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

Molecules ◽  
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.

Bioassays and In Silico Methods in the Identification of Human DNA Topoisomerase IIα Inhibitors

2018 ◽  
Vol 25 (28) ◽  
pp. 3286-3318 ◽  
Author(s):  
Kaja Bergant ◽  
Matej Janezic ◽  
Andrej Perdih
Keyword(s):  
In Silico ◽  
In Vivo Studies ◽  
Topoisomerase Iiα ◽  
Dna Topoisomerase ◽  
Human Dna ◽  
Practical Guidelines ◽  
In Silico Methods ◽  
Dna Topoisomerase Iiα

Background: The family of DNA topoisomerases comprises a group of enzymes that catalyse the induction of topological changes to DNA. These enzymes play a role in the cell replication machinery and are, therefore, important targets for anticancer drugs - with human DNA topoisomerase IIα being one of the most prominent. Active compounds targeting this enzyme are classified into two groups with diverse mechanisms of action: DNA poisons act by stabilizing a covalent cleavage complex between DNA and the topoisomerase enzyme, transforming it into a cellular toxin, while the second diverse group of catalytic inhibitors, provides novel inhibition avenues for tackling this enzyme due to frequent occurrence of side effects observed during the DNA poison therapy. Methods: Based on a comprehensive literature search we present an overview of available bioassays and in silico methods in the identification of human DNA topoisomerase IIα inhibitors. Results and Conclusion: A comprehensive outline of the available methods and approaches that explore in detail the in vitro mechanistic and functional aspects of the topoisomerase IIα inhibition of both topo IIα inhibitor groups is presented. The utilized in vitro cell-based assays and in vivo studies to further explore the validated topo IIα inhibitors in subsequent preclinical stages of the drug discovery are discussed. The potential of in silico methods in topoisomerase IIα inhibitor discovery is outlined. A list of practical guidelines was compiled to aid new as well experienced researchers in how to optimally approach the design of targeted inhibitors and validation in the preclinical drug development stages.

Coumarins and Quinolones as Effective Multiple Targeted Agents Versus Covid-19: An in Silico Study

2021 ◽  
Vol 17 ◽  
Author(s):  
Mojgan Nejabat ◽  
Razieh Ghodsi ◽  
Farzin Hadizadeh
Keyword(s):  
Binding Affinity ◽  
In Silico ◽  
Oral Absorption ◽  
Antiviral Agent ◽  
In Vivo Studies ◽  
Reference Drug ◽  
Viral Proteases ◽  
In Silico Study

Background: The Covid-19 virus emerged a few months ago in China and infections rapidly escalated into a pandemic. Objective: To date, there is no selective antiviral agent for the management of pathologies associated with covid-19 and the need for an effective agent against it is essential. Method: In this work two home-made databases from synthetic quinolines and coumarins were virtually docked against viral proteases (3CL and PL), human cell surface proteases (TMPRSS2 and furin) and spike proteins (S1 and S2). Chloroquine, a reference drug without a clear mechanism against coronavirus was also docked on mentioned targets and the binding affinities compared with title compounds. Result: The best compounds of synthetic coumarins and quinolines for each target were determined. All compounds against all targets showed binding affinity between -5.80 to -8.99 kcal/mol in comparison with the FDA-approved drug, Chloroquine, with binding affinity of -5.7 to -7.98 kcal/mol. Two compounds, quinoline-1 and coumarin-24, were found to be effective on three targets – S2, TMPRSS2 and furin – simultaneously, with good predicted affinity between -7.54 to -8.85 kcal/mol. In silico ADME studies also confirmed good oral absorption for them. Furthermore, PASS prediction was calculated and coumarin-24 had higher probable activity (Pa) than probable inactivity (Pi) with acceptable protease inhibitory as well as good antiviral activity against Hepatitis C virus (HCV), Human immunodeficiency virus (HIV) and influenza. Conclusion: Quinoline-1 and Coumarin-24 have the potential to be used against Covid-19. Hence these agents could be useful in combating covid-19 infection after further in vitro and in vivo studies.

scholarly journals Selection of safe artemisinin derivatives using a machine learning-based cardiotoxicity platform and in vitro and in vivo validation

2021 ◽  
Author(s):  
Onat Kadioglu ◽  
Sabine M. Klauck ◽  
Edmond Fleischer ◽  
Letian Shan ◽  
Thomas Efferth
Keyword(s):  
Machine Learning ◽  
In Silico ◽  
Artemisia Annua ◽  
Reproductive Toxicity ◽  
Toxicity Prediction ◽  
Artemisinin Derivatives ◽  
Drug Candidates

AbstractThe majority of drug candidates fails the approval phase due to unwanted toxicities and side effects. Establishment of an effective toxicity prediction platform is of utmost importance, to increase the efficiency of the drug discovery process. For this purpose, we developed a toxicity prediction platform with machine-learning strategies. Cardiotoxicity prediction was performed by establishing a model with five parameters (arrhythmia, cardiac failure, heart block, hypertension, myocardial infarction) and additional toxicity predictions such as hepatotoxicity, reproductive toxicity, mutagenicity, and tumorigenicity are performed by using Data Warrior and Pro-Tox-II software. As a case study, we selected artemisinin derivatives to evaluate the platform and to provide a list of safe artemisinin derivatives. Artemisinin from Artemisia annua was described first as an anti-malarial compound and later its anticancer properties were discovered. Here, random forest feature selection algorithm was used for the establishment of cardiotoxicity models. High AUC scores above 0.830 were achieved for all five cardiotoxicity indications. Using a chemical library of 374 artemisinin derivatives as a case study, 7 compounds (deoxydihydro-artemisinin, 3-hydroxy-deoxy-dihydroartemisinin, 3-desoxy-dihydroartemisinin, dihydroartemisinin-furano acetate-d3, deoxyartemisinin, artemisinin G, artemisinin B) passed the toxicity filtering process for hepatotoxicity, mutagenicity, tumorigenicity, and reproductive toxicity in addition to cardiotoxicity. Experimental validation with the cardiomyocyte cell line AC16 supported the findings from the in silico cardiotoxicity model predictions. Transcriptomic profiling of AC16 cells upon artemisinin B treatment revealed a similar gene expression profile as that of the control compound, dexrazoxane. In vivo experiments with a Zebrafish model further substantiated the in silico and in vitro data, as only slight cardiotoxicity in picomolar range was observed. In conclusion, our machine-learning approach combined with in vitro and in vivo experimentation represents a suitable method to predict cardiotoxicity of drug candidates.

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

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.

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

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.

In silico identification of viper phospholipaseA2 inhibitors: validation by in vitro, in vivo studies

2011 ◽  
Vol 17 (12) ◽  
pp. 3063-3073 ◽  
Author(s):  
Amit Nargotra ◽  
Sujata Sharma ◽  
Mohd Iqbal Alam ◽  
Zabeer Ahmed ◽  
Asha Bhagat ◽  
...  
Keyword(s):  
In Silico ◽  
In Vivo Studies ◽  
In Silico Identification

scholarly journals In Silico Screening of Potential Drug with Antileishmanial Activty and Validation of their Activity by in Vitro and in Vivo Studies

2015 ◽  
Vol 9 (6) ◽  
Author(s):  
Carol V. Mesa ◽  
Gustavo A. Blandón ◽  
Diana L. Muñoz ◽  
Carlos E. Muskus ◽  
Andrés F. Flórez ◽  
...  
Keyword(s):  
In Silico ◽  
In Vivo Studies ◽  
Potential Drug ◽  
In Silico Screening

scholarly journals Anti-Inflammatory Potential of Daturaolone from Datura innoxia Mill.: In Silico, In Vitro and In Vivo Studies

2021 ◽  
Vol 14 (12) ◽  
pp. 1248
Author(s):  
Muhammad Waleed Baig ◽  
Humaira Fatima ◽  
Nosheen Akhtar ◽  
Hidayat Hussain ◽  
Mohammad K. Okla ◽  
...  
Keyword(s):  
In Silico ◽  
Therapeutic Potential ◽  
In Vivo Studies ◽  
Metabolic Reaction ◽  
Datura Innoxia ◽  
In Vivo Models ◽  
Immobility Time ◽  
Anti Inflammatory

Exploration of leads with therapeutic potential in inflammatory disorders is worth pursuing. In line with this, the isolated natural compound daturaolone from Datura innoxia Mill. was evaluated for its anti-inflammatory potential using in silico, in vitro and in vivo models. Daturaolone follows Lipinski’s drug-likeliness rule with a score of 0.33. Absorption, distribution, metabolism, excretion and toxicity prediction show strong plasma protein binding; gastrointestinal absorption (Caco-2 cells permeability = 34.6 nm/s); no blood–brain barrier penetration; CYP1A2, CYP2C19 and CYP3A4 metabolism; a major metabolic reaction, being aliphatic hydroxylation; no hERG inhibition; and non-carcinogenicity. Predicted molecular targets were mainly inflammatory mediators. Molecular docking depicted H-bonding interaction with nuclear factor kappa beta subunit (NF-κB), cyclooxygenase-2, 5-lipoxygenase, phospholipase A2, serotonin transporter, dopamine receptor D1 and 5-hydroxy tryptamine. Its cytotoxicity (IC50) value in normal lymphocytes was >20 µg/mL as compared to cancer cells (Huh7.5; 17.32 ± 1.43 µg/mL). Daturaolone significantly inhibited NF-κB and nitric oxide production with IC50 values of 1.2 ± 0.8 and 4.51 ± 0.92 µg/mL, respectively. It significantly reduced inflammatory paw edema (81.73 ± 3.16%), heat-induced pain (89.47 ± 9.01% antinociception) and stress-induced depression (68 ± 9.22 s immobility time in tail suspension test). This work suggests a possible anti-inflammatory role of daturaolone; however, detailed mechanistic studies are still necessary to corroborate and extrapolate the findings.

scholarly journals Identification of Structurally Similar Phytochemicals to Quercetin with High SIRT1 Binding Affinity and Improving Diabetic Wound Healing by Using In silico Approaches

2021 ◽  
Vol 12 (6) ◽  
pp. 7621-7632
Keyword(s):  
Wound Healing ◽  
In Silico ◽  
Binding Free Energy ◽  
Biological Properties ◽  
In Vivo Studies ◽  
Diabetic Wound ◽  
Binding Modes ◽  
Diabetic Wound Healing

Diabetes Mellitus is the most prevalent metabolic disorder that is increasing at an alarming rate worldwide. The unregulated glucose level leads to various types of health disorders, and one of the major diabetic complications is delayed wound healing. Due to the more side effects of synthetic drugs, there is a need to explore plants and their phytochemicals for medicinal purposes. It was found that Quercetin, a flavonoid, increases the rate of diabetic wound healing by enhancing the expression of SIRT1. This demands more insight towards Quercetin and its similar compounds, as it is hypothesized that similar compounds may have similar biological properties. Thus similarity searching was done to identify the most similar compounds of Quercetin, and then the molecular docking of the screened compounds was performed using AutoDock Vina. The unique ligands were docked into the active site of SIRT1 protein (PDB ID: 4ZZJ). The binding free energy of the interacting ligand with the protein was estimated. Six compounds were identified which possess the maximum structural similarity with Quercetin, and upon docking, it was found that gossypetin and herbacetin have similar binding modes and binding energy as that of Quercetin (-7.5 kcal/mol). Therefore, the hypothesis has been validated by in silico analysis. Our study identified two phytochemicals, Gossypetin, and Herbacetin which can prove beneficial for improving diabetic wound healing but needs to be validated further by in vitro and in vivo studies.

scholarly journals Which cytochrome P450 metabolizes phenazepam? Step by step in silico, in vitro, and in vivo studies

2018 ◽  
Vol 33 (2) ◽  
pp. 65-73 ◽  
Author(s):  
Dmitriy V. Ivashchenko ◽  
Anastasia V. Rudik ◽  
Andrey A. Poloznikov ◽  
Sergey V. Nikulin ◽  
Valeriy V. Smirnov ◽  
...  
Keyword(s):  
Cell Culture ◽  
Cytochrome P450 ◽  
In Silico ◽  
In Vivo Studies ◽  
Cyp3a Activity ◽  
Cell Culture Study ◽  
Study Results ◽  
Three Stages

Abstract Background: Phenazepam (bromdihydrochlorphenylbenzodiazepine) is the original Russian benzodiazepine tranquilizer belonging to 1,4-benzodiazepines. There is still limited knowledge about phenazepam’s metabolic liver pathways and other pharmacokinetic features. Methods: To determine phenazepam’s metabolic pathways, the study was divided into three stages: in silico modeling, in vitro experiment (cell culture study), and in vivo confirmation. In silico modeling was performed on the specialized software PASS and GUSAR to evaluate phenazepam molecule affinity to different cytochromes. The in vitro study was performed using a hepatocytes’ cell culture, cultivated in a microbioreactor to produce cytochrome P450 isoenzymes. The culture medium contained specific cytochrome P450 isoforms inhibitors and substrates (for CYP2C9, CYP3A4, CYP2C19, and CYP2B6) to determine the cytochrome that was responsible for phenazepam’s metabolism. We also measured CYP3A activity using the 6-betahydroxycortisol/cortisol ratio in patients. Results: According to in silico and in vitro analysis results, the most probable metabolizer of phenazepam is CYP3A4. By the in vivo study results, CYP3A activity decreased sufficiently (from 3.8 [95% CI: 2.94–4.65] to 2.79 [95% CI: 2.02–3.55], p=0.017) between the start and finish of treatment in patients who were prescribed just phenazepam. Conclusions: Experimental in silico and in vivo studies confirmed that the original Russian benzodiazepine phenazepam was the substrate of CYP3A4 isoenzyme.

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