Binding ability of arginine, citrulline, N-acetyl citrulline and thiocitrulline with SARS COV-2 main protease using molecular docking studies.
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ABSTRACT:
SUBMITTER: Thimmasandra Narayan R
PROVIDER: S-EPMC8021929 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A novel coronavirus responsible of acute respiratory infection closely related to SARS-CoV has recently emerged. So far there is no consensus for drug treatment to stop the spread of the virus. Discovery of a drug that would limit the virus expansion is one of the biggest challenges faced by the humanity in the last decades. In this perspective, to test existing drugs as inhibitors of SARS-CoV-2 main protease is a good approach. Among natural phenolic compounds found in plants, fruit, and vegetables; flavonoids are the most abundant. Flavonoids, especially in their glycosylated forms, display a number of physiological activities, which makes them interesting to investigate as antiviral molecules. The flavonoids chemical structures were downloaded from PubChem and protease structure 6LU7 was from the Protein Data Bank site. Molecular docking study was performed using AutoDock Vina. Among the tested molecules Quercetin-3-O-rhamnoside showed the highest binding affinity (-9,7 kcal/mol). Docking studies showed that glycosylated flavonoids are good inhibitors for the SARS-CoV-2 protease and could be further investigated by in vitro and in vivo experiments for further validation. MD simulations were further performed to evaluate the dynamic behavior and stability of the protein in complex with the three best hits of docking experiments. Our results indicate that the rutin is a potential drug to inhibit the function of Chymotrypsin-like protease (3CL pro) of Coronavirus.
| S-EPMC7561147 | biostudies-literature
Project description:Background and aimThe discovery of drugs capable of inhibiting SARS-CoV-2 is a priority for human beings due to the severity of the global health pandemic caused by COVID-19. To this end, natural products can provide therapeutic alternatives that could be employed as an effective safe treatment for COVID-19.Experimental procedureTwelve compounds were isolated from the aerial parts of C. officinalis L. and investigated for their inhibitory activities against SARS-CoV-2 Mpro compared to its co-crystallized N3 inhibitor using molecular docking studies. Furthermore, a 100 ns MD simulation was performed for the most active two promising compounds, Calendulaglycoside A (SAP5) and Osteosaponin-I (SAP8).Results and conclusionAt first, molecular docking studies showed interesting binding scores as compared to the N3 inhibitor. Calendulaglycoside A (SAP5) achieved a superior binding than the co-crystallized inhibitor indicating promising affinity and intrinsic activity towards the Mpro of SARS-CoV-2 as well. Moreover, findings illustrated preferential stability for SAP5 within the Mpro pocket over that of N3 beyond the 40 ns MD simulation course. Structural preferentiality for triterpene-Mpro binding highlights the significant role of 17β-glucosyl and carboxylic 3α-galactosyl I moieties through high electrostatic interactions across the MD simulation trajectories. Furthermore, this study clarified a promising SAR responsible for the antiviral activity against the SARS-CoV-2 Mpro and the design of new drug candidates targeting it as well. The above findings could be promising for fast examining the previously isolated triterpenes both pre-clinically and clinically for the treatment of COVID-19.
| S-EPMC8126476 | biostudies-literature
Project description:In this paper we investigate 10 different HIV protease inhibitors (HPIs) as possible repurposed-drugs candidates against SARS-CoV-2. To this end, we execute molecular docking and molecular dynamics simulations. The in silico data demonstrated that, despite their molecular differences, all HPIs presented a similar behavior for the parameters analyzed, with the exception of Nelfinavir that showed better results for most of the molecular dynamics parameters in comparison with the N3 inhibitor.
| S-EPMC7443253 | biostudies-literature
Project description:BackgroundDue to the migratory flow of infected people with severe acute respiratory syndrome virus (SARS COV-2), the number of confirmed cases of coronavirus disease 2019 (COVID-19) is accelerating globally; preclinical evidence of antiviral agents that can combat this pandemic is still elusive. We identified published articles on SARS-COV efficacy experiments in which some selected compounds were used to test the reduction of the virus load in mice.MethodsA systematic search of articles was conducted in PubMed, Web of Science, and Scopus. We then developed a combined model based on a systematic review, meta-analyses, and molecular docking studies to evaluate the effect size of preclinical studies of compounds that have been tested against SARS-COV. Because substantial heterogeneity was expected, random effect model meta-analyses were carried out to estimate the overall pooled disease's prevalence. All meta-analyses were performed with Stata version 15.0. Subgroup analyses on therapies were conducted as well. Molecular docking studies of the inhibitors in the active pocket of COVID-19 protease were also performed.ResultsFrom all screened articles, six studies were appropriate for ultimate meta-analysis and systematic review. The residual amount of heterogeneity was high (τ2 =0.02; heterogeneity I2 =85.5 % with heterogeneity chi-square =103.57, a degree of freedom =15, and p <0.001). The overall random pooled prevalence of infected mice treated with the selected compounds was 78.1 % [95 % Confidence Interval (CI): 14.7-17.0 %]. Prophylactic has a significantly higher pooled prevalence than therapeutic, with 21.8 % (95 % CI: 16.4 % to 28.8 %). Our results indicated that most of the SARS-COV inhibitors analyzed were less effective in reducing the lung virus titer of SARS-COV infection in animal models. The findings from molecular docking studies also identified COVID-19 inhibitors that are good for optimization and drug development to fight against COVID-19 infection.ConclusionsFindings from the review showed that studies on the preclinical compounds targeting SARS-COV and COVID-19 are limited. Furthermore, molecular docking studies and meta-analysis results substantiated three compounds, i.e., EIDD-2801, GS-5734, and amodiaquine. HIPPOKRATIA 2020, 24(3): 99-106.
| S-EPMC8256780 | biostudies-literature
Project description:We have used bioinformatics to identify drugs for the treatment of COVID-19, using drugs already being tested for the treatment as benchmarks like Remdesivir and Chloroquine. Our findings provide further support for drugs that are already being explored as therapeutic agents for the treatment of COVID-19 and identify promising new targets that merit further investigation. In addition, the epoxidation of Parthenolide 1 using peracids, has been scrutinized within the MEDT at the B3LYP/6-311(d,p) computational level. DFT results showed a high chemoselectivity on the double bond C3[bond, double bond]C4, in full agreement with the experimental outcomes. ELF analysis demonstrated that epoxidation reaction took place through a one-step mechanism, in which the formation of the two new C-O single bonds is somewhat asynchronous.
| S-EPMC8133493 | biostudies-literature
Project description:Main protease (Mpro) plays a key role in replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study was designed for finding natural inhibitors of SARS-CoV-2 Mpro by in silico methods. To this end, the co-crystal structure of Mpro with telaprevir was explored and receptor-ligand pharmacophore models were developed and validated using pharmit. The database of "ZINC Natural Products" was screened, and 288 compounds were filtered according to pharmacophore features. In the next step, Lipinski's rule of five was applied and absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the filtered compounds were calculated using in silico methods. The resulted 15 compounds were docked into the active site of Mpro and those with the highest binding scores and better interaction including ZINC61991204, ZINC67910260, ZINC61991203, and ZINC08790293 were selected. Further analysis by molecular dynamic simulation studies showed that ZINC61991203 and ZINC08790293 dissociated from Mpro active site, while ZINC426421106 and ZINC5481346 were stable. Root mean square deviation (RMSD), radius of gyration (Rg), number of hydrogen bonds between ligand and protein during the time of simulation, and root mean square fluctuations (RMSF) of protein and ligands were calculated, and components of binding free energy were calculated using the molecular mechanic/Poisson-Boltzmann surface area (MM/PBSA) method. The result of all the analysis indicated that ZINC61991204 and ZINC67910260 are drug-like and nontoxic and have a high potential for inhibiting Mpro.
| S-EPMC9420677 | biostudies-literature
Project description:Background: Severe acute respiratory syndrome coronavirus (SARS-CoVs) have emerged as a global health threat, which had caused a high rate of mortality. There is an urgent need to find effective drugs against these viruses. Objective: This study aims to predict the activity of unsymmetrical aromatic disulfides by constructing a QSAR model, and to design new compounds according to the structural and physicochemical attributes responsible for higher activity towards SARS-CoVs main protease. Methods: All molecules were constructed in ChemOffice software and molecular descriptors were calculated by CODESSA software. A regression-based linear heuristic method was established by changing descriptors datasets and calculating predicted IC50 values of compounds. Then, some new compounds were designed according to molecular descriptors from the heuristic method model. The compounds with predicted values smaller than a set point were constantly screened out. Finally, the properties analysis and molecular docking were conducted to further understand the structure-activity relationships of these finalized compounds. Results: The heuristic method explored the various descriptors responsible for bioactivity and gained the best linear model with R2 0.87. The success of the model fully passed the testing set validation, proving that the model has both high statistical significance and excellent predictive ability. A total of 5 compounds with ideal predicted IC50 were found from the 96 newly designed derivatives and their properties analyze was carried out. Molecular docking experiments were conducted for the optimal compound 31a, which has the best compound activity with good target protein binding capability. Conclusion: The heuristic method was quite reliable for predicting IC50 values of unsymmetrical aromatic disulfides. The present research provides meaningful guidance for further exploration of the highly active inhibitors for SARS-CoVs.
| S-EPMC10230167 | biostudies-literature
Project description:The current novel corona virus illness (COVID-19) is a developing viral disease that was discovered in 2019. There is currently no viable therapeutic strategy for this illness management. Because traditional medication development and discovery has lagged behind the threat of emerging and re-emerging illnesses like Ebola, MERS-CoV, and, more recently, SARS-CoV-2. Drug developers began to consider drug repurposing (or repositioning) as a viable option to the more traditional drug development method. The goal of drug repurposing is to uncover new uses for an approved or investigational medicine that aren't related to its original use. The main benefits of this strategy are that there is less developmental risk and that it takes less time because the safety and pharmacologic requirements are met. The main protease (Mpro) of corona viruses is one of the well-studied and appealing therapeutic targets. As a result, the current research examines the molecular docking of Mpro (PDB ID: 5R81) conjugated repurposed drugs. 12,432 approved drugs were collected from ChEMBL and drugbank libraries, and docked separately into the receptor grid created on 5R81, using the three phases of molecular docking including high throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP). Based on docking scores and MM-GBSA binding free energy calculation, top three drugs (kanamycin, sulfinalol and carvedilol) were chosen for further analyses for molecular dynamic simulations. Graphical abstract Image 1
| S-EPMC8801302 | biostudies-literature
Project description:During almost all 2020, coronavirus disease 2019 (COVID-19) pandemic has constituted the major risk for the worldwide health and economy, propelling unprecedented efforts to discover drugs for its prevention and cure. At the end of the year, these efforts have culminated with the approval of vaccines by the American Food and Drug Administration (FDA) and the European Medicines Agency (EMA) giving new hope for the future. On the other hand, clinical data underscore the urgent need for effective drugs to treat COVID-19 patients. In this work, we embarked on a virtual screening campaign against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Mpro chymotrypsin-like cysteine protease employing our in-house database of peptide and non-peptide ligands characterized by different types of warheads acting as Michael acceptors. To this end, we employed the AutoDock4 docking software customized to predict the formation of a covalent adduct with the target protein. In vitro verification of the inhibition properties of the most promising candidates allowed us to identify two new lead inhibitors that will deserve further optimization. From the computational point of view, this work demonstrates the predictive power of AutoDock4 and suggests its application for the in silico screening of large chemical libraries of potential covalent binders against the SARS-CoV-2 Mpro enzyme.
| S-EPMC8029447 | biostudies-literature
Project description:The identification of chemotherapeutic drugs against Novel Coronavirus (2019-nCoV) is a significant requirement due to the rapid rise in deaths due to Corona Viral Infection all around the world. Therefore, it is of interest to document the molecular docking analysis data of 32 N-substituted Oseltamivir derivatives inhibitors of influenza virus H5N1 with the Novel Coronavirus main protease (2019-nCoV). We describe the optimal binding features of Oseltamivir derivatives with the SARS-Cov-2 main protease (Code PDB: 6LU7) for further consideration.
| S-EPMC7434956 | biostudies-literature