Docking Program Research Articles

Binding free energy predictions in host-guest systems using Autodock4. A retrospective analysis on SAMPL6, SAMPL7 and SAMPL8 challenges

We systematically tested the Autodock4 docking program for absolute binding free energy predictions using the host-guest systems from the recent SAMPL6, SAMPL7 and SAMPL8 challenges. We found that Autodock4 behaves surprisingly well, outperforming in many instances expensive molecular dynamics or quantum chemistry techniques, with an extremely favorable benefit-cost ratio. Some interesting features of Autodock4 predictions are revealed, yielding valuable hints on the overall reliability of docking screening campaigns in drug discovery projects.

A Review on Molecular Docking

Molecular docking is computational modeling of structure complexes formed by two or more interacting molecule. The goal of molecular docking is prediction of three dimensional structure of interest. Molecular docking software mostly used in drug improvement. Molecules and effortless entrance to structural databases has befallen essential mechanism. Molecular Docking provide a collection of expensive tools for drug design and analysis. Simple prophecy of molecules and easy way in to structural databases has become essential components on the desktop of the medicinal chemist. The most important application of molecular docking is virtual screening. A variety of docking programs were residential to imagine the three dimensional structure of the molecule and docking gain can also be analyze with the assist of dissimilar computational methods. Molecular docking is a key tool in structural molecular biology and computer-assist drug design. Docking can be worn to execute virtual screening on large libraries of compounds, rank the results, and suggest structural hypotheses of how the ligands reduce the target, which is precious in lead optimization.

Improving virtual screening results with MM/GBSA and MM/PBSA rescoring.

Virtual screening (VS) based on molecular docking is one of the most useful methods in computer-aided drug design. By allowing to identify computationally putative ligands binding to the proteins of interest, VS dramatically reduces the time and expense of the development of novel therapeutics. Among the limitations of the VS approaches is the low accuracy of scoring functions implemented in docking methods for assessing binding affinity. Many such scoring functions are developed for rapid, high-throughput evaluation of binding energy of multiple conformations generated by a searching algorithm. The methods for more rigorous calculation of binding affinity calculation are generally time-consuming. Even so, in many studies more accurate methods were used for rescoring of the final poses and false-positive hits evaluation. We performed VS for three benchmark sets and used energy minimization with MM/PB(GB)SA methods (molecular mechanics energies combined with the Poisson-Boltzmann or generalized Born and surface area) to rescore binding affinities. The comparison of the area under the curve (AUC), enrichment factor (EF), and Boltzmann-enhanced discrimination of receiver operating characteristics (BEDROC) showed essential improvements in the binding energy prediction after the rescoring. Finally, we provide a program for minimization and rescoring VS results based on freely available AmberTools. The code requires just the final binding poses of the ligand as the input and can be used with any docking program.

Prospective Role of Peptide-Based Antiviral Therapy Against the Main Protease of SARS-CoV-2.

The recently emerged coronavirus (SARS-CoV-2) has created a crisis in world health, and economic sectors as an effective treatment or vaccine candidates are still developing. Besides, negative results in clinical trials and effective cheap solution against this deadly virus have brought new challenges. The viral protein, the main protease from SARS-CoV-2, can be effectively targeted due to its viral replication and pathogenesis role. In this study, we have enlisted 88 peptides from the AVPdb database. The peptide molecules were modeled to carry out the docking interactions. The four peptides molecules, P14, P39, P41, and P74, had more binding energy than the rest of the peptides in multiple docking programs. Interestingly, the active points of the main protease from SARS-CoV-2, Cys145, Leu141, Ser139, Phe140, Leu167, and Gln189, showed nonbonded interaction with the peptide molecules. The molecular dynamics simulation study was carried out for 200 ns to find out the docked complex’s stability where their stability index was proved to be positive compared to the apo and control complex. Our computational works based on peptide molecules may aid the future development of therapeutic options against SARS-CoV-2.

Successfully Initiating a Bike Share Program in Smaller Communities: The College or University as a Focal Point

Successful bike share systems are more common in larger than smaller cities. People use bikes to run errands, shop, go out to eat, or tour the city. But what about smaller communities that make up so much of the United States? For the sake of access to transportation and the economic boost to smaller municipalities, it is important to implement a bike share program that provides its citizens with options for public transportation. Incorporating a bike share system should be considered in smaller cities or municipalities that contain colleges or universities, given the large available student population that would be interested in using bikes for their own transportation needs. The approach is to first build the foundation for bike share success among college students while methodologically planning to increase bike availability to sites with probable high participation usage, including locations centrally located to city commerce in the community. The purpose of this article is to present the foundation to implement a successful bike share program for those smaller cities and communities with a college or university. The benefits of a bike share partnership with a college campus, overall physical activity (PA) and health benefits, potential and current demographic groups to use the bike share scheme, economic benefits, environmental factors, dock versus dockless bike share programs, and the finances and logistics of a bike share scheme will be examined. Yearlong strategies and important considerations for a successful bike share program will be explored.

IN SILICO IDENTIFICATION OF APOBEC3B SMALL MOLECULE INHIBITORS FROM DTP-NCI LIBRARIES

Objective: APOBEC3B (A3B) enzyme causes C-to-T or C-to-G somatic alteration in the cancer genome, leading to the evolution of a broad spectrum of human cancers. The present study aims to identify A3B small molecule inhibitors using a top-down approach via pharmacoinformatic virtual screening.
 Methods: Virtual screening of 2951 drug-alike molecules with diversified structures from the National Cancer Institute Development Therapeutics Program (DTP-NCI) compounds library was performed using GOLD and AutoDock Vina docking programs against the 3D structure of A3B (PDB ID: 5TD5).
 Results: Amongst the docked compounds, Nordracorubin, NSC641233 and Raloxifene hydrochloride showed the most potent binding affinities towards A3B on both Autodock/Vina and GOLD. Several significant similarities were observed between A3B and the three hits, including hydrogen bonds and pi-pi stacking. The three compounds also exhibited interaction with the centralized zinc cofactor and amino acid residues that directly contribute the deaminase activity of A3B enzyme.
 Conclusion: We hypothesize that the findings from this study could significantly shorten the quest for novel molecules against the A3B after confirmation with subsequent in vitro and in vivo studies in the near future.

Investigation of potential inhibitor properties of ethanolic propolis extracts against ACE-II receptors for COVID-19 treatment by molecular docking study.

The angiotensin-converting enzyme (ACE)-related carboxypeptidase, ACE-II, is a type I integral membrane protein of 805 amino acids that contains 1 HEXXH-E zinc binding consensus sequence. ACE-II has been implicated in the regulation of heart function and also as a functional receptor for the coronavirus that causes the severe acute respiratory syndrome (SARS). In this study, the potential of some flavonoids presents in propolis to bind to ACE-II receptors was calculated with in silico. Binding constants of ten flavonoids, caffeic acid, caffeic acid phenethyl ester, chrysin, galangin, myricetin, rutin, hesperetin, pinocembrin, luteolin and quercetin were measured using the AutoDock 4.2 molecular docking program. And also, these binding constants were compared to reference ligand of MLN-4760. The results are shown that rutin has the best inhibition potentials among the studied molecules with high binding energy − 8.04 kcal/mol, and it is followed by myricetin, quercetin, caffeic acid phenethyl ester and hesperetin. However, the reference molecule has binding energy of – 7.24 kcal/mol. In conclusion, the high potential of flavonoids in ethanolic propolis extracts to bind to ACE-II receptors indicates that this natural bee product has high potential for COVID-19 treatment, but this needs to be supported by experimental studies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00203-021-02351-1.

Identification of Allosteric Inhibitors of CD73 Using Three‐Phrase Computational Protocol for Drug Discovery

A three-phase computational protocol for drug discovery has been developed that includes 1) 3D shape characterization of binding sites of a protein to predict optimum performance with selected molecular docking programs; 2) Implementation of predictive algorithms for pharmacokinetic properties and ADME profiling for targeted searches in the ZINC15 database; 3) Flexible molecular docking/dynamics protocols of small molecule/protein complexes for drug discovery. Focusing on cancer immunotherapy to implement this computational approach, the allosteric site of ecto-5’-nucleotidase (CD73), a regulator of the extracellular concentration of adenosine, is targeted for large scale small molecule searches. CD73 which hydrolyzes AMP to adenosine, is a GPI-anchored cell surface protein cleaved and activated in the extracellular environment as a homodimer. CD73 exhibits higher expression on lymphocytes, endothelial, and epithelial cells during a stress response and his been reported activated for various types of cancer. CD73 participates in blocking antitumor responses and enhances tumor growth and metastasis by producing high levels of adenosine in the extracellular environment. Protein coordinates of CD73 were downloaded for these from Rutgers Consortium of Structural Biology (RCSB) Protein Data Bank (PDB) and the potential inhibitory molecules from the ZINC15 Database. AutoDock Vina was selected as the ideal docking program for the target based on comparing predicting binding constants with actual Ki's and RMSD analysis of the co-crystallized ligand with the re-docked ligand. Once molecules with high affinity predicted scores were identified from docking, molecular dynamics studies were performed on the highest scoring protein/small molecule complexes. Studies were carried out using GROMACS, implemented with AMBER force field. Dissociation constants (Ki's) for the protein-ligand complex were calculated throughout MD runs. Conformational changes in the binding sites were observed visually and quantitified with PCA analysis. Novel hydrogen bonding networks and hydrophobic networks of residues in the 3D structures were identified to connect the active sites to the allosteric binding site using a MD protocol.

Exploring the Docking and Inhibition of the Hinge‐Region Peptide of IgA1 to its Bacterial Protease

Immunoglobulin A (IgA) is an important antibody within the human body's immune response and comprises over 90% of the upper and lower respiratory immune systems (Chi et al., 2017). The bacterial pathogens such as Hemophilus influenzae, Neisseria gonorrhea, Neisseria meningitides, and Streptococcus pneumonia function to inactivate IgA1 through the production of a high molecular weight proteinase called IgA1P (Burton et al., 1988). Inhibitors of bacterial IgA1 proteinases are being researched as a method to enhance the activity of naturally occurring IgA1 and as an alternative to antibacterials (Burton et al., 1989). Three inhibitors of specifically the IgA1P of Hemophilus influenzae were designed and tested through docking studies with Autodock and HPEPDOCK software. The pentapeptide inhibitors, as opposed to Burton's tetrapeptide inhibitors, of this variant of IgA1P were based on the hinge-region of IgA1 found in the Hemophilus influenzae variant instead of the Neisseria gonorrhoeae variant. These inhibitors were found to successfully bind to the active site of IgA1P through trials ran with the docking programs. Inhibitor evaluation was supported by looking at values of compounds known to bind to the active site and values of randomly constructed peptides. The inhibitor peptides of PSPST, SPSTP, and TPSPS were found suitable as potential inhibitors to IgA1P and were synthesized using Solid Phase Peptide Synthesis. After the synthesis of the inhibitors, an inhibitory assay was implemented to assess the effectiveness of the synthesized inhibitors. The results allowed for physical confirmations to be made on the effectiveness of the designed inhibitors and whether they would have any merit to compete with the hinge-region peptide for medical use.

Disease-specific antigen presentation on MHC class II is inhibited by a small molecule in Sjögren’s Syndrome

Abstract Sjogren’s Syndrome (SjS) is one of the more common autoimmune diseases that has a strong genetic linkage. To date, no vaccine or therapeutic exists to cure SjS, and patients must rely on lifelong therapies to treat symptoms. Class II MHC are the primary susceptibility loci that form the genetic basis for many auto-immune disorders including SjS. I-Ag7 is the MHC in NOD mice that is used for the presentation of autoantigens and plays a critical role in the adaptive immune response. HLA-DQ8 the MHC in humans, is analogous to I-Ag7, in the NOD mouse model and is an important model for the onset of SjS. Using an in-silico molecular docking program a chemical library was screened that defined small molecules that were capable of occupying specific structural pockets along the I-Ag7 binding groove, with the objective of influencing auto-antigen peptide presentation to T cells. In this study we show, that the small molecule TATD can inhibit TCR signaling based on the structural pocket targeting mechanism. TATD previously proven to inhibit the onset of diabetes by blocking the auto-antigen presentation on I-Ag7, was analyzed to observe effects of prevention of SjS by, preventing the accumulation of B and T cells within the salivary gland of NOD mice. Treated mice also showed reduction in the incidence of inflammatory cell infiltration into lacrimal and salivary glands as compared to control mice with notable reduction in of the hallmark SjS anti-nuclear antibodies of Ro52, Ro60 and La. As a result this study presents a novel method for identifying small molecules capable of inhibiting T cell responses, with potentially therapeutic applications.

Identification of potential inhibitory compounds of an essential nucleotide biosynthesis enzyme, 6‐Phosphogluconate Dehydrogenase in Plasmodium Vivax

The erythrocytic infection and onset of malaria is a result of the protozoan parasitism from the Plasmodium genus. In 2018, there were an estimated 228 million cases of malaria worldwide largely attributed to P. falciparum and P. vivax infections. Current chemotherapy efforts against the Plasmodium parasites target mitochondrial function (Malarone), the 30s ribosomal subunit (Vibramycin) and prevention of the parasite's abilities to degrade the host's hemoglobin (Chloroquine), however, rising mutations have decreased their therapeutic effects. The essentiality of 6-phosphogluconate dehydrogenase (6PGDH) is demonstrated in its oxidation of 6-phosphogluconate (6PG) to ribulose-5-phosphate and the reduction of nicotinamide adenine dinucleotide phosphate (NADP+) to provide precursors in nucleic acid synthesis. Here, the homologous 3D structure of 6PGDH from P. falciparum was used for molecular docking studies since there is not a published structure of P. vivax 6PGDH in the Protein Data Bank (PDB). The structures of 6PGDH from P. falciparum and P. vivax display 80.30% sequence identity. The apo form of Pf6PGDH (PDB ID: 6FQX) was aligned with the structures containing the 6PG substrate (PDB ID: 6FQZ) and NADP+ coenzyme (PDB ID: 6FQY) ligands in order to define the active site. The 6PGDH protein was virtually screened against 307,735 ligands from several diverse compound libraries using the molecular docking program Genetic Optimization Ligand Docking (GOLD) and ranked for their predicted binding fitness based on empirical scoring functions of the employed genetic algorithm. The highest binding compound, ZINC55224876, received a GOLD Fitness score of 91.1 and demonstrated strong hydrophobic interactions as quantified by the piecewise linear potential (PLP) sub-score. The ligands gathered to act as controls were obtained from studies conducted on Trypanosoma brucei 6PGDH that demonstrated a reduction in protein function to act as positive controls. The screening of the positive and negative control ligands against the Pf6PGDH structure culminated in GOLD Fitness scores of 74.76 for the highest to the lowest score of 41.75. The top 10% of the highest overall scoring library, the Zinc ChemBridge library (124,345 ligands) resulted in a range of GOLD Fitness scores from 91.1- 59.73, whereas the lowest overall scoring library, Fragment (3,963 ligands) received scores ranging from 59.84-20.88. The resulting top scoring ligands may further be used for future enzyme assays in the process of drug discovery.

Impact of Redox Modification on Protein Kinase A (PKA) and Mitogen Activated Protein Kinase 1 (MAPK1) Substrate Selection

Cyclic adenosine monophosphate-dependent protein kinase (PKA) and mitogen-activated protein kinase 1 (MAPK1) are critical regulators in cell signaling that control a diverse set of cellular functions, including gene expression, cell cycle progression, tumor suppression, and apoptosis. Dysregulation of these kinases has been linked to many diseases, including cancer, renal disorders, and cardiovascular diseases. We hypothesized that, by modifying the substrate selectivity of PKA and MAPK1, cells may regulate which pathway is activated in response to a given signal. Specifically, we investigated the impact of redox modification on the substrate selection of PKA and MAPK1. To this end, we used surface plasmon resonance (SPR) and fluorescence polarization (FP) spectroscopy to assess the ability of oxidized and reduced forms of PKA and MAPK1 to bind a variety of model peptide ligands (e.g., PKI, Kemptide, and CREBtide for PKA and Lig-D, pepRSK1, and pepMEF2A for MAPK1). The binding of each substrate was monitored in real-time and the apparent rate constants (kon,app, and koff,app) and equilibrium binding parameters (i.e., KD,app) were determined for each kinase-ligand pair. These studies suggest that H2O2-dependent oxidation of PKA and MAPK1 alter their interactions with some ligands while having little effect on others. To gain further insights into the factors driving the differential changes in the interaction between these kinases and their peptide ligands, we used the ligand docking program, AutoDock CrankPep (ADCP), to model interactions between these peptide ligands and the oxidized and reduced forms of the kinases. These studies suggest that oxidization of each kinase leads to subtle changes in the architecture of its ligand-binding sites that disrupt interactions with some ligands while not affecting others. Together, these studies offer important insights into the mechanisms of crosstalk between redox and phosphorylation-dependent signaling at the level of kinase substrate selection and have implications for kinase regulation during normal and pathological states.

The Identification of Natural Products that are Predicted to Bind to the SARS‐CoV‐2 3CL Protease

Considerable attention has been paid to immunological approaches to dealing with the Covid‐19 pandemic. In addition, existing pharmaceuticals, such as the modified mononucleotide Remdesvir, have been studied in the context of the viral infection.This study looks at different classes of compounds, natural products, some already ingested by millions of people every day, and asks if there is evidence that they might bind to Covid‐19 viral proteins and possibly interfere with viral replication.In this study, the Universal Natural Products Database was used to search for compounds that bind to the SARS‐CoV‐2 3CL Protease. The database was interrogated using the Smina docking program, a branch of Autodock Vina. Those compounds that were predicted by Smina to bind better than ‐9 kcal/mole were then successively interrogated with LeDock, a program that gives results that are considerably different from Smina.The compounds with predicted binding values of ‐11 kcal/mole or lower by both programs were then studied by observing their predicted binding using several programs that enable the examination of ligand‐protein interactions.While this study identified many compounds of potential interest, this report concentrates on compounds that are commonly found in foodstuffs. Some but not all of these compounds are structurally close to those compounds that have been classified by others as Pan‐Assay Interference Compounds, PAINS.

Alantolactone inhibits cervical cancer progression by downregulating BMI1

Cervical cancer is the second most common cancer in women. Despite advances in cervical cancer therapy, tumor recurrence and metastasis remain the leading causes of mortality. High expression of BMI1 is significantly associated with poor tumor differentiation, high clinical grade, and poor prognosis of cervical cancer, and is an independent prognostic factor in cervical carcinoma. Alantolactone (AL), a sesquiterpene lactone, exhibits potent anti-inflammatory and anticancer activities. In this paper, we investigated the mechanism of AL in reducing the proliferation, migration, and invasion of HeLa and SiHa cervical cancer cells as well as its promotion of mitochondrial damage and autophagy. BMI1 silencing decreased epithelial-mesenchymal transformation-associated proteins and increased autophagy-associated proteins in HeLa cells. These effects were reversed by overexpression of BMI1 in HeLa cells. Thus, BMI1 expression is positively correlated with invasion and negatively correlated with autophagy in HeLa cells. Importantly, AL decreased the weight, volume, and BMI1 expression in HeLa xenograft tumors. Furthermore, the structure of BMI1 and target interaction of AL were virtually screened using the molecular docking program Autodock Vina; AL decreased the expression of N-cadherin, vimentin, and P62 and increased the expression of LC3B and Beclin-1 in xenograft tumors. Finally, expression of BMI1 increased the phosphorylation of STAT3, which is important for cell proliferation, survival, migration, and invasion. Therefore, we suggest that AL plays a pivotal role in inhibiting BMI1 in the tumorigenesis of cervical cancer and is a potential therapeutic agent for cervical cancer.

Discovery of new inhibitor for the protein arginine deiminase type 4 (PAD4) by rational design of α-enolase-derived peptides

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease affecting about 0.24 % of the world population. Protein arginine deiminase type 4 (PAD4) is believed to be responsible for the occurrence of RA by catalyzing citrullination of proteins. The citrullinated proteins act as autoantigens by stimulating an immune response. Citrullinated α-enolase has been identified as one of the autoantigens for RA. Hence, α-enolase serves as a suitable template for design of potential peptide inhibitors against PAD4. The binding affinity of α-enolase-derived peptides and PAD4 was virtually determined using PatchDock and HADDOCK docking programs. Synthesis of the designed peptides was performed using a solid phase peptide synthesis method. The inhibitory potential of each peptide was determined experimentally by PAD4 inhibition assay and IC50 measurement. PAD4 assay data show that the N-P2 peptide is the most favourable substrate among all peptides. Further modification of N-P2 by changing the Arg residue to canavanine [P2 (Cav)] rendered it an inhibitor against PAD4 by reducing the PAD4 activity to 35 % with IC50 1.39 mM. We conclude that P2 (Cav) is a potential inhibitor against PAD4 and can serve as a starting point for the development of even more potent inhibitors.

High-throughput virtual laboratory for drug discovery using massive datasets

Time-to-solution for structure-based screening of massive chemical databases for COVID-19 drug discovery has been decreased by an order of magnitude, and a virtual laboratory has been deployed at scale on up to 27,612 GPUs on the Summit supercomputer, allowing an average molecular docking of 19,028 compounds per second. Over one billion compounds were docked to two SARS-CoV-2 protein structures with full optimization of ligand position and 20 poses per docking, each in under 24 hours. GPU acceleration and high-throughput optimizations of the docking program produced 350× mean speedup over the CPU version (50× speedup per node). GPU acceleration of both feature calculation for machine-learning based scoring and distributed database queries reduced processing of the 2.4 TB output by orders of magnitude. The resulting 50× speedup for the full pipeline reduces an initial 43 day runtime to 21 hours per protein for providing high-scoring compounds to experimental collaborators for validation assays.

Discovery of Novel 1,2,4-Oxadiazole Derivatives as Potent Caspase-3 Activator for Cancer Treatment

In the present study, a quantitative structure–activity relationship (QSAR) and docking studies were accomplished on a series of 1,2,4-oxadiazoles. The results of QSARs are reliable and have high predictive ability for both the internal (q2 = 0.610) and external (pred_r2 = 0.553) datasets with least standard error (SE; i.e., 0.130) and four principal components, which signifies the reliability of the generated model. Molecular docking was also reported by the GOLD docking program, which showed that the hydrogen bonding may be responsible for the activity, and may be further increased upon adding high electronegative substitutions.

MSLDOCK: Multi-Swarm Optimization for Flexible Ligand Docking and Virtual Screening

Autodock and its various variants are widely utilized docking approaches, which adopt optimization methods as search algorithms for flexible ligand docking and virtual screening. However, many of them have their limitations, such as poor accuracy for dockings with highly flexible ligands and low docking efficiency. In this paper, a multi-swarm optimization algorithm integrated with Autodock environment is proposed to design a high-performance and high-efficiency docking program, namely, MSLDOCK. The search algorithm is a combination of the random drift particle swarm optimization with a novel multi-swarm strategy and the Solis and Wets local search method with a modified implementation. Due to the algorithm's structure, MSLDOCK also has a multithread mode. The experimental results reveal that MSLDOCK outperforms other two Autodock-based approaches in many aspects, such as self-docking, cross-docking, and virtual screening accuracies as well as docking efficiency. Moreover, compared with three non-Autodock-based docking programs, MSLDOCK can be a reliable choice for self-docking and virtual screening, especially for dealing with highly flexible ligand docking problems. The source code of MSLDOCK can be downloaded for free from https://github.com/lcmeteor/MSLDOCK.

Computational Graphics Software for Interactive Docking and Visualization of Ligand-Protein Complementarity.

The Dockeye software is designed to complement automated docking protocols by allowing the user's chemical know-how and experience of what makes for good protein-ligand binding, knowledge that is not easily encoded into automated algorithms, to guide the docking. It allows the interactive manipulation of the ligand placement against a protein target. Real-time intuitively comprehensible feedback about the location, spatial density, and the extent of both favorable and unfavorable atomic interactions between ligand and protein is provided through a carefully designed graphical object. It is also a tool for the graphical analysis of the interactions of known protein-ligand complexes. Comparative docking of 58 protein-ligand complexes with Dockeye and Autodock Vina shows how this software can be used synergistically with automated docking programs to significantly improve the task of discovery of ligand placement.

Natural products as inhibitors of COVID-19 main protease–A virtual screening by molecular docking

Background: The novel coronavirus (2019-nCoV) causes a severe respiratory illness unknown to a human before. Its alarmingly quick transmission to many countries across the world has resulted in a global health emergency. Therefore, an imminent need for drugs to combat this disease has been increased. Worldwide collaborative efforts from scientists are underway to determine a therapy to treat COVID-19 infections and reduce mortality rates. Since herbal medicines and purified natural products have been reported to have antiviral activity against Coronaviruses (CoVs), this in silico evaluation was performed for identifying potential natural compounds with promising inhibitory activities against COVID-19. Methods: In this study, a High Throughput Virtual Screening (HTVS) protocol was used as a fast method for discovering novel drug candidates as potential COVID-19 main protease (Mpro) inhibitors. Over 180,000 natural product-based compounds were obtained from the ZINC database and virtually screened against the COVID-19 Mpro. In this study, the Glide docking program was applied for high throughput virtual screening. Also, Extra precision (XP) has been used following the induced-fit docking (IFD) approach. The ADME properties of all compounds were analyzed and a final selection was made based on the Lipinski rule of five. Also, molecular dynamics (MD) simulations were conducted for a virtual complex of the best scoring compound with COVID-19 protease. Results: Nineteen compounds were introduced as new potential inhibitors. Compound ZINC08765174 (1-[3-(1H-indol-3-yl) propanoyl]-N-(4-phenylbutan-2-yl)piperidine-3-carboxamide showed a strong binding affinity (-11.5 kcal/mol) to the COVID-19 Mpro comparing to peramivir (-9.8 kcal/mol) as a positive control. Conclusions: Based on these findings, nineteen compounds were proposed as possible new COVID-19 inhibitors, of which ZINC08765174 had a high affinity to Mpro. Furthermore, the promising ADME properties of the selected compounds emphasize their potential as attractive candidates for the treatments of COVID-19.