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1.
SAR QSAR Environ Res ; 32(11): 863-888, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1606722

ABSTRACT

The novel severe acute respiratory syndrome coronavirus (SARS CoV-2) was introduced as an epidemic in 2019 and had millions of deaths worldwide. Given the importance of this disease, the recommendation and design of new active compounds are crucial. 3-chymotrypsin-like protease (3 CLpro) inhibitors have been identified as potent compounds for treating SARS-CoV-2 disease. So, the design of new 3 CLpro inhibitors was proposed using a quantitative structure-activity relationship (QSAR) study. In this context, a powerful adaptive least absolute shrinkage and selection operator (ALASSO) penalized variable selection method with inherent advantages coupled with a nonlinear artificial neural network (ANN) modelling method were used to provide a QSAR model with high interpretability and predictability. After evaluating the accuracy and validity of the developed ALASSO-ANN model, new compounds were proposed using effective descriptors, and the biological activity of the new compounds was predicted. Ligand-receptor (LR) interactions were also performed to confirm the interaction strength of the compounds using molecular docking (MD) study. The pharmacokinetics properties and calculated Lipinski's rule of five were applied to all proposed compounds. Due to the ease of synthesis of these suggested new compounds, it is expected that they have acceptable pharmacological properties.


Subject(s)
Antiviral Agents/chemistry , Coronavirus 3C Proteases/antagonists & inhibitors , Protease Inhibitors/chemistry , SARS-CoV-2/drug effects , Antiviral Agents/pharmacokinetics , Coronavirus 3C Proteases/chemistry , Inhibitory Concentration 50 , Molecular Docking Simulation , Neural Networks, Computer , Protease Inhibitors/pharmacokinetics , Quantitative Structure-Activity Relationship , Reproducibility of Results , SARS-CoV-2/enzymology
2.
Biomolecules ; 11(12)2021 12 04.
Article in English | MEDLINE | ID: covidwho-1554985

ABSTRACT

Inflammation involves a complex biological response of the body tissues to damaging stimuli. When dysregulated, inflammation led by biomolecular mediators such as caspase-1 and tumor necrosis factor-alpha (TNF-alpha) can play a detrimental role in the progression of different medical conditions such as cancer, neurological disorders, autoimmune diseases, and cytokine storms caused by viral infections such as COVID-19. Computational approaches can accelerate the search for dual-target drugs able to simultaneously inhibit the aforementioned proteins, enabling the discovery of wide-spectrum anti-inflammatory agents. This work reports the first multicondition model based on quantitative structure-activity relationships and a multilayer perceptron neural network (mtc-QSAR-MLP) for the virtual screening of agency-regulated chemicals as versatile anti-inflammatory therapeutics. The mtc-QSAR-MLP model displayed accuracy higher than 88%, and was interpreted from a physicochemical and structural point of view. When using the mtc-QSAR-MLP model as a virtual screening tool, we could identify several agency-regulated chemicals as dual inhibitors of caspase-1 and TNF-alpha, and the experimental information later retrieved from the scientific literature converged with our computational results. This study supports the capabilities of our mtc-QSAR-MLP model in anti-inflammatory therapy with direct applications to current health issues such as the COVID-19 pandemic.


Subject(s)
Anti-Inflammatory Agents/pharmacology , Caspase Inhibitors/pharmacology , Drug Repositioning/methods , Tumor Necrosis Factor-alpha/antagonists & inhibitors , Anti-Inflammatory Agents/chemistry , COVID-19/drug therapy , Caspase 1/metabolism , Caspase Inhibitors/chemistry , Humans , Inflammation/drug therapy , Molecular Docking Simulation , Quantitative Structure-Activity Relationship , Tumor Necrosis Factor-alpha/metabolism
3.
SAR QSAR Environ Res ; 32(12): 963-983, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1532255

ABSTRACT

The coronavirus helicase is an essential enzyme required for viral replication/transcription pathways. Structural studies revealed a sulphate moiety that interacts with key residues within the nucleotide-binding site of the helicase. Compounds with a sulphoxide or a sulphone moiety could interfere with these interactions and consequently inhibit the enzyme. The molecular operating environment (MOE) was used to dock 189 sulphoxide and sulphone-containing FDA-approved compounds to the nucleotide-binding site. Zafirlukast, a leukotriene receptor antagonist used to treat chronic asthma, achieved the lowest docking score at -8.75 kcals/mol. The inhibitory effect of the compounds on the SARS-CoV-2 helicase dsDNA unwinding activity was tested by a FRET-based assay. Zafirlukast was the only compound to inhibit the enzyme (IC50 = 16.3 µM). The treatment of Vero E6 cells with 25 µM zafirlukast prior to SARS-CoV-2 infection decreased the cytopathic effects of SARS-CoV-2 significantly. These results suggest that zafirlukast alleviates SARS-CoV-2 pathogenicity by inhibiting the viral helicase and impairing the viral replication/transcription pathway. Zafirlukast could be clinically developed as a new antiviral treatment for SARS-CoV-2 and other coronavirus diseases. This discovery is based on molecular modelling, in vitro inhibition of the SARS-CoV helicase activity and cell-based SARS-CoV-2 viral replication.


Subject(s)
Antiviral Agents/pharmacology , DNA Helicases/antagonists & inhibitors , Indoles/pharmacology , Phenylcarbamates/pharmacology , SARS-CoV-2/drug effects , Sulfonamides/pharmacology , Animals , COVID-19/drug therapy , Chlorocebus aethiops , Fluorescence Resonance Energy Transfer , Quantitative Structure-Activity Relationship , SARS-CoV-2/enzymology , Vero Cells , Virus Replication/drug effects
4.
ChemMedChem ; 16(22): 3418-3427, 2021 11 19.
Article in English | MEDLINE | ID: covidwho-1525425

ABSTRACT

Currently, limited therapeutic options are available for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). We have developed a set of pyrazine-based small molecules. A series of pyrazine conjugates was synthesized by microwave-assisted click chemistry and benzotriazole chemistry. All the synthesized conjugates were screened against the SAR-CoV-2 virus and their cytotoxicity was determined. Computational studies were carried out to validate the biological data. Some of the pyrazine-triazole conjugates (5 d-g) and (S)-N-(1-(benzo[d]thiazol-2-yl)-2-phenylethyl)pyrazine-2-carboxamide 12 i show significant potency against SARS-CoV-2 among the synthesized conjugates. The selectivity index (SI) of potent conjugates indicates significant efficacy compared to the reference drug (Favipiravir).


Subject(s)
Antiviral Agents/pharmacology , Pyrazines/pharmacology , SARS-CoV-2/drug effects , Amides/pharmacology , Animals , Antiviral Agents/chemical synthesis , Antiviral Agents/metabolism , Antiviral Agents/toxicity , Chlorocebus aethiops , Coronavirus RNA-Dependent RNA Polymerase/metabolism , Microbial Sensitivity Tests , Molecular Docking Simulation , Molecular Structure , Pyrazines/chemical synthesis , Pyrazines/metabolism , Pyrazines/toxicity , Quantitative Structure-Activity Relationship , Vero Cells
5.
Molecules ; 26(20)2021 Oct 14.
Article in English | MEDLINE | ID: covidwho-1470936

ABSTRACT

The SARS-CoV-2 virus is highly contagious to humans and has caused a pandemic of global proportions. Despite worldwide research efforts, efficient targeted therapies against the virus are still lacking. With the ready availability of the macromolecular structures of coronavirus and its known variants, the search for anti-SARS-CoV-2 therapeutics through in silico analysis has become a highly promising field of research. In this study, we investigate the inhibiting potentialities of triazole-based compounds against the SARS-CoV-2 main protease (Mpro). The SARS-CoV-2 main protease (Mpro) is known to play a prominent role in the processing of polyproteins that are translated from the viral RNA. Compounds were pre-screened from 171 candidates (collected from the DrugBank database). The results showed that four candidates (Bemcentinib, Bisoctrizole, PYIITM, and NIPFC) had high binding affinity values and had the potential to interrupt the main protease (Mpro) activities of the SARS-CoV-2 virus. The pharmacokinetic parameters of these candidates were assessed and through molecular dynamic (MD) simulation their stability, interaction, and conformation were analyzed. In summary, this study identified the most suitable compounds for targeting Mpro, and we recommend using these compounds as potential drug molecules against SARS-CoV-2 after follow up studies.


Subject(s)
Antiviral Agents/chemistry , Coronavirus 3C Proteases/antagonists & inhibitors , Protease Inhibitors/chemistry , SARS-CoV-2/enzymology , Triazoles/chemistry , Antiviral Agents/metabolism , Antiviral Agents/therapeutic use , Benzocycloheptenes/chemistry , Benzocycloheptenes/metabolism , Binding Sites , COVID-19/drug therapy , COVID-19/virology , Coronavirus 3C Proteases/metabolism , Databases, Chemical , Half-Life , Humans , Ligands , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/metabolism , Protease Inhibitors/therapeutic use , Protein Binding , Quantitative Structure-Activity Relationship , SARS-CoV-2/isolation & purification , Triazoles/metabolism , Triazoles/therapeutic use
7.
Molecules ; 25(20)2020 Oct 12.
Article in English | MEDLINE | ID: covidwho-1389460

ABSTRACT

Docking of over 160 aminothiourea derivatives at the SARS-CoV-2 S-protein-human ACE2 receptor interface, whose structure became available recently, has been evaluated for its complex stabilizing potency and subsequently subjected to quantitative structure-activity relationship (QSAR) analysis. The structural variety of the studied compounds, that include 3 different forms of the N-N-C(S)-N skeleton and combinations of 13 different substituents alongside the extensive length of the interface, resulted in the failure of the QSAR analysis, since different molecules were binding to different parts of the interface. Subsequently, absorption, distribution, metabolism, and excretion (ADME) analysis on all studied compounds, followed by a toxicity analysis using statistical models for selected compounds, was carried out to evaluate their potential use as lead compounds for drug design. Combined, these studies highlighted two molecules among the studied compounds, i.e., 5-(pyrrol-2-yl)-2-(2-methoxyphenylamino)-1,3,4-thiadiazole and 1-(cyclopentanoyl)-4-(3-iodophenyl)-thiosemicarbazide, as the best candidates for the development of future drugs.


Subject(s)
Antiviral Agents/pharmacology , Betacoronavirus/isolation & purification , Coronavirus Infections/drug therapy , Peptidyl-Dipeptidase A/chemistry , Pneumonia, Viral/drug therapy , Protein Interaction Domains and Motifs/drug effects , Semicarbazides/chemistry , Spike Glycoprotein, Coronavirus/chemistry , Angiotensin-Converting Enzyme 2 , Betacoronavirus/drug effects , COVID-19 , Coronavirus Infections/virology , Humans , Models, Statistical , Molecular Structure , Pandemics , Peptidyl-Dipeptidase A/metabolism , Pneumonia, Viral/virology , Protein Conformation , Quantitative Structure-Activity Relationship , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/metabolism
8.
J Mol Graph Model ; 108: 107968, 2021 11.
Article in English | MEDLINE | ID: covidwho-1373131

ABSTRACT

NF-κB is a central regulator of immunity and inflammation. It is suggested that the inflammatory response mediated by SARS-CoV-2 is predominated by NF-κB activation. Thus, NF-κB inhibition is considered a potential therapeutic strategy for COVID-19. The aim of this study was to identify potential anti-inflammation lead molecules that target NF-κB using a quantitative structure-activity relationships (QSAR) model of currently used and investigated anti-inflammatory drugs as the basis for screening. We applied an integrated approach by starting with the inflammation-based QSAR model to screen three libraries containing more than 220,000 drug-like molecules for the purpose of finding potential drugs that target the NF-κB/IκBα p50/p65 (RelA) complex. We also used QSAR models to rule out molecules that were predicted to be toxic. Among screening libraries, 382 molecules were selected as potentially nontoxic and were analyzed further by short and long molecular dynamics (MD) simulations and free energy calculations. We have discovered five hit ligands with highly predicted anti-inflammation activity and nearly no predicted toxicities which had strongly favorable protein-ligand interactions and conformational stability at the binding pocket compared to a known NF-κB inhibitor (procyanidin B2). We propose these hit molecules as potential NF-κB inhibitors which can be further investigated in pre-clinical studies against SARS-CoV-2 and may be used as a scaffold for chemical optimization and drug development efforts.


Subject(s)
COVID-19 , Quantitative Structure-Activity Relationship , Drug Discovery , Humans , Inflammation/drug therapy , NF-kappa B/metabolism , SARS-CoV-2
9.
Int J Mol Sci ; 22(15)2021 Aug 03.
Article in English | MEDLINE | ID: covidwho-1346502

ABSTRACT

Thrombosis is a life-threatening disease with a high mortality rate in many countries. Even though anti-thrombotic drugs are available, their serious side effects compel the search for safer drugs. In search of a safer anti-thrombotic drug, Quantitative Structure-Activity Relationship (QSAR) could be useful to identify crucial pharmacophoric features. The present work is based on a larger data set comprising 1121 diverse compounds to develop a QSAR model having a balance of acceptable predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The developed six parametric model fulfils the recommended values for internal and external validation along with Y-randomization parameters such as R2tr = 0.831, Q2LMO = 0.828, R2ex = 0.783. The present analysis reveals that anti-thrombotic activity is found to be correlated with concealed structural traits such as positively charged ring carbon atoms, specific combination of aromatic Nitrogen and sp2-hybridized carbon atoms, etc. Thus, the model captured reported as well as novel pharmacophoric features. The results of QSAR analysis are further vindicated by reported crystal structures of compounds with factor Xa. The analysis led to the identification of useful novel pharmacophoric features, which could be used for future optimization of lead compounds.


Subject(s)
Fibrinolytic Agents/pharmacology , Heterocyclic Compounds/pharmacology , Thrombosis/drug therapy , Fibrinolytic Agents/chemistry , Heterocyclic Compounds/chemistry , Humans , Models, Molecular , Quantitative Structure-Activity Relationship
10.
SAR QSAR Environ Res ; 32(9): 689-698, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1322544

ABSTRACT

Perhaps there is some similarity between the coronavirus of 2017 and the COVID-19. Consequently, a predictive model for the antiviral activity for the Middle East respiratory syndrome coronavirus (MERS-CoV, 2017) could be useful for designing the strategy and tactics in the struggle with coronaviruses in general and with COVID 19 in particular. Quantitative structure-activity relationships (QSARs) of inhibitory activity to MERS-CoV were developed. The index of ideality of correlation was applied to build up these models for the antiviral activity. The statistical quality of the best model is quite good (r2 = 0.84). A mechanistic interpretation of these models based on the molecular features with strong positive (i.e. promoters for endpoint increase) and strong negative (i.e. promoters for endpoint decrease) influence on the inhibitory activity is suggested. A collection of possible biologically active compounds, constructed using data on the above molecular features which are statistically reliable promoters of increase or decrease of the activity, is presented.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Monte Carlo Method , Quantitative Structure-Activity Relationship , SARS-CoV-2/drug effects , Humans
11.
Molecules ; 25(20)2020 Oct 10.
Article in English | MEDLINE | ID: covidwho-1302394

ABSTRACT

A series of 27 compounds of general structure 2,3-dihydro-benzo[1,4]oxazin-4-yl)-2-{4-[3-(1H-3indolyl)-propyl]-1-piperazinyl}-ethanamides, Series I: 7(a-o) and (2-{4-[3-(1H-3-indolyl)-propyl]-1-piperazinyl}-acetylamine)-N-(2-morfolin-4-yl-ethyl)-fluorinated benzamides Series II: 13(a-l) were synthesized and evaluated as novel multitarget ligands towards dopamine D2 receptor, serotonin transporter (SERT), and monoamine oxidase-A (MAO-A) directed to the management of major depressive disorder (MDD). All the assayed compounds showed affinity for SERT in the nanomolar range, with five of them displaying Ki values from 5 to 10 nM. Compounds 7k, Ki = 5.63 ± 0.82 nM, and 13c, Ki = 6.85 ± 0.19 nM, showed the highest potencies. The affinities for D2 ranged from micro to nanomolar, while MAO-A inhibition was more discrete. Nevertheless, compounds 7m and 7n showed affinities for the D2 receptor in the nanomolar range (7n: Ki = 307 ± 6 nM and 7m: Ki = 593 ± 62 nM). Compound 7n was the only derivative displaying comparable affinities for SERT and D2 receptor (D2/SERT ratio = 3.6) and could be considered as a multitarget lead for further optimization. In addition, docking studies aimed to rationalize the molecular interactions and binding modes of the designed compounds in the most relevant protein targets were carried out. Furthermore, in order to obtain information on the structure-activity relationship of the synthesized series, a 3-D-QSAR CoMFA and CoMSIA study was conducted and validated internally and externally (q2 = 0.625, 0.523 for CoMFA and CoMSIA and r2ncv = 0.967, 0.959 for CoMFA and CoMSIA, respectively).


Subject(s)
Biological Assay/methods , Receptors, Dopamine D2/metabolism , Serotonin Plasma Membrane Transport Proteins/metabolism , Molecular Docking Simulation , Quantitative Structure-Activity Relationship , Receptors, Dopamine D2/genetics , Serotonin Plasma Membrane Transport Proteins/genetics , Structure-Activity Relationship
12.
SAR QSAR Environ Res ; 31(7): 511-526, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-1301250

ABSTRACT

In the context of recently emerged pandemic of COVID-19, we have performed two-dimensional quantitative structure-activity relationship (2D-QSAR) modelling using SARS-CoV-3CLpro enzyme inhibitors for the development of a multiple linear regression (MLR) based model. We have used 2D descriptors with an aim to develop an easily interpretable, transferable and reproducible model which may be used for quick prediction of SAR-CoV-3CLpro inhibitory activity for query compounds in the screening process. Based on the insights obtained from the developed 2D-QSAR model, we have identified the structural features responsible for the enhancement of the inhibitory activity against 3CLpro enzyme. Moreover, we have performed the molecular docking analysis using the most and least active molecules from the dataset to understand the molecular interactions involved in binding, and the results were then correlated with the essential structural features obtained from the 2D-QSAR model. Additionally, we have performed in silico predictions of SARS-CoV 3CLpro enzyme inhibitory activity of a total of 50,437 compounds obtained from two anti-viral drug databases (CAS COVID-19 antiviral candidate compound database and another recently reported list of prioritized compounds from the ZINC15 database) using the developed model and provided prioritized compounds for experimental detection of their performance for SARS-CoV 3CLpro enzyme inhibition.


Subject(s)
Betacoronavirus/enzymology , Cysteine Endopeptidases/chemistry , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , Quantitative Structure-Activity Relationship , Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Betacoronavirus/drug effects , COVID-19 , Coronavirus Infections , Drug Design , Linear Models , Molecular Docking Simulation , Pandemics , Pneumonia, Viral , SARS-CoV-2
13.
SAR QSAR Environ Res ; 32(6): 473-493, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1236142

ABSTRACT

COVID-19 is the most unanticipated incidence of 2020 affecting the human population worldwide. Currently, it is utmost important to produce novel small molecule anti-SARS-CoV-2 drugs urgently that can save human lives globally. Based on the earlier SARS-CoV and MERS-CoV infection along with the general characters of coronaviral replication, a number of drug molecules have been proposed. However, one of the major limitations is the lack of experimental observations with different drug molecules. In this article, 70 diverse chemicals having experimental SARS-CoV-2 3CLproinhibitory activity were accounted for robust classification-based QSAR analysis statistically validated with 4 different methodologies to recognize the crucial structural features responsible for imparting the activity. Results obtained from all these methodologies supported and validated each other. Important observations obtained from these analyses were also justified with the ligand-bound crystal structure of SARS-CoV-2 3CLpro enzyme. Our results suggest that molecules should contain a 2-oxopyrrolidine scaffold as well as a methylene (hydroxy) sulphonic acid warhead in proper orientation to achieve higher inhibitory potency against SARS-CoV-2 3CLpro. Outcomes of our study may be able to design and discover highly effective SARS-CoV-2 3CLpro inhibitors as potential anticoronaviral therapy to crusade against COVID-19.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Coronavirus 3C Proteases/antagonists & inhibitors , Protease Inhibitors/pharmacology , SARS-CoV-2/drug effects , Coronavirus 3C Proteases/chemistry , Drug Design , Drug Discovery , Models, Molecular , Protease Inhibitors/chemistry , Quantitative Structure-Activity Relationship , SARS-CoV-2/enzymology
14.
Ecotoxicol Environ Saf ; 219: 112357, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1233412

ABSTRACT

The coronavirus disease-19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is rampant in the world and is a serious threat to global health. The SARS-CoV-2 RNA has been detected in various environmental media, which speeds up the pace of the virus becoming a global biological pollutant. Because many engineered nanomaterials (ENMs) are capable of inducing anti-microbial activity, ENMs provide excellent solutions to overcome the virus pandemic, for instance by application as protective coatings, biosensors, or nano-agents. To tackle some mechanistic issues related to the impact of ENMs on SARS-CoV-2, we investigated the molecular interactions between carbon nanoparticles (CNPs) and a SARS-CoV-2 RNA fragment (i.e., a model molecule of frameshift stimulation element from the SARS-CoV-2 RNA genome) using molecular mechanics simulations. The interaction affinity between the CNPs and the SARS-CoV-2 RNA fragment increased in the order of fullerenes < graphenes < carbon nanotubes. Furthermore, we developed quantitative structure-activity relationship (QSAR) models to describe the interactions of 17 different types of CNPs from three dimensions with the SARS-CoV-2 RNA fragment. The QSAR models on the interaction energies of CNPs with the SARS-CoV-2 RNA fragment show high goodness-of-fit and robustness. Molecular weight, surface area, and the sum of degrees of every carbon atom were found to be the primary structural descriptors of CNPs determining the interactions. Our research not only offers a theoretical insight into the adsorption/separation and inactivation of SARS-CoV-2, but also allows to design novel ENMs which act efficiently on the genetic material RNA of SARS-CoV-2. This contributes to minimizing the challenge of time-consuming and labor-intensive virus experiments under high risk of infection, whilst meeting our precautionary demand for options to handle any new versions of the coronavirus that might emerge in the future.


Subject(s)
Carbon/chemistry , Nanoparticles/chemistry , RNA, Viral/chemistry , SARS-CoV-2 , Models, Chemical , Nucleic Acid Conformation , Quantitative Structure-Activity Relationship
15.
Comput Biol Med ; 134: 104483, 2021 07.
Article in English | MEDLINE | ID: covidwho-1224673

ABSTRACT

The search for effective treatment against novel coronavirus (COVID-19) remains a global challenge due to controversies on available vaccines. In this study, data of SARS coronavirus 3C-like protease (3CLpro) inhibitors; a key drug target in the coronavirus genome was retrieved from CHEMBL database. Quantitative Structure-Activity Relationship (QSAR) studies, Molecular docking, Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) and molecular dynamics simulation (MDS) were carried out using these 3CLpro inhibitors. QSAR model constructed using the data had correlation coefficient R2 value of 0.907; cross-validated correlation coefficient Q2 value of 0.866 and test set predicted correlation coefficient R2pred value of 0.517. Variance inflation factor (VIF) values for descriptors contained in the model ranged from 1.352 to 1.68, hence, these descriptors were orthogonal to one another. Therefore, the model was statistically significant and can be used to screen and design new molecules for their inhibitory activity against 3CLpro. Molecular docking showed that seven of the compounds (inhibitors) used in the study had a remarkable binding affinity (-9.2 to -10.3 kcal/mol) for 3CLpro. ADMET study revealed that five (CHEMBL Accession IDs 19438, 196635, 377150, 208763, and 210097) of the seven compounds with good binding ability obeyed Lipinski's rule of five. Hence, they were compounds with drug-like properties. MDS analysis revealed that 3CLpro-compound 21, 3CLpro-compound 22, 3CLpro-compound 40 complexes are very stable as compared to the reference 3CLpro-X77 complex. Therefore, this study identified three potent inhibitors of 3CLpro viz. CHEMBL194398, CHEMBL196635, and CHEMBL210097 that can be further explored for the treatment of COVID-19.


Subject(s)
COVID-19 , SARS Virus , Antiviral Agents , Humans , Molecular Docking Simulation , Protease Inhibitors/pharmacology , Quantitative Structure-Activity Relationship , SARS-CoV-2
16.
Molecules ; 26(6)2021 Mar 11.
Article in English | MEDLINE | ID: covidwho-1190434

ABSTRACT

Considering the urgency of the COVID-19 pandemic, we developed a receptor-based pharmacophore model for identifying FDA-approved drugs and hits from natural products. The COVID-19 main protease (Mpro) was selected for the development of the pharmacophore model. The model consisted of a hydrogen bond acceptor, donor, and hydrophobic features. These features demonstrated good corroboration with a previously reported model that was used to validate the present model, showing an RMSD value of 0.32. The virtual screening was carried out using the ZINC database. A set of 208,000 hits was extracted and filtered using the ligand pharmacophore mapping, applying the lead-like properties. Lipinski's filter and the fit value filter were used to minimize hits to the top 2000. Simultaneous docking was carried out for 200 hits for natural drugs belonging to the FDA-approved drug database. The top 28 hits from these experiments, with promising predicted pharmacodynamic and pharmacokinetic properties, are reported here. To optimize these hits as Mpro inhibitors and potential treatment options for COVID-19, bench work investigations are needed.


Subject(s)
Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Biological Products/chemistry , Biological Products/pharmacology , COVID-19/drug therapy , Receptors, Drug/metabolism , Binding Sites , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/chemistry , Coronavirus 3C Proteases/metabolism , Databases, Pharmaceutical , Drug Discovery , Humans , Hydrogen Bonding , Hydrophobic and Hydrophilic Interactions , Ligands , Molecular Docking Simulation , Molecular Dynamics Simulation , Protein Binding , Quantitative Structure-Activity Relationship
17.
Int J Mol Sci ; 22(8)2021 Apr 12.
Article in English | MEDLINE | ID: covidwho-1178287

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes the papain-like protease (PLpro). The protein not only plays an essential role in viral replication but also cleaves ubiquitin and ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from host proteins, making it an important target for developing new antiviral drugs. In this study, we searched for novel, noncovalent potential PLpro inhibitors by employing a multistep in silico screening of a 15 million compound library. The selectivity of the best-scored compounds was evaluated by checking their binding affinity to the human ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), which, as a deubiquitylating enzyme, exhibits structural and functional similarities to the PLpro. As a result, we identified 387 potential, selective PLpro inhibitors, from which we retrieved the 20 best compounds according to their IC50 values toward PLpro estimated by a multiple linear regression model. The selected candidates display potential activity against the protein with IC50 values in the nanomolar range from approximately 159 to 505 nM and mostly adopt a similar binding mode to the known, noncovalent SARS-CoV-2 PLpro inhibitors. We further propose the six most promising compounds for future in vitro evaluation. The results for the top potential PLpro inhibitors are deposited in the database prepared to facilitate research on anti-SARS-CoV-2 drugs.


Subject(s)
Antiviral Agents/chemistry , Antiviral Agents/metabolism , Coronavirus Papain-Like Proteases/antagonists & inhibitors , Protease Inhibitors/chemistry , Protease Inhibitors/metabolism , SARS-CoV-2/enzymology , Animals , Antiviral Agents/toxicity , Computer Simulation , Crystallography, X-Ray , Databases, Chemical , Databases, Protein , Drug Evaluation, Preclinical , Humans , Inhibitory Concentration 50 , Lethal Dose 50 , Ligands , Mutagenicity Tests , Protease Inhibitors/toxicity , Quantitative Structure-Activity Relationship , Rats , Ubiquitin Thiolesterase/chemistry , Ubiquitin Thiolesterase/metabolism
18.
Arch Pharm (Weinheim) ; 354(4): e2000378, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1162498

ABSTRACT

Many diseases as well as acute conditions can lead to fatigue, which can be either temporary or chronic in nature. Acute fatigue develops frequently after physical exercise or after alcohol hangover, whereas microbial infections such as influenza or COVID-19 and chronic diseases like Parkinson's disease or multiple sclerosis are often associated with chronic fatigue. Oxidative stress and a resulting disturbance of mitochondrial function are likely to be common denominators for many forms of fatigue, and antioxidant treatments have been shown to be effective in alleviating the symptoms of fatigue. In this study, we review the role of reactive oxygen and nitrogen species in fatigue and the antioxidant effects of the intake of molecular hydrogen. We propose that molecular hydrogen is well suited for the treatment of temporary and chronic forms of oxidative stress-associated fatigue.


Subject(s)
COVID-19 , Fatigue , Hydrogen , Oxidative Stress , Antioxidants/metabolism , Antioxidants/pharmacology , COVID-19/metabolism , COVID-19/physiopathology , Fatigue/etiology , Fatigue/metabolism , Fatigue/therapy , Humans , Hydrogen/metabolism , Hydrogen/pharmacology , Nitrogen , Oxidative Stress/drug effects , Oxidative Stress/physiology , Quantitative Structure-Activity Relationship , Reactive Oxygen Species , SARS-CoV-2
19.
J Chem Inf Model ; 61(4): 2016-2025, 2021 04 26.
Article in English | MEDLINE | ID: covidwho-1139703

ABSTRACT

The global pandemic caused by the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening the health and economic systems worldwide. Despite the enormous efforts of scientists and clinicians around the world, there is still no drug or vaccine available worldwide for the treatment and prevention of the infection. A rapid strategy for the identification of new treatments is based on repurposing existing clinically approved drugs that show antiviral activity against SARS-CoV-2 infection. In this study, after developing a quantitative structure activity relationship analysis based on molecular topology, several macrolide antibiotics are identified as promising SARS-CoV-2 spike protein inhibitors. To confirm the in silico results, the best candidates were tested against two human coronaviruses (i.e., 229E-GFP and SARS-CoV-2) in cell culture. Time-of-addition experiments and a surrogate model of viral cell entry were used to identify the steps in the virus life cycle inhibited by the compounds. Infection experiments demonstrated that azithromycin, clarithromycin, and lexithromycin reduce the intracellular accumulation of viral RNA and virus spread as well as prevent virus-induced cell death, by inhibiting the SARS-CoV-2 entry into cells. Even though the three macrolide antibiotics display a narrow antiviral activity window against SARS-CoV-2, it may be of interest to further investigate their effect on the viral spike protein and their potential in combination therapies for the coronavirus disease 19 early stage of infection.


Subject(s)
COVID-19 , Pharmaceutical Preparations , Anti-Bacterial Agents , Antiviral Agents/pharmacology , Humans , Macrolides/pharmacology , Quantitative Structure-Activity Relationship , SARS-CoV-2 , Spike Glycoprotein, Coronavirus
20.
Molecules ; 26(4)2021 Feb 10.
Article in English | MEDLINE | ID: covidwho-1110462

ABSTRACT

Currently, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has infected people among all countries and is a pandemic as declared by the World Health Organization (WHO). SARS-CoVID-2 main protease is one of the therapeutic drug targets that has been shown to reduce virus replication, and its high-resolution 3D structures in complex with inhibitors have been solved. Previously, we had demonstrated the potential of natural compounds such as serine protease inhibitors eventually leading us to hypothesize that FDA-approved marine drugs have the potential to inhibit the biological activity of SARS-CoV-2 main protease. Initially, field-template and structure-activity atlas models were constructed to understand and explain the molecular features responsible for SARS-CoVID-2 main protease inhibitors, which revealed that Eribulin Mesylate, Plitidepsin, and Trabectedin possess similar characteristics related to SARS-CoVID-2 main protease inhibitors. Later, protein-ligand interactions are studied using ensemble molecular-docking simulations that revealed that marine drugs bind at the active site of the main protease. The three-dimensional reference interaction site model (3D-RISM) studies show that marine drugs displace water molecules at the active site, and interactions observed are favorable. These computational studies eventually paved an interest in further in vitro studies. Finally, these findings are new and indeed provide insights into the role of FDA-approved marine drugs, which are already in clinical use for cancer treatment as a potential alternative to prevent and treat infected people with SARS-CoV-2.


Subject(s)
Peptide Hydrolases/chemistry , Peptide Hydrolases/metabolism , SARS-CoV-2/physiology , Serine Proteinase Inhibitors/pharmacology , Catalytic Domain , Depsipeptides/chemistry , Depsipeptides/pharmacology , Drug Repositioning , Furans/chemistry , Furans/pharmacology , Humans , Ketones/chemistry , Ketones/pharmacology , Models, Molecular , Molecular Docking Simulation , Peptides, Cyclic , Quantitative Structure-Activity Relationship , SARS-CoV-2/drug effects , Serine Proteinase Inhibitors/chemistry , Trabectedin/chemistry , Trabectedin/pharmacology , Viral Proteins/antagonists & inhibitors , Virus Replication/drug effects
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