A Comprehensive Survey of Prospective Structure-Based Virtual Screening for Early Drug Discovery in the Past Fifteen Years.

Structure-based virtual screening (SBVS), also known as molecular docking, has been increasingly applied to discover small-molecule ligands based on the protein structures in the early stage of drug discovery. In this review, we comprehensively surveyed the prospective applications of molecular docking judged by solid experimental validations in the literature over the past fifteen years. Herein, we systematically analyzed the novelty of the targets and the docking hits, practical protocols of docking screening, and the following experimental validations. Among the 419 case studies we reviewed, most virtual screenings were carried out on widely studied targets, and only 22% were on less-explored new targets. Regarding docking software, GLIDE is the most popular one used in molecular docking, while the DOCK 3 series showed a strong capacity for large-scale virtual screening. Besides, the majority of identified hits are promising in structural novelty and one-quarter of the hits showed better potency than 1 µM, indicating that the primary advantage of SBVS is to discover new chemotypes rather than highly potent compounds. Furthermore, in most studies, only in vitro bioassays were carried out to validate the docking hits, which might limit the further characterization and development of the identified active compounds. Finally, several successful stories of SBVS with extensive experimental validations have been highlighted, which provide unique insights into future SBVS drug discovery campaigns.

Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2.

COVID-19 (Corona Virus Disease of 2019) caused by the novel 'Severe Acute Respiratory Syndrome Coronavirus-2' (SARS-CoV-2) has wreaked havoc on human health and the global economy. As a result, for new medication development, it's critical to investigate possible therapeutic targets against the novel virus. 'Non-structural protein 15' (Nsp15) endonuclease is one of the crucial targets which helps in the replication of virus and virulence in the host immune system. Here, in the current study, we developed the structure-based pharmacophore model based on Nsp15-UMP interactions and virtually screened several databases against the selected model. To validate the screening process, we docked the top hits obtained after secondary filtering (Lipinski's rule of five, ADMET & Topkat) followed by 100 ns molecular dynamics (MD) simulations. Next, to revalidate the MD simulation studies, we have calculated the binding free energy of each complex using the MM-PBSA procedure. The discovered repurposed drugs can aid the rational design of novel inhibitors for Nsp15 of the SARS-CoV-2 enzyme and may be considered for immediate drug development.

Looking for SARS-CoV-2 therapeutics through computational approaches.

BACKGROUND: In the last few years in silico tools, including drug repurposing coupled with structure-based virtual screening, have been extensively employed to look for anti-COVID-19 agents. OBJECTIVE: The present review aims to provide readers with a portrayal of computational approaches that could conduct more quickly and cheaply to novel anti-viral agents. Particular attention is given to docking-based virtual screening. METHOD: The World Health Organization website was consulted to gain the latest information on SARS-CoV-2, its novel variants and their interplay with COVID-19 severity and treatment options. The Protein Data Bank was explored to look for 3D coordinates of SARS-CoV-2 proteins in their free and bound states, in the wild-types and mutated forms. Recent literature related to in silico studies focused on SARS-CoV-2 proteins was searched through PubMed. RESULTS: A large amount of work has been devoted thus far to computationally targeting viral entry and searching for inhibitors of the S-protein/ACE2 receptor complex. Another large area of investigation is linked to in silico identification of molecules able to block viral proteases -including Mpro- thus avoiding maturation of proteins crucial for virus life cycle. Such computational studies have explored the inhibitory potential of the most diverse molecule databases (including plant extracts, dietary compounds, FDA approved drugs). CONCLUSION: More efforts need to be dedicated in the close future to experimentally validate the therapeutic power of in silico identified compounds in order to catch, among the wide ensemble of computational hits, novel therapeutics to prevent and/or treat COVID-19.

In Silico Structure-Based Vaccine Design.

Structure-based vaccine design (SBVD) is an important technique in computational vaccine design that uses structural information on a targeted protein to design novel vaccine candidates. This increasing ability to rapidly model structural information on proteins and antibodies has provided the scientific community with many new vaccine targets and novel opportunities for future vaccine discovery. This chapter provides a comprehensive overview of the status of in silico SBVD and discusses the current challenges and limitations. Key strategies in the field of SBVD are exemplified by a case study on design of COVID-19 vaccines targeting SARS-CoV-2 spike protein.

Diversifying the chloroquinoline scaffold against SARS-CoV-2 main protease: Virtual screening approach using cross-docking, SiteMap analysis and molecular dynamics simulation

The absence of designated remedies for coronavirus disease 19 (Covid-19) and the lack of treatment protocols drove scientists to propose new small molecules and to attempt to repurpose existing drugs against various targets of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in order to bring forward efficient solutions. The main protease (Mpro) is one of the most promising drug targets due to its crucial role in fighting viral replic-ation. Several antiviral drugs have been used in an attempt to overcome the pandemic, such as hydroxychloroquine (HCQ). Despite its perceived positive outcomes in the beginning of the disease, HCQ was associated with several drawbacks, such as insolubility, toxicity, and cardiac adverse effects. There-fore, in the present study, a structure-based virtual screening approach was performed to identify structurally modified ligands of the chloroquinoline (CQ) scaffold with good solubility, absorption, and permeation aimed at eventually suggesting a more dependable alternative. PDB ID:7BRP Mpro was chosen as the most reliable receptor after cross-docking calculation using 30 crystal struc-tures. Then, a SiteMap analysis was performed and a total of 231,456 structur-ally modified compounds of the CQ scaffold were suggested. After Lipinski criteria filtration, 64,312 molecules were docked and their MM-GBSA free binding energy were calculated. Next, ADME descriptors were calculated, and 12 molecules with ADME properties better than that of HCQ were identified. The resulting molecules were subjected to molecular dynamics (MD) simul-ation for 100 ns. The results of the study indicate that 3 molecules (CQ_22;CQ_2 and CQ_5) show better interactions and stability with the Mpro receptor. Binding interaction analysis indicates that GLU143, THR26, and HIS41 amino acids are potential binding hot-spot residues for the remaining 3 ligands.

Predictive analysis, diagnosis of COVID-19 through computational screening and validation with spectro photometrical approach

Objective: To develop Favipiravir, based predictive models of coronavirus disease 2019 (COVID-19) from small molecule databases such as PubChem, Drug Bank, Zinc Database, and literature. Method(s): High Throughput Virtual Screening (HTVS) using different computational screening methods is used to identify the target and lead molecules. CoMFA (Comparative Molecular Field Analysis) is a 3D-QSAR procedure depending on information from known dynamic atoms and eventually permits one to plan and anticipate exercises of particles. These two analysis is used to train predictive models. Result(s): The predictive model achieved the highest accuracy score with a relatively small dataset size can be a subject of overfitting. Datasets with over 500 samples demonstrate an accuracy of about 85-95%, that can be considered as very good. Conclusion(s): From the result it is observed that Increasing level of potassium, sodium and nitrogen will lead to burst lipid bilayer membrane of virus which cause RNA replication rapidly. However, low level of sodium, potassium and nitrogen will help in the DNA polymerase inhibition and replication can be stopped. The best developed QSAR model in terms of the druggability and activity relation has been selected over the parent Favipiravir molecule for designing COVID-19 drugs may lead towards pharmaceutical development in future.Copyright © 2023, The Author(s), under exclusive licence to Korean Society of Environmental Risk Assessment and Health Science.

Virtual and In Vitro Screening of Natural Products Identifies Indole and Benzene Derivatives as Inhibitors of SARS-CoV-2 Main Protease (Mpro).

The rapid spread of the coronavirus disease 2019 (COVID-19) resulted in serious health, social, and economic consequences. While the development of effective vaccines substantially reduced the severity of symptoms and the associated deaths, we still urgently need effective drugs to further reduce the number of casualties associated with SARS-CoV-2 infections. Machine learning methods both improved and sped up all the different stages of the drug discovery processes by performing complex analyses with enormous datasets. Natural products (NPs) have been used for treating diseases and infections for thousands of years and represent a valuable resource for drug discovery when combined with the current computation advancements. Here, a dataset of 406,747 unique NPs was screened against the SARS-CoV-2 main protease (Mpro) crystal structure (6lu7) using a combination of ligand- and structural-based virtual screening. Based on 1) the predicted binding affinities of the NPs to the Mpro, 2) the types and number of interactions with the Mpro amino acids that are critical for its function, and 3) the desirable pharmacokinetic properties of the NPs, we identified the top 20 candidates that could potentially inhibit the Mpro protease function. A total of 7 of the 20 top candidates were subjected to in vitro protease inhibition assay and 4 of them (4/7; 57%), including two beta carbolines, one N-alkyl indole, and one Benzoic acid ester, had significant inhibitory activity against Mpro protease. These four NPs could be developed further for the treatment of COVID-19 symptoms.

FDA approved drugs with antiviral activity against SARS-CoV-2: From structure-based repurposing to host-specific mechanisms.

The continuing heavy toll of the COVID-19 pandemic necessitates development of therapeutic options. We adopted structure-based drug repurposing to screen FDA-approved drugs for inhibitory effects against main protease enzyme (Mpro) substrate-binding pocket of SARS-CoV-2 for non-covalent and covalent binding. Top candidates were screened against infectious SARS-CoV-2 in a cell-based viral replication assay. Promising candidates included atovaquone, mebendazole, ouabain, dronedarone, and entacapone, although atovaquone and mebendazole were the only two candidates with IC50s that fall within their therapeutic plasma concentration. Additionally, we performed Mpro assays on the top hits, which demonstrated inhibition of Mpro by dronedarone (IC50 18 µM), mebendazole (IC50 19 µM) and entacapone (IC50 9 µM). Atovaquone showed only modest Mpro inhibition, and thus we explored other potential mechanisms. Although atovaquone is Dihydroorotate dehydrogenase (DHODH) inhibitor, we did not observe inhibition of DHODH at the respective SARS-CoV-2 IC50. Metabolomic profiling of atovaquone treated cells showed dysregulation of purine metabolism pathway metabolite, where ecto-5'-nucleotidase (NT5E) was downregulated by atovaquone at concentrations equivalent to its antiviral IC50. Atovaquone and mebendazole are promising candidates with SARS-CoV-2 antiviral activity. While mebendazole does appear to target Mpro, atovaquone may inhibit SARS-CoV-2 viral replication by targeting host purine metabolism.

Structural insights into SARS-CoV-2 main protease conformational plasticity.

The spread of different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants underscores the need for insights into the structural properties of its structural and non-structural proteins. The highly conserved homo-dimeric chymotrypsin-like protease (3CL MPRO ), belonging to the class of cysteine hydrolases, plays an indispensable role in processing viral polyproteins that are involved in viral replication and transcription. Studies have successfully demonstrated the role of MPRO as an attractive drug target for designing antiviral treatments because of its importance in the viral life cycle. Herein, we report the structural dynamics of six experimentally solved structures of MPRO (i.e., 6LU7, 6M03, 6WQF, 6Y2E, 6Y84, and 7BUY including both ligand-free and ligand-bound states) at different resolutions. We have employed a structure-based balanced forcefield, CHARMM36m through state-of-the-art all-atoms molecular dynamics simulations at µ-seconds scale at room temperature (303K) and pH 7.0 to explore their structure-function relationship. The helical domain-III responsible for dimerization mostly contributes to the altered conformational states and destabilization of MPRO . A keen observation of the high degree of flexibility in the P5 binding pocket adjoining domain II-III highlights the reason for observation of conformational heterogeneity among the structural ensembles of MPRO . We also observe a differential dynamics of the catalytic pocket residues His41, Cys145, and Asp187, which may lead to catalytic impairment of the monomeric proteases. Among the highly populated conformational states of the six systems, 6LU7 and 7M03 forms the most stable and compact MPRO conformation with intact catalytic site and structural integrity. Altogether, our findings from this extensive study provides a benchmark to identify physiologically relevant structures of such promising drug targets for structure-based drug design and discovery of potent drug-like compounds having clinical potential.

Proposing lead compounds for the development of SARS-CoV-2 receptor-binding inhibitors.

The COVID-19 pandemic has had deleterious effects on the world and demands urgent measures to find therapeutic agents to combat the current and related future outbreaks. The entry of SARS-CoV-2 into the host's cell is facilitated by the interaction between the viral spike receptor-binding domain (sRBD) and the human angiotensin-converting enzyme 2 (hACE2). Although the interface of sRBD involved in the sRBD-hACE2 interaction has been projected as a primary vaccine and drug target, currently no small-molecule drugs have been approved for covid-19 treatment targeting sRBD. Herein structure-based virtual screening and molecular dynamics (MD) simulation strategies were applied to identify novel potential small-molecule binders of the SARS-CoV-2 sRBD from an sRBD-targeted compound library as leads for the development of anti-COVID-19 drugs. The library was initially screened against sRBD by using the GOLD docking program whereby 19 compounds were shortlisted based on docking scores after using a control compound to set the selection cutoff. The stability of each compound in MD simulations was used as a further standard to select four hits namely T4S1820, T4589, E634-1449, and K784-7078. Analyses of simulations data showed that the four compounds remained stably bound to sRBD for ≥ 80 ns with reasonable affinities and interacted with pharmacologically important amino acid residues. The compounds exhibited fair solubility, lipophilicity, and toxicity-propensity characteristics that could be improved through lead optimization regimes. The overall results suggest that the scaffolds of T4S1820, E634-1449, and K784-7078 could serve as seeds for developing potent small-molecule inhibitors of SARS-CoV-2 receptor binding and cell entry.Communicated by Ramaswamy H. Sarma.

Virtual screening campaigns and ADMET evaluation to unlock the potency of flavonoids from Erythrina as 3CLpro SARS-COV-2 inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic with more than 6 million deaths worldwide. Flavonoids from the genus Erythrina may inhibit SARS-CoV-2, targeting 3C-like protease (3CLpro), an enzyme essential in the virus's growth. Hence, this study aimed to screen 378 flavonoids from Erythrina against 3CLpro, using molecular docking, Lipinski's rule of five, and in silico absorption, distribution, metabolism, excretion, and toxicity. These virtual screening campaigns suggest that 108 flavonoids have stronger binding energy values (−13.23 to −10.20 kcal/mol) than the N3 inhibitor (−10.14 kcal/mol) as the reference ligand. Some 33 of these flavonoids may be hepatoxicity and mutagenicity-free. They are also non-hERG I and II inhibitors. Two of them, orientanol E (171) and erycaffra F (57), have binding energy values in the top 10 hits and good absorption profiles, despite their poor distribution properties. They may have a high bioavailability in the body and be excreted from the body through feces. Conducted molecular dynamics simulations also support orientanol E (171) and erycaffra F (57) as 3CLpro inhibitor candidates. Our study suggests that flavonoids from Erythrina have potential as 3CLpro inhibitors, which help guide further in vitro and in vivo experiments in COVID-19 drug development © 2023 Vicki Nishinarizki et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)

In silico design of ACE2 mutants for competitive binding of SARS-CoV-2 receptor binding domain with hACE2

The receptor binding motif (RBM) within the S-protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been touted as one of the main targets for vaccine/therapeutic development due to its interaction with the human angiotensin II converting enzyme 2 (hACE2) to facilitate virus entry into the host cell. The mechanism of action is based on the disruption of binding between the RBM and the hACE2 to prevent virus uptake for replication. In this work, we applied in silico approaches to design specific competitive binders for SARS-CoV-2 S-protein receptor binding motif (RBM) by using hACE2 peptidase domain (PD) mutants. Online single point mutation servers were utilised to estimate the effect of PD mutation on the binding affinity with RBM. The PD mutants were then modelled and the binding free energy was calculated. Three PD variants were designed with an increased affinity and interaction with SARS-CoV-2-RBM. It is hope that these designs could serve as the initial work for vaccine/drug development and could eventually interfere the preliminary recognition between SARS-CoV-2 and the host cell. © 2022 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved.

Virtual screening and structure-based 3D pharmacophore approach to identify small-molecule inhibitors of SARS-CoV-2 Mpro.

The outbreak caused by a coronavirus 2 has required quick and potential treatment strategies. The main protease enzyme Mpro plays an important role in the viral replication which renders it an important target for discovering SARS-CoV-2 inhibitors. In this study, 3D pharmacophore structure-based virtual screening and molecular docking were conducted using MOE and Bristol University Docking Engine (BUDE). Around 400,000 molecules of ZINC15 database were docked against the crystal structure of main protease, followed by 3D pharmacophore filtration. Six top-ranked hits (ZINC58717986, ZINC60399606, ZINC58662884, ZINC45988635, ZINC54706757 and ZINC17320595) were identified based on their strong spatial affinity and forming H-bonds with key residues H41, E166, Q189 and T190 of the binding pocket of Mpro SARS-CoV-2. The 6 hits subjected to molecular dynamics simulations for 100 ns followed by binding free energy calculations using MM-PBSA technique. Interestingly, three hits showed free binding energy (ΔGbinding) lower than tert-butyl N-[1-[(2S)-1-[[(2S)-4-(benzylamino)-3,4-dioxo-1-[(3S)-2-oxopyrrolidin-3-yl]butan-2-yl]amino]-3-cyclopropyl-1-oxopropan-2-yl]-2-oxopyridin-3-yl]carbamate (α-ketoamide 13 b) (ΔGbinding) -76.67 ± 0.5 kJ/mol which suggested their potential against SARS-CoV-2. The best binding free energy candidates, ZINC58717986 (ΔGbinding) -98.41 ± 0.7 kJ/mol. The second-best hit candidate, ZINC54706757 (ΔGbinding) -83.4 ± 0.6 kJ/mol and the third one ZINC17320595 (ΔGbinding) -78.85 ± 0.5 kJ/mol. Per residue decomposition free energy indicates H41, S46, H164, E166, D187, Q189 and Q192 are hot spot residues while residues M49, M165, L167 and P168 contribute to the hydrophobic interactions. The pharmacokinetic study suggests that the selected 6 hits possess drug-like properties. The 3D pharmacophore virtual screening, molecular dynamics and MM-PBSA approaches facilitated identification 3 promising hits with low free binding energy as SARS-CoV-2 inhibitors.Communicated by Ramaswamy H. Sarma.

Applications and prospects of cryo-EM in drug discovery.

Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time- and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy (cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence (AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of medium-resolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.

Identification of Four New Chemical Series of Small Drug-Like Natural Products as Potential Neuropilin-1 Inhibitors by Structure-Based Virtual Screening: Pharmacophore-Based Molecular Docking and Dynamics Simulation.

Neuropilin-1 (NRP-1), a surface transmembrane glycoprotein, is one of the most important co-receptors of VEGF-A165 (vascular endothelial growth factor) responsible for pathological angiogenesis. In general, NRP-1 overexpression in cancer correlates with poor prognosis and more tumor aggressiveness. NRP-1 role in cancer has been mainly explained by mediating VEGF-A165-induced effects on tumor angiogenesis. NRP-1 was recently identified as a co-receptor and an independent gateway for SARS-CoV-2 through binding subunit S2 of Spike protein in the same way as VEGF-A165. Thus, NRP-1 is of particular value as a target for cancer therapy and other angiogenesis-dependent diseases as well as for SARS-CoV-2 antiviral intervention. Herein, The Super Natural II, the largest available database of natural products (∼0.33 M), pre-filtered with drug-likeness criteria (absorption, distribution, metabolism and excretion/toxicity), was screened against NRP-1. NRP-1/VEGF-A165 interaction is one of protein-protein interfaces (PPIs) known to be challenging when approached in-silico. Thus, a PPI-suited multi-step virtual screening protocol, incorporating a derived pharmacophore with molecular docking and followed by MD (molecular dynamics) simulation, was designed. Two stages of pharmacophorically constrained molecular docking (standard and extra precisions), a mixed Torsional/Low-mode conformational search and MM-GBSA ΔG binding affinities calculation, resulted in the selection of 100 hits. These 100 hits were subjected to 20 ns MD simulation, that was extended to 100 ns for top hits (20) and followed by post-dynamics analysis (atomic ligand-protein contacts, RMSD, RMSF, MM-GBSA ΔG, Rg, SASA and H-bonds). Post-MD analysis showed that 19 small drug-like nonpeptide natural molecules, grouped in four chemical scaffolds (purine, thiazole, tetrahydropyrimidine and dihydroxyphenyl), well verified the derived pharmacophore and formed stable and compact complexes with NRP-1. The discovered molecules are promising and can serve as a base for further development of new NRP-1 inhibitors.

Design of a stabilized RBD enables potently neutralizing SARS-CoV-2 single-component nanoparticle vaccines.

Waning immunity and emerging variants necessitate continued vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Improvements in vaccine safety, tolerability, and ease of manufacturing would benefit these efforts. Here, we develop a potent and easily manufactured nanoparticle vaccine displaying the spike receptor-binding domain (RBD). Computational design to stabilize the RBD, eliminate glycosylation, and focus the immune response to neutralizing epitopes results in an RBD immunogen that resolves issues hindering the efficient nanoparticle display of the native RBD. This non-glycosylated RBD can be genetically fused to diverse single-component nanoparticle platforms, maximizing manufacturing ease and flexibility. All engineered RBD nanoparticles elicit potently neutralizing antibodies in mice that far exceed monomeric RBDs. A 60-copy particle (noNAG-RBD-E2p) also elicits potently neutralizing antibodies in non-human primates. The neutralizing antibody titers elicited by noNAG-RBD-E2p are comparable to a benchmark stabilized spike antigen and reach levels against Omicron BA.5 that suggest that it would provide protection against emerging variants.

Selection of suitable protein structure from Protein Data Bank: An important step in Structure based Drug Design Studies.

Selection of a protein structure is an important step for the success of the drug discovery process using structure-based design. Selection of the right crystal structure is a critical step as multiple crystal structures are available for the same protein in the protein data bank (PDB). In this communication, we have discussed a systematic approach for selecting the right type of protein structure. Some case studies for the selection of crystal structures of TACE, 11ß-HSD1, DprE1 andSARS-CoV-2 Mpro enzymes have been discussed for the purpose of illustration.

Advanced simulations and screening to repurposing a 3C protease inhibitor against the rupintrivir-resistant human norovirus-induced gastroenteritis.

Human norovirus (HuNoV) causes acute viral gastroenteritis in all age groups, and dehydration and severe diarrhea in the elderly. The World Health Organization reports ∼1.45 million deaths from acute gastroenteritis annually in the world. Rupintrivir, an inhibitory medicine against the human rhinovirus C3 protease, has been reported to inhibit HuNoV 3C protease. However, several HuNoV 3C protease mutations have been revealed to reduce the susceptibility of HuNoV to rupintrivir. The structural details behind rupintrivir-resistance of these single-point mutations (A105V and I109V) are not still clear. Hence, in this study, a combination of computational techniques were used to determine the rupintrivir-resistance mechanism and to propose an inhibitor against wild-type and mutant HuNoV 3C protease through structure-based virtual screening. Dynamic structural results indicated the unstable binding of rupintrivir at the cleft binding site of the wild-type and mutant 3C proteases, leading to its detachment. Our findings presented that the domain II of the HuNoV 3C protease had a critical role in binding of inhibitory molecules. Binding energy computations, steered molecular dynamics and umbrella sampling simulations confirmed that amentoflavone, the novel suggested inhibitor, strongly binds to the cleft site of all protease models and has a good structural stability in the complex system along the molecular dynamic simulations. Our in silico study proposed the selected compound as a potential inhibitor against the HuNoV 3C protease. However, additional experimental and clinical studies are required to corroborate the therapeutic efficacy of the compound.