactions with pharmacological targets and predicting their metabolic transformations. In this study, we consider the estimation of the biological activity profiles of organic compounds, taking into account the action of both the parent molecule and its metabolites in the human body. We used an external dataset that consists of 864 parent compounds with known metabolites. It is shown that the complex assessment of active pharmaceutical ingredients' interactions with the human organism increases the quality of computer-aided estimates. The toxic and adverse effects showed the most significant difference: reaching 0.16 for recall and 0.14 for precision.

Matrix metalloproteinase inhibitors identified from Camellia sinensis for COVID-19 prophylaxis: an in silico approach

To respond to the public panic, government and private research organizations of every country keep working on the COVID-19 pandemic, even though still there is a lack of more efficacious medicine for the choice of Coronavirus disease treatment. To counteract on this situation several approved drugs including anti-malarial (hydroxychloroquine and chloroquine), and few anti-viral (remdesvir) agents are choice of treatment for COVID-19. However, these agents suffer from certain limitation in their uses and pointed that there is no specific treatment or vaccine available to counter this contagious disease. Hence, there is urgent requirement to find a specific cure for the disease. In this view, there are several ongoing clinical trials of both western and traditional medicines. In present study, phytochemicals from Camellia sinensis were retrieved from the database and identified based on their ability to inhibit matrix metalloproteinase (MMPs) against SARS-CoV-2 main protease. Camellia sinensis entails of a massive number of phytochemicals with a good source of polyphenols such as Catechin, Epicatechin, Epigallocatechin and (–)-Epigallocatechin gallate. Molecular docking was performed using the GLIDE docking module of Schrodinger Suite software. The analysis displayed docking score for the five polyphenols i.e. theaflavin (− 8.701), 1-O-caffeoylquinic acid (− 7.795), Genistein (− 7.168), Epigallocatechin 3-gallate (− 6.282) and Ethyl trans-caffeate (− 5.356). Interestingly, theaflavin and Epigallocatechin 3-gallate have not revealed any side effects. These polyphenolic compounds had a strong binding affinity with hydrogen bonds and a good drug-likeness score. Therefore, Camellia sinensis could be the beneficial option in the prophylaxis of the COVID-19 outbreak.

In silico study of thymohydroquinone interaction with blood-brain barrier disrupting proteins

Aim:

To evaluate the inhibitory interaction of thymohydroquinone against blood–brain barrier (BBB)-associated neuropsychiatric and neurodegenerative disorders.

Materials & methods:

An elaborated in silico study was designed to evaluate the interaction of thymohydroquinone with BBB-disrupting proteins and to highlight its pharmacokinetic and safety attributes.

Results:

Thymohydroquinone demonstrated stable interaction with BBB-disrupting protein active site with Ki (inhibition constant) ranges of (2.71 mM–736.15 μM), binding energy (-4.3 to 5.6 Kcal/mol), ligand efficiency (-0.36 to 0.42 Kcal/mol) and root mean square deviation value of (0.80–2.59 Å).

Conclusion:

Further pharmacokinetic analysis revealed that thymohydroquinone is BBB and central nervous system (CNS) permeant with high acute toxicity and could be a candidate drug for the treatment of these neurological conditions.

The blood–brain barrier (BBB) is a complex neurological barrier whose disruption is associated with the development and exacerbation of different neurodegenerative and neuropsychiatric diseases. There are several drug candidates available that provide symptomatic treatment but have low BBB and central nervous system (CNS) permeability. Thymohydroquinone, a renowned medicinal compound has demonstrated a promising role in inhibiting BBB-disrupting proteins by forming hydrogen bonds with the active subunits with great stability and efficiency, thus, outcompeting its natural substrate. Through pharmacokinetic investigation, it was proven that thymohydroquinone has high BBB and CNS permeability with appropriate acute toxicity and adverse effects profiles.

In silico toxicity evaluation of Salubrinal and its analogues

This paper reports on a comprehensive in silico toxicity assessment of Salubrinal and its analogues containing a cinnamic acid residue or quinoline ring using the online servers admetSAR, ADMETlab, ProTox, ADVERPred, Pred-hERG and Vienna LiverTox. Apart from rare exceptions, in all 55 studied structures, mild or practical absence of acute toxicity was predicted for rats (III or IV toxicity class). Cardiotoxic, hepatotoxic and immunotoxic effects were predicted for Salubrinal and its analogues. We constructed models of the main predicted anti-targets hERG, BSEP, MRP3, MRP4 and AhR using the principle of homologous modeling. Molecular docking studies were carried out with the obtained models. We carried out molecular docking for all targets using AutoDock Vina, implemented in the PyRx 0.8 software package. According to the results of molecular docking, the compounds analyzed are potential moderate or weak hERG blockers. Induction of cholestasis and, as a consequence, liver damage by these drugs, directly related to inhibition of BSEP, MRP3 and MRP4, most likely will not be observed. Interaction with AhR for the studied compounds is impossible for steric reasons and, as a consequence, toxic effects on the immune and other organ systems associated with the activation of the AhR signaling pathway are excluded.

Multiple neuroprotective features of Scutellaria pinnatifida-derived small molecule

Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorders with no precise etiology. Multiple lines of evidence support that environmental factors, either neurotoxins or neuroinflammation, can induce Parkinsonism. In this study, we purified an active compound, neobaicalein (Skullcapflavone II), from the roots of Scutellaria pinnatifida (S. pinnatifida). Neobaicalein not only had protective impacts on rotenone-induced neurotoxicity but in glial cultures, it dampened the inflammatory response when stimulated with lipopolysaccharide (LPS). Neobaicalein had high antioxidant activity without any obvious toxicity. In addition, it could raise the cell viability, decrease early apoptosis, reduce the generation of reactive oxygen species (ROS), and keep the neurite's length normal in the treated SH-SY5Y cells. Pathway enrichment analysis (PEA) and target prediction provided insights into the PD related genes, protein-protein interaction (PPI) network, and the key proteins enriched in the signaling pathways. Furthermore, docking simulation (DS) on the proteins of the PD-PPI network revealed that neobaicalein might interact with the key proteins involved in PD pathology, including MAPK14, MAPK8, and CASP3. It also blocks the destructive processes, such as cell death, inflammation, and oxidative stress pathways. Our results demonstrate that neobaicalein alleviates pathological effects of factors related to PD, and may provide new insight into PD therapy.

A multiparametric organ toxicity predictor for drug discovery

The assessment of major organ toxicities through in silico predictive models plays a crucial role in drug discovery. Computational tools can predict chemical toxicities using the knowledge gained from experimental studies which drastically reduces the attrition rate of compounds during drug discovery and developmental stages. The purpose of in silico predictions for drug leads and anticipating toxicological endpoints of absorption, distribution, metabolism, excretion and toxicity, clinical adverse impacts and metabolism of pharmaceutically active substances has gained widespread acceptance in academia and pharmaceutical industries. With unrestricted accessibility to powerful biomarkers, researchers have an opportunity to contemplate the most accurate predictive scores to evaluate drug's adverse impact on various organs.A multiparametric model involving physico-chemical properties, quantitative structure-activity relationship predictions and docking score was found to be a more reliable predictor for estimating chemical toxicities with potential to reflect atomic-level insights. These in silico models provide informed decisions to carry out in vitro and in vivo studies and subsequently confirms the molecules clues deciphering the cytotoxicity, pharmacokinetics, and pharmacodynamics and organ toxicity properties of compounds. Even though the drugs withdrawn by USFDA at later phases of drug discovery which should have passed all the state-of-the-art experimental approaches and currently acceptable toxicity filters, there is a dire need to interconnect all these molecular key properties to enhance our knowledge and guide in the identification of leads to drug optimization phases. Current computational tools can predict ADMET and organ toxicities based on pharmacophore fingerprint, toxicophores and advanced machine-learning techniques.

Network pharmacology-based assessment to elucidate the molecular mechanism of anti-diabetic action of Tinospora cordifolia

Background

Tinospora cordifolia is used traditionally for the treatment of diabetes and is used in various formulations. Scientific evidence is also available for its anti-diabetic potency under various animal models. However, the probable molecular mechanism of Tinospora cordifolia in the treatment of diabetes has not been illuminated yet. Hence, the present study dealt to elucidate the probable molecular mechanism of anti-diabetic effect of Tinospora cordifolia using network pharmacology approach.

Methods

The structural information of bioactive phytoconstituents was retrieved from different open source databases. Compounds were then predicted for their hits with the probable targets involved in the diabetes mellitus. Phytoconstituents were also predicted for their druglikeness score, probable side effects, and ADMET profile. The modulated protein pathways were identified by using the Kyoto Encyclopedia of Genes and Genomes pathway analysis. The interaction between the compounds, proteins, and pathways was interpreted based on the edge count. The docking study was performed using Autodock4.0.

Results

Nine phytoconstituents from Tinospora cordifolia were identified to modulate the pathogenic protein molecules involved in diabetes mellitus. Among them, tembetarine scored highest druglikeness hit and had the maximum interaction with proteins involved in diabetes. Further, neuroactive ligand-receptor interaction was predicted as majorly modulated pathway.

Conclusion

The current study identified an important antidiabetic constituent, tembetarine which modulated the majority of diabetic proteins majorly modulating neuroactive ligand-receptor interaction.

Assessment of the cardiovascular adverse effects of drug-drug interactions through a combined analysis of spontaneous reports and predicted drug-target interactions

Adverse drug effects (ADEs) are one of the leading causes of death in developed countries and are the main reason for drug recalls from the market, whereas the ADEs that are associated with action on the cardiovascular system are the most dangerous and widespread. The treatment of human diseases often requires the intake of several drugs, which can lead to undesirable drug-drug interactions (DDIs), thus causing an increase in the frequency and severity of ADEs. An evaluation of DDI-induced ADEs is a nontrivial task and requires numerous experimental and clinical studies. Therefore, we developed a computational approach to assess the cardiovascular ADEs of DDIs. This approach is based on the combined analysis of spontaneous reports (SRs) and predicted drug-target interactions to estimate the five cardiovascular ADEs that are induced by DDIs, namely, myocardial infarction, ischemic stroke, ventricular tachycardia, cardiac failure, and arterial hypertension. We applied a method based on least absolute shrinkage and selection operator (LASSO) logistic regression to SRs for the identification of interacting pairs of drugs causing corresponding ADEs, as well as noninteracting pairs of drugs. As a result, five datasets containing, on average, 3100 potentially ADE-causing and non-ADE-causing drug pairs were created. The obtained data, along with information on the interaction of drugs with 1553 human targets predicted by PASS Targets software, were used to create five classification models using the Random Forest method. The average area under the ROC curve of the obtained models, sensitivity, specificity and balanced accuracy were 0.837, 0.764, 0.754 and 0.759, respectively. The predicted drug targets were also used to hypothesize the potential mechanisms of DDI-induced ventricular tachycardia for the top-scoring drug pairs. The created five classification models can be used for the identification of drug combinations that are potentially the most or least dangerous for the cardiovascular system.

[Xenobiotic toxicity prediction combined with xenobiotic metabolism prediction in the human body]

The majority of xenobiotics undergo a number of chemical reactions known as biotransformation in human body. The biological activity, toxicity, and other properties of the metabolites may significantly differ from those of the parent compound. Not only xenobiotic itself and its final metabolites produced in large quantities, but the intermediate and final metabolites that are formed in trace quantities, can cause undesirable effects. We have developed a freely available web resource MetaTox (http://www.way2drug.com/mg/) for integral assessment of xenobiotics toxicity taking into account their metabolism in the humans. The generation of the metabolite structures is based on the reaction fragments. The estimates of the probability of the reaction of a certain class and the probability of site of biotransformation are used at the generation of the xenobiotic metabolism pathways. The web resource MetaTox allows researchers to assess the metabolism of compounds in the humans and to obtain assessment of their acute, chronic toxicity, and adverse effects.

Improving inverse docking target identification with Z-score selection

The utilization of inverse docking methods for target identification has been driven by an increasing demand for efficient tools for detecting potential drug side-effects. Despite impressive achievements in the field of inverse docking, identifying true positives from a pool of potential targets still remains challenging. Notably, most of the developed techniques have low accuracies, limit the pool of possible targets that can be investigated or are not easy to use for non-experts due to a lack of available scripts or webserver. Guided by our finding that the absolute docking score was a poor indication of a ligand's protein target, we developed a novel "combined Z-score" method that used a weighted fraction of ligand and receptor-based Z-scores to identify the most likely binding target of a ligand. With our combined Z-score method, an additional 14%, 3.6%, and 6.3% of all ligand-protein pairs of the Astex, DUD, and DUD-E databases, respectively, were correctly predicted compared to a docking score-based selection. The combined Z-score had the highest area under the curve in a ROC curve analysis of all three datasets and the enrichment factor for the top 1% predictions using the combined Z-score analysis was the highest for the Astex and DUD-E datasets. Additionally, we developed a user-friendly python script (compatible with both Python2 and Python3) that enables users to employ the combined Z-score analysis for target identification using a user-defined list of ligands and targets. We are providing this python script and a user tutorial as part of the supplemental information.

Computer-aided prediction of biological activity spectra for chemical compounds: opportunities and limitation

An essential characteristic of chemical compounds is their biological activity since its presence can become the basis for the use of the substance for therapeutic purposes, or, on the contrary, limit the possibilities of its practical application due to the manifestation of side action and toxic effects. Computer assessment of the biological activity spectra makes it possible to determine the most promising directions for the study of the pharmacological action of particular substances, and to filter out potentially dangerous molecules at the early stages of research. For more than 25 years, we have been developing and improving the computer program PASS (Prediction of Activity Spectra for Substances), designed to predict the biological activity spectrum of substance based on the structural formula of its molecules. The prediction is carried out by the analysis of structure-activity relationships for the training set, which currently contains information on structures and known biological activities for more than one million molecules. The structure of the organic compound is represented in PASS using Multilevel Neighborhoods of Atoms descriptors; the activity prediction for new compounds is performed by the naive Bayes classifier and the structure-activity relationships determined by the analysis of the training set. We have created and improved both local versions of the PASS program and freely available web resources based on PASS (http://www.way2drug.com). They predict several thousand biological activities (pharmacological effects, molecular mechanisms of action, specific toxicity and adverse effects, interaction with the unwanted targets, metabolism and action on molecular transport), cytotoxicity for tumor and non-tumor cell lines, carcinogenicity, induced changes of gene expression profiles, metabolic sites of the major enzymes of the first and second phases of xenobiotics biotransformation, and belonging to substrates and/or metabolites of metabolic enzymes. The web resource Way2Drug is used by over 18,000 researchers from more than 90 countries around the world, which allowed them to obtain over 600,000 predictions and publish about 500 papers describing the obtained results. The analysis of the published works shows that in some cases the interpretation of the prediction results presented by the authors of these publications requires an adjustment. In this work, we provide the theoretical basis and consider, on particular examples, the opportunities and limitations of computer-aided prediction of biological activity spectra.