Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Virtual Screening of Peptides with High Affinity for SARS-CoV-2 Main Protease

ABSTRACT: The current pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 2,000,000 deaths worldwide. Currently, vaccine development and drug repurposing have been the main strategies. However, the development of new drugs could be the solution if the main strategies fail. Here, a virtual screening of pentapeptides was applied in order to identify peptides with high affinity to SARS-CoV-2 main protease (Mpro). Over 70,000 peptides were screened employing a genetic algorithm that uses a docking score as the fitness value. The algorithm was coupled with a RESTful API to persist data and avoid redundancy. The docking exhaustiveness was adapted to the number of peptides in each virtual screening step, where the higher the number of peptides, the lower the exhaustiveness. Two potential peptides were selected (HHYWH and HYWWT), which have higher affinity to Mpro than to human proteases. Albeit preliminary, the data presented here provide some basis for the rational design of peptide-based drugs to treat COVID-19.

SUBMITTER: Porto W

PROVIDER: S-EPMC8018786 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Identification of promising high-affinity inhibitors of SARS-CoV-2 main protease from African Natural Products Databases by Virtual Screening.

Project description:With the rapid spread of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen agent of COVID-19 pandemic created a serious threat to global public health, requiring the most urgent research for potential therapeutic agents. The availability of genomic data of SARS-CoV-2 and efforts to determine the protein structure of the virus facilitated the identification of potent inhibitors by using structure-based approach and bioinformatics tools. Many pharmaceuticals have been proposed for the treatment of COVID-19, although their effectiveness has not been assessed yet. However, it is important to find out new-targeted drugs to overcome the resistance concern. Several viral proteins such as proteases, polymerases or structural proteins have been considered as potential therapeutic targets. But the virus target must be essential for host invasion match some drugability criterion. In this Work, we selected the highly validated pharmacological target main protease Mpro and we performed high throughput virtual screening of African Natural Products Databases such as NANPDB, EANPDB, AfroDb, and SANCDB to identify the most potent inhibitors with the best pharmacological properties. In total, 8753 natural compounds were virtually screened by AutoDock vina against the main protease of SARS-CoV-2. Two hundred and five (205) compounds showed high-affinity scores (less than - 10.0 Kcal/mol), while fifty-eight (58) filtered through Lipinski's rules showed better affinity than known Mpro inhibitors (i.e., ABBV-744, Onalespib, Daunorubicin, Alpha-ketoamide, Perampanel, Carprefen, Celecoxib, Alprazolam, Trovafloxacin, Sarafloxacin, Ethyl biscoumacetate…). Those promising compounds could be considered for further investigations toward the developpement of SARS-CoV-2 drug development.

| S-EPMC10055610 | biostudies-literature

Identification of high affinity and low molecular alternatives of boceprevir against SARS-CoV-2 main protease: A virtual screening approach.

Project description:SARS-CoV-2 has posed global challenge for healthcare due to COVID-19. The main protease (Mpro) of this virus is considered as a major target for drug development efforts. In this work, we have used virtual screening approach with molecular dynamics simulations to identify high affinity and low molecular weight alternatives of boceprevir, a repurposed drug currently being evaluated against Mpro. Out of 180 compounds screened, two boceprevir analogs (PubChem ID: 57841991 and 58606278) were reported as potential alternatives with comparable predicted protease inhibitor potential and pharmacological properties. Further experimental validation of the reported compounds may contribute to the ongoing investigation of boceprevir.

| S-EPMC7892318 | biostudies-literature

Virtual Screening for SARS-CoV-2 Main Protease Inhibitory Peptides from the Putative Hydrolyzed Peptidome of Rice Bran.

Project description:The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the loss of life and has affected the life quality, economy, and lifestyle. The SARS-CoV-2 main protease (Mpro), which hydrolyzes the polyprotein, is an interesting antiviral target to inhibit the spreading mechanism of COVID-19. Through predictive digestion, the peptidomes of the four major proteins in rice bran, albumin, glutelin, globulin, and prolamin, with three protease enzymes (pepsin, trypsin, and chymotrypsin), the putative hydrolyzed peptidome was established and used as the input dataset. Then, the prediction of the antiviral peptides (AVPs) was performed by online bioinformatics tools, i.e., AVPpred, Meta-iAVP, AMPfun, and ENNAVIA programs. The amino acid composition and cytotoxicity of candidate AVPs were analyzed by COPid and ToxinPred, respectively. The ten top-ranked antiviral peptides were selected and docked to the SARS-CoV-2 main protease using GalaxyPepDock. Only the top docking scored candidate (AVP4) was further analyzed by molecular dynamics simulation for one nanosecond. According to the bioinformatic analysis results, the candidate SARS-CoV-2 main protease inhibitory peptides were 7-33 amino acid residues and formed hydrogen bonds at Thr22-24, Glu154, and Thr178 in domain 2 with short bonding distances. In addition, these top-ten candidate bioactive peptides contain hydrophilic amino acid residues and have a positive net charge. We hope that this study will provide a potential starting point for peptide-based therapeutic agents against COVID-19.

| S-EPMC9598432 | biostudies-literature

Virtual screening of approved drugs as potential SARS-CoV-2 main protease inhibitors.

Project description:The global emergency caused by COVID-19 makes the discovery of drugs capable of inhibiting SARS-CoV-2 a priority, to reduce the mortality and morbidity of this disease. Repurposing approved drugs can provide therapeutic alternatives that promise rapid and ample coverage because they have a documented safety record, as well as infrastructure for large-scale production. The main protease of SARS-CoV-2 (Mpro) is an excellent therapeutic target because it is critical for viral replication; however, Mpro has a highly flexible active site that must be considered when performing computer-assisted drug discovery. In this work, potential inhibitors of the main protease (Mpro) of SARS-Cov-2 were identified through a docking-assisted virtual screening procedure. A total of 4384 drugs, all approved for human use, were screened against three conformers of Mpro. The ligands were further studied through molecular dynamics simulations and binding free energy analysis. A total of nine currently approved molecules are proposed as potential inhibitors of SARS-CoV-2. These molecules can be further tested to speed the development of therapeutics against COVID-19.

| S-EPMC7316061 | biostudies-literature

Identification of repurposing therapeutics toward SARS-CoV-2 main protease by virtual screening.

Project description:SARS-CoV-2 causes the current global pandemic coronavirus disease 2019. Widely-available effective drugs could be a critical factor in halting the pandemic. The main protease (3CLpro) plays a vital role in viral replication; therefore, it is of great interest to find inhibitors for this enzyme. We applied the combination of virtual screening based on molecular docking derived from the crystal structure of the peptidomimetic inhibitors (N3, 13b, and 11a), and experimental verification revealed FDA-approved drugs that could inhibit the 3CLpro of SARS-CoV-2. Three drugs were selected using the binding energy criteria and subsequently performed the 3CLpro inhibition by enzyme-based assay. In addition, six common drugs were also chosen to study the 3CLpro inhibition. Among these compounds, lapatinib showed high efficiency of 3CLpro inhibition (IC50 value of 35 ± 1 μM and Ki of 23 ± 1 μM). The binding behavior of lapatinib against 3CLpro was elucidated by molecular dynamics simulations. This drug could well bind with 3CLpro residues in the five subsites S1', S1, S2, S3, and S4. Moreover, lapatinib's key chemical pharmacophore features toward SAR-CoV-2 3CLpro shared important HBD and HBA with potent peptidomimetic inhibitors. The rational design of lapatinib was subsequently carried out using the obtained results. Our discovery provides an effective repurposed drug and its newly designed analogs to inhibit SARS-CoV-2 3CLpro.

| S-EPMC9246117 | biostudies-literature

Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening.

Project description:Background: Conserved domains within SARS-CoV-2 nonstructural proteins represent key targets for the design of novel inhibitors. Methods: The authors aimed to identify potential SARS-CoV-2 NSP5 inhibitors using the ZINC database along with structure-based virtual screening and molecular dynamics simulation. Results: Of 13,840 compounds, 353 with robust docking scores were initially chosen, of which ten hit compounds were selected as candidates for detailed analyses. Three compounds were selected as coronavirus NSP5 inhibitors after passing absorption, distribution, metabolism, excretion and toxicity study; root and mean square deviation; and radius of gyration calculations. Conclusion: ZINC000049899562, ZINC000169336666 and ZINC000095542577 are potential NSP5 protease inhibitors that warrant further experimental studies.

| S-EPMC8612299 | biostudies-literature

High Throughput Virtual Screening to Discover Inhibitors of the Main Protease of the Coronavirus SARS-CoV-2.

Project description:We use state-of-the-art computer-aided drug design (CADD) techniques to identify prospective inhibitors of the main protease enzyme, 3CLpro of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19. From our screening of over one million compounds including approved drugs, investigational drugs, natural products, and organic compounds, and a rescreening protocol incorporating enzyme dynamics via ensemble docking, we have been able to identify a range of prospective 3CLpro inhibitors. Importantly, some of the identified compounds had previously been reported to exhibit inhibitory activities against the 3CLpro enzyme of the closely related SARS-CoV virus. The top-ranking compounds are characterized by the presence of multiple bi- and monocyclic rings, many of them being heterocycles and aromatic, which are flexibly linked allowing the ligands to adapt to the geometry of the 3CLpro substrate site and involve a high amount of functional groups enabling hydrogen bond formation with surrounding amino acid residues, including the catalytic dyad residues H41 and C145. Among the top binding compounds we identified several tyrosine kinase inhibitors, which include a bioflavonoid, the group of natural products that binds best to 3CLpro. Another class of compounds that decently binds to the SARS-CoV-2 main protease are steroid hormones, which thus may be endogenous inhibitors and might provide an explanation for the age-dependent severity of COVID-19. Many of the compounds identified by our work show a considerably stronger binding than found for reference compounds with in vitro demonstrated 3CLpro inhibition and anticoronavirus activity. The compounds determined in this work thus represent a good starting point for the design of inhibitors of SARS-CoV-2 replication.

| S-EPMC7396980 | biostudies-literature

Fenoterol and dobutamine as SARS-CoV-2 main protease inhibitors: A virtual screening study.

Project description:Global health is under heavy threat by a worldwide pandemic caused by a new type of coronavirus (COVID-19) since its rapid spread in China in 2019 [1]. Currently, there are no approved specific drugs and effective treatment for COVID-19 infection, but several available drugs are known to facilitate tentative treatment. Since drug design, development and testing procedures are time-consuming [2], [1], [2], [3], virtual screening studies with the aid of available drug databases take the initiative at this point and save the time. Besides, drug repurposing strategies promises to identify new agents for the novel diseases in a time-critical fashion. In this study, we used structure based virtual screening method on FDA approved drugs and compounds in clinical trials. As a result of this study we choose three most prominent compounds for further studies. Here we show that these three compounds (dobutamine and its two derivatives) can be considered as promising inhibitors for SARS-CoV-2 main protease and results also demonstrate the possible interactions of dobutamine and its derivatives with SARS-CoV-2 main protease (6W63) [6]. Our efforts in this work directly address current urgency of a new drug discovery against COVID-19.

| S-EPMC7550866 | biostudies-literature

Virtual screening for small molecular non-covalent binders of the SARS-CoV-2 main protease.

Project description: Not available

| S-EPMC8130460 | biostudies-literature

Lead Discovery of SARS-CoV-2 Main Protease Inhibitors through Covalent Docking-Based Virtual Screening.

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

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data