Rutin as promising drug for the treatment of Parkinson’s disease: an assessment of MAO-B inhibitory potential by docking, molecular dynamics and DFT studies

Deep convolutional neural network-based identification and biological evaluation of MAO-B inhibitors

Parkinson's disease (PD) is one of the most prominent motor disorder of adult-onset dementia connected to memory and other cognitive abilities. Individuals with this vicious neurodegenerative condition tend to have an elevated expression of Monoamine Oxidase-B (MAO-B) that catalyzes the oxidative deamination of aryalkylamines neurotransmitters with concomitant reduction of oxygen to hydrogen peroxide. This oxidative stress damages mitochondrial DNA and contributes to the progression of PD. To address this, we have developed a deep learning (DL)-based virtual screening protocol for the identification of promising MAO-B inhibitors using Convolutional neural network (ConvNet) based image classification technique by dealing with two unique kinds of image datasets associated with MACCS fingerprints. Following model building and prediction on the Maybridge library, our approach shortlisted the top 11 compounds at the end of molecular docking protocol. Further, the biological validation of the hits identified 4 compounds as promising MAO-B inhibitors. Among these, the compound RF02426 was found to have >50 % inhibition at 10 μM. Additionally, the study also underscored the utility of scaffold analysis as an effective way for evaluating the significance of structurally diverse compounds in data-driven investigations. We believe that our models are able to pick up diverse chemotype and this can be a starting scaffold for further structural optimization with medicinal chemistry efforts in order to improve their inhibition efficacy and be established as novel MAO-B inhibitors in the furture.

Exploring Indonesian actinomycete extracts for anti-tubercular compounds: Integrating inhibition assessment, genomic analysis, and prediction of its target by molecular docking

Tuberculosis (TB) is the foremost cause of infectious fatality globally. The primary global challenge in combatting TB lies in addressing the emergence of drug-resistant variants of the disease. However, the number of newly approved agents for treating TB has remained remarkably low over recent decades. Hence, research endeavors for discovering novel anti-TB agents are always needed. In the present study, we screened over 1,500 culture extracts from actinomycetes isolated in Indonesia for their inhibitory activity against Mycobacterium smegmatis used as a surrogate in the primary screening. The initial screening yielded approximately 6.2 % hit extracts, with a selection criterion of >80 % growth inhibition. The confirmed hit extracts were subsequently subjected to growth inhibition assay against Mycobacterium bovis and Mycobacterium tuberculosis. Approximately 20 % of the hit extracts that showed growth inhibition also exhibited efficacy against M. bovis BCG and M. tuberculosis H37Rv pathogenic strain. An active compound was successfully purified from a large-scale culture of the most potent representative extract by high-performance liquid chromatography and thin-layer chromatography. The structure of the active compound was elucidated by mass spectrometry and nuclear magnetic resonance. This compound displayed structural similarities to actinomycin group and exhibited robust inhibition, with IC50 values of 0.74, 0.02, and 0.07 μg/mL against M. smegmatis, M. bovis, and M. tuberculosis, respectively. The Actinomycetes strain A612, which produced the active compound, was taxonomically classified by phylogenetic analysis of 16s rRNA gene and whole genome sequencing data as Streptomyces parvus. Computational genome analysis utilizing anti-SMASH 7.0 unveiled that S. parvus A612 strain harbors 40 biosynthetic gene clusters with the potential to produce 16 known (with >70 % similarity) and 24 unknown compounds. A non-ribosomal peptide synthesis (NRPS) gene cluster associated with actinomycin D biosynthesis was also identified, boasting an 85 % similarity. Molecular docking analysis of actinomycin D and 21 potential M. tuberculosis targets revealed possible interactions with multiple targets. The purified active compound inhibited recombinant M. tuberculosis shikimate kinase (MtSK), which validated the results obtained from the docking analysis.

Structural, computational and in silico studies of 4-bromo-3-flurobenzonitrile as anti-Alzheimer and anti-Parkinson agents

A novel dimer of the 4-bromo-3-fluorobenzonitrile was crystallized and studied using a spectroscopic method such as the scanning electron microscope method. The computational simulations substantiated the structural analysis findings. The Hirshfeld surface analysis has been performed for visualizing, exploring and quantifying the intra and inter-molecular interactions that stabilize the crystal packing of the compound. The NBO and QTAIM analyses were applied to study the nature and origin of the attractive forces involved in the crystal structure. Further, the pharmacokinetic properties of the compound were evaluated, indicating good brain-blood barrier and central nervous system penetration capability. Hence, in silico studies was carried out to explore the binding pattern of the titled compound against acetylcholinesterase and butyrylcholinesterase, and tumor necrosis factor-alpha converting enzyme proteins using molecular docking and molecular dynamics simulations approach. Further, the titled compound is compared with standard drugs through molecular docking studies. The in silico studies finally predicts that the compound under investigation may act as a good inhibitor for treating Alzheimer's disease and further in vitro and in vivo studies may provide its therapeutic potential.Communicated by Ramaswamy H. Sarma.

Structure-Based Design of Novel MAO-B Inhibitors: A Review

With the significant growth of patients suffering from neurodegenerative diseases (NDs), novel classes of compounds targeting monoamine oxidase type B (MAO-B) are promptly emerging as distinguished structures for the treatment of the latter. As a promising function of computer-aided drug design (CADD), structure-based virtual screening (SBVS) is being heavily applied in processes of drug discovery and development. The utilization of molecular docking, as a helping tool for SBVS, is providing essential data about the poses and the occurring interactions between ligands and target molecules. The current work presents a brief discussion of the role of MAOs in the treatment of NDs, insight into the advantages and drawbacks of docking simulations and docking software, and a look into the active sites of MAO-A and MAO-B and their main characteristics. Thereafter, we report new chemical classes of MAO-B inhibitors and the essential fragments required for stable interactions focusing mainly on papers published in the last five years. The reviewed cases are separated into several chemically distinct groups. Moreover, a modest table for rapid revision of the revised works including the structures of the reported inhibitors together with the utilized docking software and the PDB codes of the crystal targets applied in each study is provided. Our work could be beneficial for further investigations in the search for novel, effective, and selective MAO-B inhibitors.

Flavonols in Action: Targeting Oxidative Stress and Neuroinflammation in Major Depressive Disorder

Major depressive disorder is one of the most common mental illnesses that highly impairs quality of life. Pharmacological interventions are mainly focused on altered monoamine neurotransmission, which is considered the primary event underlying the disease's etiology. However, many other neuropathological mechanisms that contribute to the disease's progression and clinical symptoms have been identified. These include oxidative stress, neuroinflammation, hippocampal atrophy, reduced synaptic plasticity and neurogenesis, the depletion of neurotrophic factors, and the dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis. Current therapeutic options are often unsatisfactory and associated with adverse effects. This review highlights the most relevant findings concerning the role of flavonols, a ubiquitous class of flavonoids in the human diet, as potential antidepressant agents. In general, flavonols are considered to be both an effective and safe therapeutic option in the management of depression, which is largely based on their prominent antioxidative and anti-inflammatory effects. Moreover, preclinical studies have provided evidence that they are capable of restoring the neuroendocrine control of the HPA axis, promoting neurogenesis, and alleviating depressive-like behavior. Although these findings are promising, they are still far from being implemented in clinical practice. Hence, further studies are needed to more comprehensively evaluate the potential of flavonols with respect to the improvement of clinical signs of depression.

Silibinin chronic treatment in a rat model of Parkinson disease: A comprehensive in-vivo evaluation and in silico molecular modeling

BACKGROUND

Apoptosis, oxidative stress, and neuroinflammation have been linked to the onset of Parkinson's disease (PD). Although the pre-treatment effects of Silibinin on a PD model have been evaluated, in the current study we investigated the chronic therapeutic effects of Silibinin microinjection on a rat model of established parkinsonism along with behavioral and laboratory markers assessments.

METHOD

Parkinsonism was induced by 6-hydroxydopamine (6-OHDA, 8 μg/2μl/rat). 21 days after that, animals were treated with Silibinin (100, 200, and 300 mg/kg for 15 consecutive days). Every two days, the bar test was used to evaluate Silibinin's anti-cataleptic properties. At the end, myeloperoxidase (MPO) activity and toll-like receptor 4 (TLR4) expression in the substantia nigra pars compacta (SNc), along with cerebrospinal fluid (CSF) levels of tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1β, IL-6, caspase-3, Bax and Bcl-2 levels were assessed. We used homology modeling to predict the 3D structure of TLR4.

RESULT

Silibinin's Chronic treatment, dose-dependently decreased catalepsy. MPO activity and levels of TNF-α, IL-6, and IL-1β were reduced in Silibinin-treated rats in all three doses. Silibinin decreased Bax/Bcl-2 ratio, caspase-3, and downregulated TLR4 expression. Molecular docking revealed that there were hydrophobic and hydrogen bond interactions between the studied ligand and TLR4. Silibinin formed a stable complex with both monomer and dimer forms of TLR4.

CONCLUSION

In accordance with molecular modeling and alleviation of TLR4 activity with a consequent reduction in oxidative stress, restoration of CSF inflammatory cytokine, and minimization of SNc neuronal apoptosis, long-term therapy with Silibinin offers a potential opportunity for symptomatic PD treatment.

Molecular docking/dynamics simulations, MEP analysis, bioisosteric replacement and ADME/T prediction for identification of dual targets inhibitors of Parkinson's disease with novel scaffold

Monoamine oxidase B and Adenosine A2A receptors are used as key targets for Parkinson's disease. Recently, hMAO-B and hA2AR Dual-targets inhibitory potential of a novel series of Phenylxanthine derivatives has been established in experimental findings. Hence, the current study examines the interactions between 38 compounds of this series with hMAO-B and hA2AR targets using different molecular modeling techniques to investigate the binding mode and stability of the formed complexes. A molecular docking study revealed that the compounds L24 ((E)-3-(3-Chlorophenyl)-N-(4-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl) phenyl) acrylamide and L32 ((E)-3-(3-Chlorophenyl)-N-(3-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl)phenyl)acrylamide) had a high affinity (S-score: -10.160 and -7.344 kcal/mol) with the pocket of hMAO-B and hA2AR targets respectively, and the stability of the studied complexes was confirmed during MD simulations. Also, the MEP maps of compounds 24 and 32 were used to identify the nucleophilic and electrophilic attack regions. Moreover, the bioisosteric replacement approach was successfully applied to design two new analogs of each compound with similar biological activities and low energy scores. Furthermore, ADME-T and Drug-likeness results revealed the promising pharmacokinetic properties and oral bioavailability of these compounds. Thus, compounds L24, L32, and their analogs can undergo further analysis and optimization in order to design new lead compounds with higher efficacy toward Parkinson's disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00139-3.

Screening of Monoamine Oxidase B Inhibitors from Fragaria nubicola by Ligand Fishing and Their Neuroprotective Effects

Fragaria nubicola, known as Tibetan strawberry, is an edible plant possessing various health-promoting effects. However, its functional compositions were rarely studied. In this work, monoamine oxidase B (MAO-B) inhibitors in this plant were rapidly screened using the enzyme-functionalized magnetic nanoparticles coupled with UPLC-QTOF-MS. Two inhibitors, quercetin-3-O-β-d-glucuronide-6″-methyl ester (1) and kaempferol-3-O-β-d-glucuronide-6″-methyl ester (2), were identified from this plant with the IC₅₀ values of 19.44 ± 1.17 and 22.63 ± 1.78 μM, respectively. Enzyme kinetic analysis and molecular docking were carried out to investigate the mechanism of inhibition. Contents of both compounds as well as those of total phenolics and flavonoids were quantified to be 24.76 ± 1.26, 35.59 ± 1.17, 837.67 ± 10.62, and 593.46 ± 10.37 μg/g, respectively. In addition, both compounds exhibited significant neuroprotective effects on 6-hydroxydopamine-induced PC12 cells. This is the first report on the neuroprotective components of F. nubicola, suggesting its potential for developing neuroprotective functional food.

Phenolic compounds from Tradescantia pallida ameliorate diabetes by inhibiting enzymatic and non-enzymatic pathways

Diabetes is a chronic metabolic disorder marked by postprandial hyperglycemia due to several etiologies including abnormal carbohydrate digestion and glycation of hemoglobin. The prolong use of synthetic drugs results in characteristic side effects which necessitates the discovery of safe and cost-effective substitutes. The aim of the current study is to isolate and evaluate the antidiabetic potential of the phenolic compounds from the leaves of Tradescantia pallida. Syringic acid, p-coumaric acid, morin and catechin (compounds 1-4) were isolated and characterized from Tradescantia pallida leaves using column chromatography and spectroscopic techniques. The in vitro antidiabetic potential of the phenolic compounds were assessed using α-amylase and non-enzymatic glycosylation of hemoglobin protein assays. A mechanistic insight of interactions between phenolic compounds and human α-amylase and hemoglobin protein were scrutinized by employing molecular docking method. Prime Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) calculations were carried out to find the binding energies of the ligand-protein complexes. Morin and catechin were further analyzed to find the dynamic and thermodynamic constraints of the complexes under specific biological conditions using molecular dynamic simulation trajectories. The stability and flexibility of the complexes were justified by fluctuation of α-carbon chain, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) and type of interactions involved which authenticated the in vitro inhibitory potential of morin and catechin against enzymatic and non-enzymatic pathways. The current study could be fruitful in rational designing of safe antidiabetic drugs of natural origin.Communicated by Ramaswamy H. Sarma.

Ligand fishing of monoamine oxidase B inhibitors from Platycodon grandiflorus (Jacq.) A.DC. roots by the enzyme functionalised magnetic nanoparticles

INTRODUCTION

As a famous traditional Chinese medicine, roots of Platycodon grandiflorus (Jacq.) A.DC. have shown multiple effects against neurodegenerative diseases. To investigate the components against Parkinson's disease (PD), the roots of P. grandiflora were selected as the research subject.

OBJECTIVE

Screening and identifying of monoamine oxidase B (MAO-B) inhibitors from the roots of P. grandiflorum via enzyme functionalised magnetic nanoparticles (MNPs)-based ligand fishing combined with high-performance liquid chromatography-mass spectrometry (HPLC-MS) analysis.

METHOD

MAO-B functionalised MNPs have been synthesised for screening MAO-B inhibitors from the roots of P. grandiflorum. The ligands were identified by HPLC-MS and nuclear magnetic resonance (NMR) analysis, and their anti-PD activity was evaluated via MAO-B inhibition assay and cell viability assay in vitro.

RESULTS

Two MAO-B inhibitors were fished out and identified by HPLC-MS as protocatechuic aldehyde (1) and coumarin (2), with the half maximal inhibitory concentrations of 28.54 ± 0.39 and 25.39 ± 0.29 μM, respectively. Among them, 1 could also significantly increase the viability of 6-hydroxydopamine-damaged PC12 cells.

CONCLUSION

The results are helpful to elucidate the anti-PD activity of the plant, and the ligand fishing method has shown good potential in discovery of MAO-B inhibitors.

Prediction of α-Glucosidase Inhibitory Activity of LC-ESI-TQ-MS/MS-Identified Compounds from Tradescantia pallida Leaves

Diabetes is a chronic disease that leads to abnormal carbohydrate digestion and hyperglycemia. The long-term use of marketed drugs results in secondary infections and side effects that demand safe and natural substitutes for synthetic drugs. The objective of this study is to evaluate the antidiabetic potential of compounds from the leaves of Tradescantia pallida. Thirteen phenolic compounds were identified from the ethyl acetate fraction of leaves of Tradescantia pallida using liquid chromatography-mass spectrometry. The compounds were then studied for the type of interactions between polyphenols and human α-glucosidase protein using molecular docking analysis. Prime Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) calculations were performed to measure the binding free energies responsible for the formation of ligand-protein complexes. The compounds were further investigated for the thermodynamic constraints under a specified biological environment using molecular dynamic simulations. The flexibility of the ligand-protein systems was verified by Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) and molecular interactions. The results authenticated the antidiabetic potential of polyphenols identified from the leaves of Tradescantia pallida. Our investigations could be helpful in the design of safe antidiabetic agents, but further in vitro and in vivo investigations are required.

The Structural, Biological, and In-Silico Profiling of Novel Capryloyl Tetra-Glucoside and Aliphatic Ester Constituents from the Abutilon indicum Offers New Perspectives on the Treatment of Pain and Inflammation

Abutilon indicum L. (Malvaceae), more often referred to as Peeli booti, Kanghi, and Kakhi, is a perennial shrub found in many countries of Asia. Traditionally, this plant is used as a diuretic to treat inflammation, discomfort, urethral infections, and gout. Inflammation and pain are key topics of interest for researchers throughout the globe, since they are linked to almost every illness that could affect humans or animals. The present study was conducted to isolate the phytoconstituents from the methanolic extract of Abutilon indicum collected from the Bihar state Koshi river belt in India, and to evaluate the isolated phytoconstituents' ability to reduce nociception and inflammation. Furthermore, molecular docking was performed to investigate the molecular interaction profile, with possible therapeutic targets for anti-inflammatory medicines. A. indicum methanolic extract yielded two novel phytocompounds identified as 5'-hydroxyhexyl n-hexadecanoate (AB-01) and n-octanoyl-β-D-glucopyranosyl-(2'-1'')-β-D-glucopyranosyl-(2''-1''')-β-D-glucopyranosyl-(2'''-1'''')-β-D-glucopyranoside (AB-05), together with three previously recognized phytocompounds such as ester glucoside. All isolated molecules were tested for the efficacy of analgesic and anti-inflammatory characteristics at doses of 5 and 10 mg/kg body weight. The isolated compound's molecular interaction profile with anti-inflammatory drug targets cyclooxygenase-2 and tumor necrosis factor-alpha possessed high potential energy in molecular docking. These findings may aid in developing anti-inflammatory and analgesic drugs from A. indicum.

Toward the Discovery of a Novel Class of Leads for High Altitude Disorders by Virtual Screening and Molecular Dynamics Approaches Targeting Carbonic Anhydrase

For decades, carbonic anhydrase (CA) inhibitors, most notably the acetazolamide-bearing 1,3,4-thiadiazole moiety, have been exploited at high altitudes to alleviate acute mountain sickness, a syndrome of symptomatic sensitivity to the altitude characterized by nausea, lethargy, headache, anorexia, and inadequate sleep. Therefore, inhibition of CA may be a promising therapeutic strategy for high-altitude disorders. In this study, co-crystallized inhibitors with 1,3,4-thiadiazole, 1,3-benzothiazole, and 1,2,5-oxadiazole scaffolds were employed for pharmacophore-based virtual screening of the ZINC database, followed by molecular docking and molecular dynamics simulation studies against CA to find possible ligands that may emerge as promising inhibitors. Compared to the co-crystal ligands of PDB-1YDB, 6BCC, and 6IC2, ZINC12336992, ZINC24751284, and ZINC58324738 had the highest docking scores of -9.0, -9.0, and -8.9 kcal/mol, respectively. A molecular dynamics (MD) simulation analysis of 100 ns was conducted to verify the interactions of the top-scoring molecules with CA. The system's backbone revealed minor fluctuations, indicating that the CA-ligand complex was stable during the simulation period. Simulated trajectories were used for the MM-GBSA analysis, showing free binding energies of -16.00 ± 0.19, -21.04 ± 0.17, and -19.70 ± 0.18 kcal/mol, respectively. In addition, study of the frontier molecular orbitals of these compounds by DFT-based optimization at the level of B3LYP and the 6-311G(d,p) basis set showed negative values of the HOMO and LUMO, indicating that the ligands are energetically stable, which is essential for forming a stable ligand-protein complex. These molecules may prove to be a promising therapy for high-altitude disorders, necessitating further investigations.

In silico and in vitro studies on the inhibition of laccase activity by Ellagic acid: Implications in drug designing for the treatment of Cryptococcal infections

In recent years, the increased frequency of drug-resistant strains of Cryptococcus neoformans has depleted our antifungal armory. In the present study, we investigated the inhibitory potential of ellagic acid (EA) against C. neoformans laccase through in silico and in vitro studies. For the first time, a homology modelling was established to model laccase and modelled protein served as a receptor for docking EA. Thermodynamic stability of the docked complex was ascertained by molecular dynamics simulation (MD). The analysis of root mean square deviation and fluctuation of alpha carbons of protein justifies the stability of the bound EA in the binding pocket of laccase. Frontier molecular orbitals of the EA was studied by density functional theory-based optimization by using the Lee-Yang-Parr correlation functional (B3LYP) approach. Negative values of the highest occupied/unoccupied molecular orbitals (HOMO/LUMO) indicated that laccase with EA forms a stable complex. Interestingly, EA inhibited laccase activity both in vitro and in yeast cells of C. neoformans. Moreover, EA treatment remarkably inhibited the proliferation of C. neoformans inside macrophages. The findings of the present study unveil the molecular basis of the interactions of laccase with EA, which may prove to be beneficial for designing laccase inhibitors as potential anti-cryptococcal agents.

Topological Coindices and Quantitative Structure-Property Analysis of Antiviral Drugs Investigated in the Treatment of COVID-19

SARS-CoV-2 is a new strain of coronavirus family that has never been previously detected in humans. This has grown into a huge public health issue that has affected people all around the world. Presently, there is no specific antiviral treatment for COVID-19. To tackle the outbreak, a number of drugs are being explored or have been utilized based on past experience. A molecular descriptor (or topological index) is a numerical value that describes a compound’s molecular structure and has been successfully employed in many QSPR/QSAR investigations to represent several physicochemical attributes. In order to determine topological characteristics of graphs, coindices (topological) take nonadjacent pair of vertices into account. In this study, we introduced CoM-polynomial and numerous degree-based topological coindices for several antiviral medicines such as lopinavir, ritonavir remdesivir, hydroxychloroquine, chloroquine, theaflavin, thalidomide, and arbidol which were studied using the CoM-polynomial approach. In the QSPR model, the linear regression approach is used to analyze the relationships between physicochemical properties and topological coindices. The findings show that the topological coindices under investigation have a substantial relationship with the physicochemical properties of possible antiviral medicines in question. As a result, topological coindices may be effective tools for studying antiviral drugs in the future for QSPR analyses.

Safety, Stability, and Therapeutic Efficacy of Long-Circulating TQ-Incorporated Liposomes: Implication in the Treatment of Lung Cancer

Thymoquinone (TQ), which is one of the main bioactive constituents of Nigella sativa seeds, has demonstrated its potential against various cancer models. The poor solubility of TQ in aqueous solution limits its uses in clinical application. The present study aimed to develop a novel formulation of TQ to increase its bioavailability and therapeutic potential with minimal toxicity. Polyethylene glycol (PEG)-coated DSPC/cholesterol comprising TQ liposomes (PEG-Lip-TQ) were prepared and characterized on various aspects. A computational investigation using molecular docking was used to assess the possible binding interactions of TQ with 12 prospective anticancer drug targets. The in vitro anticancer activity was assessed in A549 and H460 lung cancer cells in a time- and dose-dependent manner, while the oral acute toxicity assay was evaluated in silico as well as in vivo in mice. TQ docked to the Hsp90 target had the lowest binding energy of −6.05 kcal/mol, whereas caspase 3 was recognized as the least likely target for TQ with a binding energy of −1.19 kcal/mol. The results showed 96% EE with 120 nm size, and −10.85 mv, ζ-potential of PEG-Lip-TQ, respectively. The cell cytotoxicity data demonstrated high sensitivity of PEG-Lip-TQ and a several fold decrease in the IC₅₀ while comparing free TQ. The cell cycle analysis showed changes in the distribution of cells with doses. The in vivo data revealed an ~9-fold increase in the LD₅₀ of PEG-Lip-TQ on free TQ as an estimated 775 and 89.5 mg/kg b.w, respectively. This study indicates that the pharmacological and efficacy profile of PEG-lip-TQ is superior to free TQ, which will pave the way for an exploration of the effect of TQ formulation in the treatment of lung cancer in clinical settings.

Targeting SARS-CoV-2 main protease by teicoplanin: A mechanistic insight by docking, MM/GBSA and molecular dynamics simulation

First emerged in late December 2019, the outbreak of novel severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) pandemic has instigated public-health emergency around the globe. Till date there is no specific therapeutic agent for this disease and hence, the world is craving to identify potential antiviral agents against SARS-CoV-2. The main protease (M^Pro) is considered as an attractive drug target for rational drug design against SARS-CoV-2 as it is known to play a crucial role in the viral replication and transcription. Teicoplanin is a glycopeptide class of antibiotic which is regularly used for treating Gram-positive bacterial infections, has shown potential therapeutic efficacy against SARS-CoV-2 in vitro. Therefore, in this study, a mechanistic insight of intermolecular interactions between teicoplanin and SARS-CoV-2 M^Pro has been scrutinized by molecular docking. Both monomeric and dimeric forms of M^Pro was used in docking involving blind as well as defined binding site based on the known inhibitor. Binding energies of teicoplanin-M^Pro complexes were estimated by Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) computations from docking and simulated trajectories. The dynamic and thermodynamics constraints of docked drug in complex with target proteins under specific physiological conditions was ascertained by all-atom molecular dynamics simulation of 100 ns trajectory. Root mean square deviation and fluctuation of carbon α chain justified the stability of the bound complex in biological environments. The outcomes of current study are supposed to be fruitful in rational design of antiviral drugs against SARS-CoV-2.

Elucidation of Teicoplanin Interactions with Drug Targets Related to COVID-19

Teicoplanin is a glycopeptide antibiotic effective against several bacterial infections, has exhibited promising therapeutic efficiency against COVID-19 in vitro, and the rationale for its use in COVID-19 is yet to be recognized. Hence, in this study a number of molecular modeling techniques were employed to decrypt the mechanistic insight of teicoplanin interaction with several COVID-19 drug targets. Initially, molecular docking was employed to study the teicoplanin interaction with twenty-five SARS-CoV-2 structural and non-structural proteins which was followed by molecular mechanics/generalized Born surface area (MM/GBSA) computation for binding energy predictions of top ten models from each target. Amongst all macromolecular targets, the N-terminal domain of the nucleocapsid protein displayed the strongest affinity with teicoplanin showing binding energies of −7.4 and −102.13 kcal/mol, in docking and Prime MM/GBSA, respectively. Thermodynamic stability of the teicoplanin-nucleocapsid protein was further probed by molecular dynamics simulations of protein–ligand complex as well as unbounded protein in 100 ns trajectories. Post-simulation MM-GBSA computation of 50 frames extracted from simulated trajectories estimated an average binding energy of −62.52 ± 12.22 kcal/mol. In addition, conformational state of protein in complex with docked teicoplanin displayed stable root-mean-square deviation/fluctuation. In conclusion, computational investigation of the potential targets of COVID-19 and their interaction mechanism with teicoplanin can guide the design of novel therapeutic armamentarium for the treatment of SARS-CoV-2 infection. However, additional studies are warranted to establish the clinical use or relapses, if any, of teicoplanin in the therapeutic management of COVID-19 patients.

Isolation, characterization, anti-MRSA evaluation, and in-silico multi-target anti-microbial validations of actinomycin X2 and actinomycin D produced by novel Streptomyces smyrnaeus UKAQ_23

Streptomyces smyrnaeus UKAQ_23, isolated from the mangrove-sediment, collected from Jubail,Saudi Arabia, exhibited substantial antimicrobial activity against methicillin-resistant Staphylococcus aureus (MRSA), including non-MRSA Gram-positive test bacteria. The novel isolate, under laboratory-scale conditions, produced the highest yield (561.3 ± 0.3 mg/kg fermented agar) of antimicrobial compounds in modified ISP-4 agar at pH 6.5, temperature 35 °C, inoculum 5% v/w, agar 1.5% w/v, and an incubation period of 7 days. The two major compounds, K1 and K2, were isolated from fermented medium and identified as Actinomycin X2 and Actinomycin D, respectively, based on their structural analysis. The antimicrobial screening showed that Actinomycin X2 had the highest antimicrobial activity compared to Actinomycin D, and the actinomycins-mixture (X2:D, 1:1, w/w) against MRSA and non-MRSA Gram-positive test bacteria, at 5 µg/disc concentrations. The MIC of Actinomycin X2 ranged from 1.56-12.5 µg/ml for non-MRSA and 3.125-12.5 µg/ml for MRSA test bacteria. An in-silico molecular docking demonstrated isoleucyl tRNA synthetase as the most-favored antimicrobial protein target for both actinomycins, X2 and D, while the penicillin-binding protein-1a, was the least-favorable target-protein. In conclusion, Streptomyces smyrnaeus UKAQ_23 emerged as a promising source of Actinomycin X2 with the potential to be scaled up for industrial production, which could benefit the pharmaceutical industry.

Topological indices and QSPR/QSAR analysis of some antiviral drugs being investigated for the treatment of COVID-19 patients

The spread of novel virus SARS-CoV-2, well known as COVID-19 has become a major health issue currently which has turned up to a pandemic worldwide. The treatment recommendations are variable. Lack of appropriate medication has worsened the disease. On the basis of prior research, scientists are testing drugs based on medical therapies for SARS and MERS. Many drugs which include lopinavir, ritonavir and thalidomide are listed in the new recommendations. A topological index is a type of molecular descriptor that simply defines numerical values associated with the molecular structure of a compound that is effectively used in modeling many physicochemical properties in numerous quantitative structure-property/activity relationship (QSPR/QSAR) studies. In this study, several degree-based and neighborhood degree sum-based topological indices for several antiviral drugs were investigated by using a M-polynomial and neighborhood M-polynomial methods. In addition, a QSPR was established between the various topological indices and various physicochemical properties of these antiviral drugs along with remdesivir, chloroquine, hydroxychloroquine and theaflavin was performed in order to assess the efficacy of the calculated topological indices. The obtained results reveal that topological indices under study have strong correlation with the physicochemical characteristics of the potential antiviral drugs. A biological activity (pIC50) of these compounds were also investigated by using multiple linear regressions (MLR) analysis.

Potential Herb-Drug Interactions in the Management of Age-Related Cognitive Dysfunction

Late-life mild cognitive impairment and dementia represent a significant burden on healthcare systems and a unique challenge to medicine due to the currently limited treatment options. Plant phytochemicals have been considered in alternative, or complementary, prevention and treatment strategies. Herbals are consumed as such, or as food supplements, whose consumption has recently increased. However, these products are not exempt from adverse effects and pharmacological interactions, presenting a special risk in aged, polymedicated individuals. Understanding pharmacokinetic and pharmacodynamic interactions is warranted to avoid undesirable adverse drug reactions, which may result in unwanted side-effects or therapeutic failure. The present study reviews the potential interactions between selected bioactive compounds (170) used by seniors for cognitive enhancement and representative drugs of 10 pharmacotherapeutic classes commonly prescribed to the middle-aged adults, often multimorbid and polymedicated, to anticipate and prevent risks arising from their co-administration. A literature review was conducted to identify mutual targets affected (inhibition/induction/substrate), the frequency of which was taken as a measure of potential interaction. Although a limited number of drugs were studied, from this work, interaction with other drugs affecting the same targets may be anticipated and prevented, constituting a valuable tool for healthcare professionals in clinical practice.

Computational Fragment-Based Design Facilitates Discovery of Potent and Selective Monoamine Oxidase-B (MAO-B) Inhibitor

Parkinson's disease (PD) is one of the most common age-related neurodegenerative diseases. Inhibition of monoamine oxidase-B (MAO-B), which is mainly found in the glial cells of the brain, may lead to an elevated level of dopamine (DA) in patients. MAO-B inhibitors have been used extensively for patients with PD. However, the discovery of the selective MAO-B inhibitor is still a challenge. In this study, a computational strategy was designed for the rapid discovery of selective MAO-B inhibitors. A series of (S)-2-(benzylamino)propanamide derivatives were designed. In vitro biological evaluations revealed that (S)-1-(4-((3-fluorobenzyl)oxy)benzyl)azetidine-2-carboxamide (C3) was more potent and selective than safinamide, a promising drug for regulating MAO-B. Further studies revealed that the selectivity mechanism of C3 was due to the steric clash caused by the residue difference of Phe208 (MAO-A) and Ile199 (MAO-B). Animal studies showed that compound C3 could inhibit cerebral MAO-B activity and alleviate 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced dopaminergic neuronal loss.

An in-silico analysis of ivermectin interaction with potential SARS-CoV-2 targets and host nuclear importin α

Ivermectin (IVM) is a broad-spectrum antiparasitic agent, having inhibitory potential against wide range of viral infections. It has also been found to hamper SARS-CoV-2 replication in vitro, and its precise mechanism of action against SARS-CoV-2 is yet to be understood. IVM is known to interact with host importin (IMP)α directly and averts interaction with IMPβ1, leading to the prevention of nuclear localization signal (NLS) recognition. Therefore, the current study seeks to employ molecular docking, molecular mechanics generalized Born surface area (MM-GBSA) analysis and molecular dynamics simulation studies for decrypting the binding mode, key interacting residues as well as mechanistic insights on IVM interaction with 15 potential drug targets associated with COVID-19 as well as IMPα. Among all COVID-19 targets, the non-structural protein 9 (Nsp9) exhibited the strongest affinity to IVM showing -5.30 kcal/mol and -84.85 kcal/mol binding energies estimated by AutoDock Vina and MM-GBSA, respectively. However, moderate affinity was accounted for IMPα amounting -6.9 kcal/mol and -66.04 kcal/mol. Stability of the protein-ligand complexes of Nsp9-IVM and IMPα-IVM was ascertained by 100 ns trajectory of all-atom molecular dynamics simulation. Structural conformation of protein in complex with docked IVM exhibited stable root mean square deviation while root mean square fluctuations were also found to be consistent. In silico exploration of the potential targets and their interaction profile with IVM can assist experimental studies as well as designing of COVID-19 drugs.

Design and synthesis of pyrazole-pyrazoline hybrids as cancer-associated selective COX-2 inhibitors

In continuation of our previous work on cancer and inflammation, 15 novel pyrazole-pyrazoline hybrids (WSPP1-15) were synthesized and fully characterized. The formation of the pyrazoline ring was confirmed by the appearance of three doublets of doublets in ¹ H nuclear magnetic resonance spectra exhibiting an AMX pattern for three protons (H_A , H_M , and H_X ) of the pyrazoline ring. All the synthesized compounds were screened for their in vitro anticancer activity against five cell lines, that is, MCF-7, A549, SiHa, COLO205, and HepG2 cells, using the MTT growth inhibition assay. 5-Fluorouracil was taken as the positive control in the study. It was observed that, among them, WSPP11 was found to be active against A549, SiHa, COLO205, and HepG2 cells, with IC₅₀ values of 4.94, 4.54, 4.86, and 2.09 µM. All the derivatives were also evaluated for their cytotoxicity against HaCaT cells. WSPP11 was also found to be nontoxic against normal cells (cell line HaCaT), with an IC₅₀ value of more than 50 µM. The derivatives were also evaluated for their in vitro anti-inflammatory activity by the protein (egg albumin) denaturation assay and the red blood cell membrane stabilizing assay, using diclofenac sodium and celecoxib as standard. Compounds that showed significant anticancer and anti-inflammatory activities were further studied for COX-2 inhibition. The manifestation of a higher COX-2 selectivity index of WSPP11 as compared with other derivatives and an in vitro anticancer activity against four cell lines further established that compounds that were more selective toward COX-2 also exhibited a better spectrum of activity against various cancer cell lines.