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Multi-Target Inhibitors are the upcoming frontrunners of the antibiotic world as they provide significant advantage over drug resistance development. Antibacterial drug discovery research, requires more robust and innovative approaches such as multi-target inhibiting drugs, which over comes the innate hurdles in the field of antibiotics. In this current study, a curated set of 5,112 phytochemical molecules were virtually screened for its multi-target inhibition potential against 7 antibacterial protein drug-targets. Behenic Acid was identified to be the most significant phytochemical molecule with potential to inhibit Catalase Peroxidase (KatG), Adenylosuccinate Synthetase (ADSS) and Pyridoxine 5'-Phosphate Synthase (PdxJ), based on SeeSAR and AutoDock Vina results. Further, the inhibition potential of Behenic Acid was validated using 500 ns Molecular Dynamics (MD) Simulation based on Desmond analysis. Behenic Acid was further investigated in-vitro using agar-well-diffusion and Minimal Inhibitory Concentration (MIC) assay, where it demonstrated 20 ± 1mm zone-of-inhibition and 50 µg/ml MIC value against both Vibrio parahaemolyticus and Aeromonas hydrophila. Zebrafish based investigations was carried to confirm the in-vivo antibacterial efficacy of Behenic Acid. It was observed that, there is a progressive dose-dependent recovery from the bacterial infection, with highest recovery and survival observed in fishes fed with 100 µg/day of Behenic Acid. Results of the in-vitro and in-vivo assays strongly support the in-silico prediction of the antibacterial activity of Behenic Acid. Based on the results presented in this study, it is concluded that, Behenic Acid is a strong multi-target antibacterial phytochemical, that exerts antagonism against aquaculture bacterial pathogens such as V. parahaemolytics and A. hydrophila.Communicated by Ramaswamy H. Sarma.
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The study aims to identify and validate a potential α-Amylase inhibitor from the leaf extract of the Parthenium hysterophorus. Molecular docking and dynamics analyses were performed to test the anti-diabetic efficacy of the compound by focusing on α-Amylase inhibition. The molecular docking study using AutoDock Vina (PyRx) and SeeSAR tools identified ß-Sitosterol as an effective α-Amylase inhibitory compound. Among the analysed fifteen phytochemicals, ß-Sitosterol demonstrated the most appreciable binding energy (-9.0 Kcal/mol) and is comparatively higher than the binding energy of the standard α-Amylase inhibitor, the Acarbose (-7.6 Kcal/mol). The significance of the interaction between ß-Sitosterol and α-Amylase was further investigated using Molecular Dynamics Simulation (MDS) for 100 ns via GROMACS. The data reveals that the compound could exhibit the highest stability with α-Amylase regarding RMSD, RMSF, SASA and Potential Energy analysis. The key residue of α-Amylase (Asp -197) shows a significantly low fluctuation of 0.7 Å while interacting with ß-Sitosterol. The data obtained from MDS results strongly suggested the potential inhibitory impact of ß-Sitosterol on α-Amylase. In addition, the proposed phytochemical was purified from the leaf extracts of P.hysterophorus using the silica gel column chromatography and identified by GC-MS analysis. The purified ß-Sitosterol demonstrated a significant 42.30% in-vitro α-Amylase enzyme inhibition property under 400 µg/ml concentration and thus supported the in-silico predictions. Further in-vivo investigations are necessary to analyse the efficiency of ß-Sitosterol on α-Amylase inhibition to help the anti-diabetic potential of the phytocompound.Communicated by Ramaswamy H. Sarma.
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Parthenium hysterophorus , alfa-Amilases , Simulação de Acoplamento Molecular , Extratos Vegetais/farmacologia , Extratos Vegetais/químicaRESUMO
Multi-target inhibitors are currently trending in the pharmaceutical research, as they possess increased efficacy and reduced toxicity. In this study multi-target inhibitors for breast cancer are explored from a curated list of natural products, i.e. 4,670 phytochemicals belonging to 360 medicinal plants. In-silico screening of phytochemicals using SeeSAR and AutoDock Vina resulted in identification of Stearyl Palmitate as a potential drug molecule that inhibits three drug targets, i.e. HER-2, MEK-1 and PARP-1 proteins. Molecular Dynamics Simulation for 100 ns each for these three protein-ligand complexes using Desmond, Maestro platform also confirmed the prediction of multi-target inhibition by Stearyl Palmitate. Further in-vitro MTT assay demonstrated that Stearyl Palmitate has a significant IC50 value of 40 µM against MCF-7 cells and >1000 µM against L929 cells. This confirmed that Stearyl Palmitate is having selective cytotoxicity towards breast cancer cells in comparison to non-cancerous cells. Fluorescence staining and flow cytometry analysis confirmed that, Stearyl Palmitate is inducing apoptosis in MCF-7 cells at IC50 concentration. Finally, in-vivo efficacy and toxicity studies were performed using zebrafishes (Danio rerio). It was observed that the fishes treated with IC50 concentration of Stearyl Palmitate demonstrated 2x folds reduction in tumour size, while double dose resulted in 4x folds reduction in tumour size. Stearyl Palmitate did not demonstrate any toxicity or side effects in the zebrafishes. It is concluded that, Stearyl Palmitate, a phytochemical reported to be present in Althea officinalis is a potential anti-breast cancer agent, with ability to inhibit multiple targets such as HER-2, MEK-1 and PARP-2 proteins.Communicated by Ramaswamy H. Sarma.
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Background: There has been a significant increase in the incidence of recurrent, resistant, and extensive dermatophyte infections worldwide recently. This menace has spurred the need for more well-designed randomized controlled trials to optimize the treatment of dermatophyte skin infections. One of the limitations in designing such studies is the limited availability of standard and validated score, to measure the severity of dermatophyte infections. Aims: To create a severity score for the evaluation of dermatophyte infections. Materials and Methods: A Delphi consensus model was used to frame a severity scoring tool for superficial dermatophyte skin infections. Fourteen experts participated in the first round and twelve experts participated in the second round. Results: Based on the expert consensus, a final scoring system proposed was: Final Severity Score (FSS) = Sum total of Body Surface Area (BSA) in hand units for each patch multiplied by the sum of the scores for pruritis (P), lichenification (L), and actively raised borders (A) for each patch (FSS = BSA in hand units × (P + E + L + A) of patch 1 + BSA in hand units × (P + E + A) of patch 2 etc.). For measuring hand units more accurately fractional values of 0.25 can be used (0.25 corresponding to an approximate 1/4th of a hand unit). A score of +1 will be added in case of the following - 1) Close contact/family member affected, 2) History of at least one recurrence in the previous 6 months after a course of oral antifungals, 3) History of immunosuppression (on immunosuppressive medication or having underlying immunosuppressive disease). The scores will be valid only if the patient has not used any treatment topical or systemic, for at least 2 weeks before enrolment. Conclusion: The proposed Dermatophytosis Area and Severity Index (DeASI) score will help the physicians and researchers standardize the treatment protocol for dermatophytosis, henceforth, assessing the response to therapy. This will also help to standardize the parameters of effectiveness while designing any clinical trial.
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INTRODUCTION: Hydroxyapatite based drug carriers offer a customized alternative to the delivery of pharmacologic agents in the osseous skeleton. They have an added advantage of being biocompatible and osteoconductive. This in vitro study aims to quantify the drug eluting properties of HA granules by spectrophotometry. MATERIALS AND METHODS: HA and HASi beads were loaded with gentamicin/ amoxycillin- clavulanate/ vancomycin and grouped into 5. Drug elution was evaluated by means of UV spectrophotometry. RESULTS: Drug eluent levels were well above bactericidal levels in all 5 groups. CONCLUSION: HA and HASi are viable options for clinicians for targeted drug delivery.