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Diabetes mellitus is a multi-systematic chronic metabolic disorder and life-threatening disease resulting from impaired glucose homeostasis. The inhibition of glucosidase, particularly α-glucosidase, could serve as an effective methodology in treating diabetes. Attributed to the catalytic function of glucosidase, the present research focuses on the synthesis of sulfonamide-based acyl pyrazoles (5a-k) followed by their in vitro and in silico screening against α-glucosidase. The envisaged structures of prepared compounds were confirmed through NMR and FTIR spectroscopy and mass spectrometry. All compounds were found to be more potent against α-glucosidase than the standard drug, acarbose (IC50 = 35.1 ± 0.14 µM), with IC50 values ranging from 1.13 to 28.27 µM. However, compound 5a displayed the highest anti-diabetic activity (IC50 = 1.13 ± 0.06 µM). Furthermore, in silico studies revealed the intermolecular interactions of most potent compounds (5a and 5b), with active site residues reflecting the importance of pyrazole and sulfonamide moieties. This interaction pattern clearly manifests various structure-activity relationships, while the docking results correspond to the IC50 values of tested compounds. Hence, recent investigation reveals the medicinal significance of sulfonamide-clubbed pyrazole derivatives as prospective therapeutic candidates for treating type 2 diabetes mellitus (T2DM).
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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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Yellow fever is a flavivirus having plus-sensed RNA which encodes a single polyprotein. Host proteases cut this polyprotein into seven nonstructural proteins including a vital NS3 protein. The present study aims to identify the most effective inhibitor against the helicase (NS3) using different advanced ligand and structure-based computational studies. A set of 300 ligands was selected against helicase by chemical structural similarity model, which are similar to S-adenosyl-l-cysteine using infiniSee. This tool screens billions of compounds through a similarity search from in-built chemical spaces (CHEMriya, Galaxi, KnowledgeSpace and REALSpace). The pharmacophore was designed from ligands in the library that showed same features. According to the sequence of ligands, six compounds (29, 87, 99, 116, 148, and 208) were taken for pharmacophore designing against helicase protein. Subsequently, compounds from the library which showed the best pharmacophore shared-features were docked using FlexX functionality of SeeSAR and their optibrium properties were analyzed. Afterward, their ADME was improved by replacing the unfavorable fragments, which resulted in the generation of new compounds. The selected best compounds (301, 302, 303 and 304) were docked using SeeSAR and their pharmacokinetics and toxicological properties were evaluated using SwissADME. The optimal inhibitor for yellow fever helicase was 2-amino-N-(4-(dimethylamino)thiazol-2-yl)-4-methyloxazole-5-carboxamide (302), which exhibits promising potential for drug development.Communicated by Ramaswamy H. Sarma.
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COPD is a multifactorial lung disease causing breathing difficulties in individuals and is becoming a major health concern worldwide. The unclear pathogenic mechanism and high mortality rate urge the development of drugs against this disease. In this study, around six COPD biomarkers identified from the preceding research through integrated gene expression analysis were taken as COPD target proteins. A total of 3307 phytocompounds were included in the COPD phytocompound library from 59 therapeutic plant sources. Furthermore, a crucial three-step virtual screening process (Absorption, Distribution, Metabolism, and Excretion, respiratory nontoxicity, less harmful and nontoxic compound category) was implemented to filter the potential drug-like phytocompounds. As a result, 160 phytocompounds were filtered with desired Absorption, Distribution, Metabolism, Excretion and Toxicity properties. The filtered 160 phytocompounds were docked against six COPD target proteins and the best-docked complexes were identified through visual inspection based on six unique parameters in SeeSAR. Furthermore, the best docked complexes were subjected to molecular dynamics simulation studies to assess the stability and conformational changes of the complexes. The presence of few amino acid residues within the crucial active, allosteric and catalytic sites of the six target proteins were revealed from the binding interaction types and major residual fluctuations from molecular docking and dynamic simulation studies respectively. This is indicative of the potential inhibitory activity of phytocompounds against the COPD biomarkers. Here we report the identified phytocompounds as a promising lead molecule for the six COPD biomarkers through in silico analysis opening new avenues in COPD pathogenesis and treatments.Communicated by Ramaswamy H. Sarma.
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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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The liver function test is an imperative element in chemotherapy management due to the idiosyncratic reaction of chemotherapy drugs. This study primly aimed to replace the toxic fragments of known protein tyrosine kinases inhibitors (PTKi) to develop safe and effective chemotherapy. All the current PTKi's were docked with the tyrosine kinases and metabolic enzymes to study the affinities on the target. It resulted from most of the PTKi's found higher affinity and efficacy with metabolic enzymes lead the hepatic cells damage. To overcome this limitation of PTKi's, a bioisosteric replacement strategy was achieved and conceptual analogs were designed. Specifically, the Generated pose of the Axitinib molecule showed that axitinib fragments C = C-, -C = O and NH2 produced clashes with active site residues of tyrosine kinases protein and good affinity with metabolic enzyme primes to the liver toxicity. The above said fragments were replaced with various bioisosteric groups and efficacy was measured. The resulting molecule shows improved affinity with tyrosine kinases enzyme and less interactions with metabolic enzyme were imminent molecule for the treatment of malignant cells with outside effects.Communicated by Ramaswamy H. Sarma.
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Antineoplásicos , Axitinib , Antineoplásicos/farmacología , Antineoplásicos/uso terapéutico , Proteínas Tirosina Quinasas , TirosinaRESUMEN
The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4.2 and manual edition of available structures for binding poses generation using SeeSAR, (2) the use of HYDE scoring for pose selection, and (3) a hierarchical ranking using HYDE and MM/GBSA. In this report, we detail our pose generation and ligands ranking protocols and provide guidelines to be used in a prospective computer aided drug design program.