In silico analysis of the antimicrobial activity of phytochemicals: towards a technological breakthrough

The Phytochemical Tactics for Battling Antibiotic Resistance in Microbes: Secondary Metabolites and Nano Antibiotics Methods

One of the most serious threats to human health is antibiotic resistance, which has left the world without effective antibiotics. While continuous research and inventions for new antibiotics are going on, especially those with new modes of action, it is unlikely that this alone would be sufficient to win the battle. Furthermore, it is also important to investigate additional approaches. One such strategy for improving the efficacy of existing antibiotics is the discovery of adjuvants. This review has collected data from various studies on the current crisis and approaches for combating multi-drug resistance in microbial pathogens using phytochemicals. In addition, the nano antibiotic approaches, are discussed, highlighting the high potentials of essential oils, alkaloids, phenolic compounds, and nano antibiotics in combating antibiotic resistance.

In silico evaluation of usnic acid derivatives to discover potential antibacterial drugs against DNA gyrase B and DNA topoisomerase IV

Due to the rising increase in infectious diseases brought on by bacteria and anti-bacterial drug resistance, antibacterial therapy has become difficult. The majority of first-line antibiotics are no longer effective against numerous germs, posing a new hazard to global human health in the 21st century. Through the drug-likeness screening, 184 usnic acid derivatives were selected from an in-house database of 340 usnic acid compounds. The pharmacokinetics (ADMET) prediction produced fifteen hit compounds, of which the lead molecule was subsequently obtained through a molecular docking investigation. The lead compounds, labelled compound-277 and compound-276, respectively, with the substantial binding affinity towards the enzymes were obtained through further docking simulation on the DNA gyrase and DNA topoisomerase proteins. Additionally, molecular dynamic (MD) simulation was performed for 300 ns on the lead compounds in order to confirm the stability of the docked complexes and the binding pose discovered during docking tests. Due to their intriguing pharmacological characteristics, these substances may be promising therapeutic candidate for anti-bacterial medication.Communicated by Ramaswamy H. Sarma.

In silico Prediction and Pharmacokinetic Studies on Glucosinolates as a Potential Drug and Key Inhibitor Molecule for Lanosterol-14α- demethylase: A Fungal Membrane Biosynthesis Enzyme

BACKGROUND

Glucosinolates (β-thioglucoside-N-hydroxysulfates) are a water-soluble organic anion with sulfur- and nitrogen-containing glycosides which are found in abundance in Cruciferous plants. Ergosterol (ERG13) lanosterol-14α-demethylase protein has been targeted for inhibition studies as a key regulator enzyme of fungal membrane biosynthesis.

OBJECTIVES

To understand the molecular mechanism of inhibition of Ergosterol (ERG13) lanosterol- 14α-demethylase by various phytochemicals from brassicales, i.e., glucosinolates and their potential role as putative drug molecules.

METHODS

In this study, in silico analyses were performed to predict the molecular basis of various glucosinolates as a potential inhibitor of lanosterol-14α-demethylase protein, which is a key regulator of fungal membrane biosynthesis and its pharmacodynamics and toxicity profile. 3d structures of various glucosinolates were retrieved from PubChem, and the target protein, lanosterol-14α-demethylase (Pdb ID- 4lxj), was retrieved from the RCSB protein data bank. Molecular docking and interactions were carried out using the PyRx software using the AutoDOCK toolbar with default parameters. Dru- LiTo, ORISIS web servers were used to predict various drug likeliness predictions and Lipinski's Rule of 5, whereas admetSAR was used for prediction of toxicity, and PASS Program was used to study the antifungal and antimicrobial properties of these compounds.

RESULTS

This study shows that among the different compounds screened, gluconasturtiin, Glucotropaeolin, and Indolylmethyl-Glucosinolate showed the highest binding energies of -8.7 kcal/mol, -8.5 kcal/mol, and -8.3 kcal/mol with the lanosterol-14α-demethylase, respectively. Further all the compounds follow the Lipinski's rule as well as they are found to be non-carcinogenic and non-cytotoxic in nature. These compounds also show antifungal properties.

CONCLUSION

This study thus reveals that various glucosinolates interact with the ERG13 enzyme at various amino acid positions, which behaves as a catalytic site, thus indicates the probable mechanism of inactivation, and subsequently, these can be used as potential drug molecules. In vitro studies can be taken to further examine the utility of these compounds as antifungal agents.

In Silico and In Vitro Screening Constituents of Eclipta alba Leaf Extract to Reveal Antimicrobial Potential

Phytochemicals have been shown to possess multiple bioactives and have been reported to showcase many medicinal effects. A similar kind of evaluation of phytoconstituents for their antimicrobial action has been reported, based on in vitro and in silico data. The goal of the research was to explore bioactive phytoconstituents of Eclipta alba leaf for antimicrobial activity. The antimicrobial activity was validated by both molecular docking and antimicrobial assay. Bioactive metabolites were identified using GC-MS. The antimicrobial and antimycobacterial activity of Eclipta alba leaves was investigated using the Kirby–Bauer well diffusion method and the rapid culture—MGIT™ DST method against a variety of human pathogens, as well as Mycobacterium tuberculosis (H37Rv) and Mycobacterium tuberculosis bacteria resistant to isoniazid and rifampicin. Eclipta alba’s GC-MS studies confirmed the detection of 17 bioactive constituents. The extract demonstrates the highest antibacterial activity against Escherichia coli (sensitive), Pseudomonas aeruginosa (sensitive) and methicillin-resistant Staphylococcus aureus (MRSA), and Pseudomonas aeruginosa susceptible and MRSA (sensitive) with zone of inhibition of 27 mm, 24 mm, and 32 mm respectively. The extract showed no effect on Mycobacterium tuberculosis (H37Rv) and Mycobacterium tuberculosis bacteria resistant to isoniazid and rifampicin in antimycobacterial activity testing. Molecular docking investigation revealed that three compounds (phthalic acid, isobutyl octadecyl ester, hexadecanoic acid, 1(hydroxymethyl)1,2-ethanediylester, and 2,myristynoyl pantetheine) have generated the best results in terms of binding energies and significant interactions with key residues of target protein 3-hydroxydecanoyl-acyl carrier protein dehydratase (FabA) and confirm its activity as antimicrobial inhibitors. These two-dimensional plots show significant protein-ligand binding interactions (van der Waals interactions, hydrogen bond, alkyl, and Pi-alkyl interactions). ADMET (absorption, distribution, metabolism, excretion, and toxicity) results additionally support the drug-likeness characteristics of concluded potential compounds. The experimental and computational results demonstrated that methanolic extract of Eclipta alba leaves had antimicrobial effects for specific infections due to the presence of phytochemical compounds.

Forecasting the spread of SARS-CoV-2 in the campania region using genetic programming

Coronavirus disease 19 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus, which is responsible for the ongoing global pandemic. Stringent measures have been adopted to face the pandemic, such as complete lockdown, shutting down businesses and trade, as well as travel restrictions. Nevertheless, such solutions have had a tremendous economic impact. Although the use of recent vaccines seems to reduce the scale of the problem, the pandemic does not appear to finish soon. Therefore, having a forecasting model about the COVID-19 spread is of paramount importance to plan interventions and, then, to limit the economic and social damage. In this paper, we use Genetic Programming to evidence dependences of the SARS-CoV-2 spread from past data in a given Country. Namely, we analyze real data of the Campania Region, in Italy. The resulting models prove their effectiveness in forecasting the number of new positives 10/15 days before, with quite a high accuracy. The developed models have been integrated into the context of SVIMAC-19, an analytical-forecasting system for the containment, contrast, and monitoring of Covid-19 within the Campania Region.

Profiling of Antifungal Activities and In Silico Studies of Natural Polyphenols from Some Plants

A worldwide increase in the incidence of fungal infections, emergence of new fungal strains, and antifungal resistance to commercially available antibiotics indicate the need to investigate new treatment options for fungal diseases. Therefore, the interest in exploring the antifungal activity of medicinal plants has now been increased to discover phyto-therapeutics in replacement to conventional antifungal drugs. The study was conducted to explore and identify the mechanism of action of antifungal agents of edible plants, including Cinnamomum zeylanicum, Cinnamomum tamala, Amomum subulatum, Trigonella foenumgraecum, Mentha piperita, Coriandrum sativum, Lactuca sativa, and Brassica oleraceae var. italica. The antifungal potential was assessed via the disc diffusion method and, subsequently, the extracts were assessed for phytochemicals and total antioxidant activity. Potent polyphenols were detected using high-performance liquid chromatography (HPLC) and antifungal mechanism of action was evaluated in silico. Cinnamomum zeylanicum exhibited antifungal activity against all the tested strains while all plant extracts showed antifungal activity against Fusarium solani. Rutin, kaempferol, and quercetin were identified as common polyphenols. In silico studies showed that rutin displayed the greatest affinity with binding pocket of fungal 14-alpha demethylase and nucleoside diphosphokinase with the binding affinity (Kd, -9.4 and -8.9, respectively), as compared to terbinafine. Results indicated that Cinnamomum zeylanicum and Cinnamomum tamala exert their antifungal effect possibly due to kaempferol and rutin, respectively, or possibly by inhibition of nucleoside diphosphokinase (NDK) and 14-alpha demethylase (CYP51), while Amomum subulatum and Trigonella foenum graecum might exhibit antifungal potential due to quercetin. Overall, the study demonstrates that plant-derived products have a high potential to control fungal infections.

Evidence of the correlation between a city's air pollution and human health through soft computing

Huge quantities of pollutants are released into the atmosphere of many cities every day. These emissions, due to physicochemical conditions, can interact with each other, resulting in additional pollutants such as ozone. The resulting accumulation of pollutants can be dangerous for human health. To date, urban pollution is recognized as one of the main environmental risk factors. This research aims to correlate, through soft computing techniques, namely Artificial Neural Networks and Genetic Programming, the data of the tumours recorded by the Local Health Authority of the city of Benevento, in Italy, with those of the pollutants detected in the air monitoring stations. Such stations can monitor many pollutants, i.e. NO2, CO, PM10, PM2.5, O3 and Benzene (C6H6). Assuming possible effects on human health in the medium term, in this work we treat the data relating to pollutants from the 2012-2014 period while, the tumour data, provided by local hospitals, refer to the time interval 2016-2018. The results show a high correlation between the cases of lung tumours and the exceedance of atmospheric particulate matter and ozone. The explicit genetic programming knowledge representation allows also to measure the relevance of each considered pollutant on human health, evidencing the major role of PM10, NO2 and O3.

Chestnut Shell Tannins: Effects on Intestinal Inflammation and Dysbiosis in Zebrafish

Simple Summary

With the increase in global population the production of animal proteins becomes increasingly crucial. Aquaculture is the first animal protein supply industry for human consumption. Intensive farming techniques are employed to increase productivity, but these may cause stressful conditions for fish, resulting in impaired growth and poor health conditions. Intestinal inflammation is one of the most common diseases of fish in intensive farming. Intestinal inflammation is usually accompanied by an alteration of the microbiota or dysbiosis. Inflammation and dysbiosis are so tightly intertwined that inflammation may contribute to or result from dysregulation of gut microbiota. Natural substances of plant origin rich in bioactive molecules or more simply phytochemicals, have been proved to be able to reduce inflammation and improve the general health status in various commercially relevant species. In this study, we evaluated the effect of tannins, a class of polyphenols, the most abundant phytochemicals, on intestinal inflammation and microbiota in zebrafish (Danio rerio), a small freshwater fish become an attractive biomedicine and aquaculture animal model during the last decades. The zebrafish has been employed in a vast array of studies aiming at investigating the essential processes underlying intestinal inflammation and injury due to its conservative gut morphology and functions. In this study, we administered a diet enriched with chestnut shell extract rich in tannins to a zebrafish model of intestinal inflammation. The treatment ameliorated the damaged intestinal morphophysiology and the microbiota asset. Our results sustain that products of natural origin with low environmental impact and low cost, such as tannins, may help to ease some of the critical issues affecting the aquaculture sector.

Abstract

The aim of the present study was to test the possible ameliorative efficacy of phytochemicals such as tannins on intestinal inflammation and dysbiosis. The effect of a chestnut shell (Castanea sativa) extract (CSE) rich in polyphenols, mainly represented by tannins, on k-carrageenan-induced intestinal inflammation in adult zebrafish (Danio rerio) was tested in a feeding trial. Intestinal inflammation was induced by 0.1% k-carrageenan added to the diet for 10 days. CSE was administered for 10 days after k-carrageenan induced inflammation. The intestinal morphology and histopathology, cytokine expression, and microbiota were analyzed. The k-carrageenan treatment led to gut lumen expansion, reduction of intestinal folds, and increase of the goblet cells number, accompanied by the upregulation of pro-inflammatory factors (TNFα, COX2) and alteration in the number and ratio of taxonomic groups of bacteria. CSE counteracted the inflammatory status enhancing the growth of health helpful bacteria (Enterobacteriaceae and Pseudomonas), decreasing the pro-inflammatory factors, and activating the anti-inflammatory cytokine IL-10. In conclusion, CSE acted as a prebiotic on zebrafish gut microbiota, sustaining the use of tannins as food additives to ameliorate the intestinal inflammation. Our results may be relevant for both aquaculture and medical clinic fields.