Evaluation of antidiabetic activity of dietary phenolic compound chlorogenic acid in streptozotocin induced diabetic rats: molecular docking, molecular dynamics, in silico toxicity, in vitro and in vivo studies

Four isobutyric acids (two nitro and two acetamido derivatives) were prepared in two steps and characterized using spectral analysis. The mRNA concentrations of PPARγ and GLUT-4 (two proteins documented as key diabetes targets) were increased by 3T3-L1 adipocytes treated with compounds 1–4, but an absence of in vitro expression of PPARα was observed. Docking and molecular dynamics studies revealed the plausible interaction between the synthesized compounds and PPARγ. In vivo studies established that compounds 1–4 have antihyperglycemic modes of action associated with insulin sensitization. Nitrocompound 2 was the most promising of the series, being orally active, and one of multiple modes of action could be selective PPARγ modulation due to its extra anchoring with Gln-286. In conclusion, we demonstrated that nitrocompound 2 showed strong in vitro and in vivo effects and can be considered as an experimental antidiabetic candidate.

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In vitro and in vivo antidiabetic activity, isolation of flavonoids, and in silico molecular docking of stem extract of Merremia tridentata (L.)

Biomedicine & Pharmacotherapy ◽

10.1016/j.biopha.2021.112611 ◽

2022 ◽

Vol 146 ◽

pp. 112611

Author(s):

Lenh Vo Van ◽

Em Canh Pham ◽

Cuong Viet Nguyen ◽

Ngoc Thoi Nguyen Duong ◽

Tuong Vi Le Thi ◽

...

Keyword(s):

Molecular Docking ◽

In Silico ◽

Antidiabetic Activity ◽

Stem Extract ◽

In Silico Molecular Docking

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An immunoinformatics study: designing multivalent T-cell epitope vaccine against canine circovirus

Journal of Genetic Engineering and Biotechnology ◽

10.1186/s43141-021-00220-4 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Pankaj Jain ◽

Amit Joshi ◽

Nahid Akhtar ◽

Sunil Krishnan ◽

Vikas Kaushik

Keyword(s):

Molecular Dynamics ◽

Amino Acids ◽

Molecular Docking ◽

In Silico ◽

Cell Epitope ◽

Cost Effective ◽

Dynamics Simulation ◽

Cloning And Expression

Abstract Background Canine circovirus is a deadly pathogen of dogs and causes vasculitis and hemorrhagic enteritis. It causes lethal gastroenteritis in pigs, fox, and dogs. Canine circovirus genome contains two main (and opposite) transcription units which encode two open reading frames (ORFs), a replicase-associated protein (Rep) and the capsid (Cap) protein. The replicase protein and capsid protein consist of 303 amino acids and 270 amino acids respectively. Several immuno-informatics methods such as epitope screening, molecular docking, and molecular-dynamics simulations were used to craft peptide-based vaccine construct against canine circovirus. Results The vaccine construct was designed by joining the selected epitopes with adjuvants by suitable linker. The cloning and expression of the vaccine construct was also performed using in silico methods. Screening of epitopes was conducted by NetMHC server that uses ANN (Artificial neural networking) algorithm. These methods are fast and cost-effective for screening epitopes that can interact with dog leukocyte antigens (DLA) and initiate an immune response. Overall, 5 epitopes, YQHLPPFRF, YIRAKWINW, ALYRRLTLI, HLQGFVNLK, and GTMNFVARR, were selected and used to design a vaccine construct. The molecular docking and molecular dynamics simulation studies show that these epitopes can bind with DLA molecules with stability. The codon adaptation and in silico cloning studies show that the vaccine can be expressed by Escherichia coli K12 strain. Conclusion The results suggest that the vaccine construct can be useful in preventing the dogs from canine circovirus infections. However, the results need further validation by performing other in vitro and in vivo experiments.

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Novel Phytochemical Constituents and their Potential to Manage Diabetes

Current Pharmaceutical Design ◽

10.2174/1381612826666201222154159 ◽

2020 ◽

Vol 26 ◽

Author(s):

Shaik Ibrahim Khalivulla ◽

Arifullah Mohammed ◽

Kokkanti Mallikarjuna

Keyword(s):

Natural Products ◽

Large Population ◽

World Health ◽

In Vivo Studies ◽

Antidiabetic Activity ◽

Therapeutic Drug ◽

Pharmacological Activities ◽

Chemical Structures

Background: Diabetes is a chronic disease affecting a large population worldwide and stands as one of the major global health challenges to be tackled. According to World Health Organization, about 400 million are having diabetes worldwide and it is the seventh leading cause of deaths in 2016. Plant based natural products had been in use from ancient time as ethnomedicine for the treatment of several diseases including diabetes. As a result of that, there are several reports on plant based natural products displaying antidiabetic activity. In the current review, such antidiabetic potential compounds reported from all plant sources along with their chemical structures are collected, presented and discussed. This kind of reports are essential to pool the available information to one source followed by statistical analysis and screening to check the efficacy of all known compounds in a comparative sense. This kind of analysis can give rise to few numbers of potential compounds from hundreds, whom can further be screened through in vitro and in vivo studies, and human trails leading to the drug development. Methods: Phytochemicals along with their potential antidiabetic property were classified according to their basic chemical skeleton. The chemical structures of all the compounds with antidiabetic activities were elucidated in the present review. In addition to this, the distribution and their other remarkable pharmacological activities of each species is also included. Results: The scrutiny of literature led to identification of 44 plants with antidiabetic compounds (70) and other pharmacological activities. For the sake of information, the distribution of each species in the world is given. Many plant derivatives may exert antidiabetic properties by improving or mimicking the insulin production or action. Different classes of compounds including sulfur compounds (1-4), alkaloids (5-11), phenolic compounds (12-17), tannins (18-23), phenylpropanoids (24-27), xanthanoids (28-31), amino acid (32), stilbenoid (33), benzofuran (34), coumarin (35), flavonoids (36-49) and terpenoids (50-70) were found to be active potential compounds for antidiabetic activity. Of the 70 listed compounds, majorly 17 compounds are from triterpenoids, 13 flavonoids and 7 are from alkaloids. Among all the 44 plant species, maximum number (7) of compounds are reported from Lagerstroemia speciosa followed by Momordica charantia (6) and S. oblonga with 5 compounds. Conclusion: This is the first paper to summarize the established chemical structures of phytochemicals that have been successfully screened for antidiabetic potential and their mechanisms of inhibition. The reported compounds could be considered as potential lead molecules for the treatment of type-2 diabetes. Further, molecular and clinical trials are required to select and establish the therapeutic drug candidates.

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Recent In Vitro and In Silico Advances in the Understanding of Intranasal Drug Delivery

Current Pharmaceutical Design ◽

10.2174/1381612826666201112143230 ◽

2020 ◽

Vol 26 ◽

Author(s):

John Chen ◽

Andrew Martin ◽

Warren H. Finlay

Keyword(s):

Drug Delivery ◽

In Silico ◽

Local Drug Delivery ◽

In Vivo Studies ◽

Intranasal Drug Delivery ◽

Nasal Sprays ◽

In Silico Studies ◽

Drug Delivery Devices

Background: Many drugs are delivered intranasally for local or systemic effect, typically in the form of droplets or aerosols. Because of the high cost of in vivo studies, drug developers and researchers often turn to in vitro or in silico testing when first evaluating the behavior and properties of intranasal drug delivery devices and formulations. Recent advances in manufacturing and computer technologies have allowed for increasingly realistic and sophisticated in vitro and in silico reconstructions of the human nasal airways. Objective: To perform a summary of advances in understanding of intranasal drug delivery based on recent in vitro and in silico studies. Conclusion: The turbinates are a common target for local drug delivery applications, and while nasal sprays are able to reach this region, there is currently no broad consensus across the in vitro and in silico literature concerning optimal parameters for device design, formulation properties and patient technique which would maximize turbinate deposition. Nebulizers are able to more easily target the turbinates, but come with the disadvantage of significant lung deposition. Targeting of the olfactory region of the nasal cavity has been explored for potential treatment of central nervous system conditions. Conventional intranasal devices, such as nasal sprays and nebulizers, deliver very little dose to the olfactory region. Recent progress in our understanding of intranasal delivery will be useful in the development of the next generation of intranasal drug delivery devices.

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In-silico Studies of Isolated Phytoalkaloid Against Lipoxygenase: Study Based on Possible Correlation

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207321666180220125406 ◽

2018 ◽

Vol 21 (3) ◽

pp. 215-221

Author(s):

Haroon Khan ◽

Muhammad Zafar ◽

Helena Den-Haan ◽

Horacio Perez-Sanchez ◽

Mohammad Amjad Kamal

Keyword(s):

In Silico ◽

Docking Studies ◽

In Vivo Studies ◽

In Vitro Assays ◽

Chronic Obstructive ◽

Lipoxygenase Inhibitors ◽

Lipoxygenase Inhibition ◽

In Silico Studies

Aim and Objective: Lipoxygenase (LOX) enzymes play an important role in the pathophysiology of several inflammatory and allergic diseases including bronchial asthma, allergic rhinitis, atopic dermatitis, allergic conjunctivitis, rheumatoid arthritis and chronic obstructive pulmonary disease. Inhibitors of the LOX are believed to be an ideal approach in the treatment of diseases caused by its over-expression. In this regard, several synthetic and natural agents are under investigation worldwide. Alkaloids are the most thoroughly investigated class of natural compounds with outstanding past in clinically useful drugs. In this article, we have discussed various alkaloids of plant origin that have already shown lipoxygenase inhibition in-vitro with possible correlation in in silico studies. Materials and Methods: Molecular docking studies were performed using MOE (Molecular Operating Environment) software. Among the ten reported LOX alkaloids inhibitors, derived from plant, compounds 4, 2, 3 and 1 showed excellent docking scores and receptor sensitivity. Result and Conclusion: These compounds already exhibited in vitro lipoxygenase inhibition and the MOE results strongly correlated with the experimental results. On the basis of these in vitro assays and computer aided results, we suggest that these compounds need further detail in vivo studies and clinical trial for the discovery of new more effective and safe lipoxygenase inhibitors. In conclusion, these results might be useful in the design of new and potential lipoxygenase (LOX) inhibitors.

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Promising Anti-stroke Signature of Voglibose: Investigation through In- Silico Molecular Docking and Virtual Screening in In-Vivo Animal Studies

Current Gene Therapy ◽

10.2174/1566523220999200726225457 ◽

2020 ◽

Vol 20 (3) ◽

pp. 223-235

Author(s):

Pooja Shah ◽

Vishal Chavda ◽

Snehal Patel ◽

Shraddha Bhadada ◽

Ghulam Md. Ashraf

Keyword(s):

Molecular Docking ◽

Virtual Screening ◽

In Silico ◽

Reductase Activity ◽

Infarct Volume ◽

Docking Studies ◽

Serum Glucose ◽

In Vivo Studies ◽

In Silico Molecular Docking

Background: Postprandial hyperglycemia considered to be a major risk factor for cerebrovascular complications. Objective: The current study was designed to elucidate the beneficial role of voglibose via in-silico in vitro to in-vivo studies in improving the postprandial glycaemic state by protection against strokeprone type 2 diabetes. Material and Methods: In-Silico molecular docking and virtual screening were carried out with the help of iGEMDOCK+ Pymol+docking software and Protein Drug Bank database (PDB). Based on the results of docking studies, in-vivo investigation was carried out for possible neuroprotective action. T2DM was induced by a single injection of streptozotocin (90mg/kg, i.v.) to neonates. Six weeks after induction, voglibose was administered at the dose of 10mg/kg p.o. for two weeks. After eight weeks, diabetic rats were subjected to middle cerebral artery occlusion, and after 72 hours of surgery, neurological deficits were determined. The blood was collected for the determination of serum glucose, CK-MB, LDH and lipid levels. Brains were excised for determination of brain infarct volume, brain hemisphere weight difference, Na+-K+ ATPase activity, ROS parameters, NO levels, and aldose reductase activity. Results: In-silico docking studies showed good docking binding score for stroke associated proteins, which possibly hypotheses neuroprotective action of voglibose in stroke. In the present in-vivo study, pre-treatment with voglibose showed a significant decrease (p<0.05) in serum glucose and lipid levels. Voglibose has shown significant (p<0.05) reduction in neurological score, brain infarct volume, the difference in brain hemisphere weight. On biochemical evaluation, treatment with voglibose produced significant (p<0.05) decrease in CK-MB, LDH, and NO levels in blood and reduction in Na+-K+ ATPase, oxidative stress, and aldose reductase activity in brain homogenate. Conclusion: In-silico molecular docking and virtual screening studies and in-vivo studies in MCAo induced stroke, animal model outcomes support the strong anti-stroke signature for possible neuroprotective therapeutics.

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Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning

Molecules ◽

10.3390/molecules26092505 ◽

2021 ◽

Vol 26 (9) ◽

pp. 2505

Author(s):

Raheem Remtulla ◽

Sanjoy Kumar Das ◽

Leonard A. Levin

Keyword(s):

Machine Learning ◽

Neural Networks ◽

In Silico ◽

Disulfide Bonds ◽

Oral Absorption ◽

In Vivo Studies ◽

Drug Candidates ◽

In Silico Methods

Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated in the downstream effects of axonal injury. A difficulty in using standard in silico methods for studying these drugs is that most computational tools are not designed for borane-containing compounds. Using in silico and machine learning methodologies, the absorption-distribution properties of these unique compounds were assessed. Features examined with in silico methods included cellular permeability, octanol-water partition coefficient, blood-brain barrier permeability, oral absorption and serum protein binding. The resultant neural networks demonstrated an appropriate level of accuracy and were comparable to existing in silico methodologies. Specifically, they were able to reliably predict pharmacokinetic features of known boron-containing compounds. These methods predicted that phosphine-borane compounds and their metabolites meet the necessary pharmacokinetic features for orally active drug candidates. This study showed that the combination of standard in silico predictive and machine learning models with neural networks is effective in predicting pharmacokinetic features of novel boron-containing compounds as neuroprotective drugs.

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