Showing papers on "Docking (molecular) published in 2020"

The HDOCK server for integrated protein-protein docking.

Abstract: The HDOCK server (http://hdock.phys.hust.edu.cn/) is a highly integrated suite of homology search, template-based modeling, structure prediction, macromolecular docking, biological information incorporation and job management for robust and fast protein-protein docking. With input information for receptor and ligand molecules (either amino acid sequences or Protein Data Bank structures), the server automatically predicts their interaction through a hybrid algorithm of template-based and template-free docking. The HDOCK server distinguishes itself from similar docking servers in its ability to support amino acid sequences as input and a hybrid docking strategy in which experimental information about the protein-protein binding site and small-angle X-ray scattering can be incorporated during the docking and post-docking processes. Moreover, HDOCK also supports protein-RNA/DNA docking with an intrinsic scoring function. The server delivers both template- and docking-based binding models of two molecules and allows for download and interactive visualization. The HDOCK server is user friendly and has processed >30,000 docking jobs since its official release in 2017. The server can normally complete a docking job within 30 min.

Fast Identification of Possible Drug Treatment of Coronavirus Disease -19 (COVID-19) Through Computational Drug Repurposing Study

Abstract: The recent outbreak of novel coronavirus disease-19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D structures of key viral proteins are resolved. The virus causing COVID-19 is SARS-CoV-2. Taking advantage of a recently released crystal structure of SARS-CoV-2 main protease in complex with a covalently bonded inhibitor, N3 (Liu et al., 10.2210/pdb6LU7/pdb), I conducted virtual docking screening of approved drugs and drug candidates in clinical trials. For the top docking hits, I then performed molecular dynamics simulations followed by binding free energy calculations using an end point method called MM-PBSA-WSAS (molecular mechanics/Poisson-Boltzmann surface area/weighted solvent-accessible surface area; Wang, Chem. Rev. 2019, 119, 9478; Wang, Curr. Comput.-Aided Drug Des. 2006, 2, 287; Wang; ; Hou J. Chem. Inf. Model., 2012, 52, 1199). Several promising known drugs stand out as potential inhibitors of SARS-CoV-2 main protease, including carfilzomib, eravacycline, valrubicin, lopinavir, and elbasvir. Carfilzomib, an approved anticancer drug acting as a proteasome inhibitor, has the best MM-PBSA-WSAS binding free energy, -13.8 kcal/mol. The second-best repurposing drug candidate, eravacycline, is synthetic halogenated tetracycline class antibiotic. Streptomycin, another antibiotic and a charged molecule, also demonstrates some inhibitory effect, even though the predicted binding free energy of the charged form (-3.8 kcal/mol) is not nearly as low as that of the neutral form (-7.9 kcal/mol). One bioactive, PubChem 23727975, has a binding free energy of -12.9 kcal/mol. Detailed receptor-ligand interactions were analyzed and hot spots for the receptor-ligand binding were identified. I found that one hot spot residue, His41, is a conserved residue across many viruses including SARS-CoV, SARS-CoV-2, MERS-CoV, and hepatitis C virus (HCV). The findings of this study can facilitate rational drug design targeting the SARS-CoV-2 main protease.

Potential Inhibitor of COVID-19 Main Protease (M pro ) From Several Medicinal Plant Compounds by Molecular Docking Study

Abstract: COVID-19, a new strain of coronavirus (CoV), was identified in Wuhan, China, in 2019. No specific therapies are available and investigations regarding COVID-19 treatment are lacking. Liu et al. (2020) successfully crystallised the COVID-19 main protease (Mpro), which is a potential drug target. The present study aimed to assess bioactive compounds found in medicinal plants as potential COVID-19 Mpro inhibitors, using a molecular docking study. Molecular docking was performed using Autodock 4.2, with the Lamarckian Genetic Algorithm, to analyse the probability of docking. COVID-19 Mpro was docked with several compounds, and docking was analysed by Autodock 4.2, Pymol version 1.7.4.5 Edu, and Biovia Discovery Studio 4.5. Nelfinavir and lopinavir were used as standards for comparison. The binding energies obtained from the docking of 6LU7 with native ligand, nelfinavir, lopinavir, kaempferol, quercetin, luteolin-7-glucoside, demethoxycurcumin, naringenin, apigenin-7-glucoside, oleuropein, curcumin, catechin, epicatechin-gallate, zingerol, gingerol, and allicin were -8.37, -10.72, -9.41, -8.58, -8.47, -8.17, -7.99, -7.89, -7.83, -7.31, -7.05, -7.24, -6.67, -5.40, -5.38, and -4.03 kcal/mol, respectively. Therefore, nelfinavir and lopinavir may represent potential treatment options, and kaempferol, quercetin, luteolin-7-glucoside, demethoxycurcumin, naringenin, apigenin-7-glucoside, oleuropein, curcumin, catechin, and epicatechin-gallate appeared to have the best potential to act as COVID-19 Mpro inhibitors. However, further research is necessary to investigate their potential medicinal use.

Virtual screening for potential inhibitors of human hexokinase II for the development of anti-dengue therapeutics

Abstract: Dengue fever, which is a disease caused by the dengue virus (DENV), is a major unsolved issue in many tropical and sub-tropical regions of the world. The absence of treatment that effectively prevent further viral propagation inside the human’s body resulted in a high number of deaths globally each year. Thus, novel anti-dengue therapies are required for effective treatment. Hu-man hexokinase II (HKII), which is the first enzyme in the glycolytic pathway, is an important drug target due to its significant impact on viral replication and survival in host cells. In this study, 23.1 million compounds were computationally-screened against HKII using the Ultrafast Shape Recognition with a CREDO Atom Types (USRCAT) algorithm. In total, 300 compounds with the highest similarity scores relative to three reference molecules, known as Al-pha-D-glucose (GLC), Beta-D-glucose-6-phosphate (BG6), and 2-deoxyglucose (2DG), were aligned. Of these 300 compounds, 165 were chosen for further structure-based screening, based on their similarity scores, ADME analysis, the Lipinski’s Rule of Five, and virtual toxicity test results. The selected analogues were subsequently docked against each domain of the HKII structure (PDB ID: 2NZT) using AutoDock Vina programme. The three top-ranked compounds for each query were then selected from the docking results based on their binding energy, the number of hydrogen bonds formed, and the specific catalytic residues. The best docking results for each analogue were observed for the C-terminus of Chain B. The top-ranked analogues of GLC, compound 10, compound 26, and compound 58, showed predicted binding energies of −7.2, −7.0, and −6.10 kcal/mol and 7, 5, and 2 hydrogen bonds, respectively. The analogues of BG6, compound 30, compound 36, and compound 38, showed predicted binding energies of −7.8, −7.4, and −7.0 kcal/mol and 11, 9, and 5 hydrogen bonds, while the top three analogues of 2DG, known as compound 1, compound 4, and compound 31, showed predicted binding energies of −6.8, −6.3, and −6.3 kcal/mol and 4, 3, and 1 hydrogen bonds, sequentially. The highest-ranked compounds in the docking analysis were then selected for molecular dynamics simulation, where compound 10, compound 30, and compound 1, which are the analogues of GLC, BG6, and 2DG, have shown strong protein-ligand stability with an RMSD value of ±5.0 A° with a 5 H bond, ±4.0 A° with an 8 H bond, and ±0.5 A° with a 2 H bond, respectively, compared to the reference molecules throughout the 20 ns simulation time. Therefore, by using the computational studies, we pro-posed novel compounds, which may act as potential drugs against DENV by inhibiting HKII’s activity.

CB-Dock: a web server for cavity detection-guided protein-ligand blind docking.

Abstract: As the number of elucidated protein structures is rapidly increasing, the growing data call for methods to efficiently exploit the structural information for biological and pharmaceutical purposes. Given the three-dimensional (3D) structure of a protein and a ligand, predicting their binding sites and affinity are a key task for computer-aided drug discovery. To address this task, a variety of docking tools have been developed. Most of them focus on docking in the preset binding sites given by users. To automatically predict binding modes without information about binding sites, we developed a user-friendly blind docking web server, named CB-Dock, which predicts binding sites of a given protein and calculates the centers and sizes with a novel curvature-based cavity detection approach, and performs docking with a popular docking program, Autodock Vina. This method was carefully optimized and achieved ~70% success rate for the top-ranking poses whose root mean square deviation (RMSD) were within 2 A from the X-ray pose, which outperformed the state-of-the-art blind docking tools in our benchmark tests. CB-Dock offers an interactive 3D visualization of results, and is freely available at http://cao.labshare.cn/cb-dock/.

SARS-CoV-2 RNA dependent RNA polymerase (RdRp) targeting: an in silico perspective.

Abstract: New treatment against SARS-CoV-2 now is a must. Nowadays, the world encounters a huge health crisis by the COVID-19 viral infection. Nucleotide inhibitors gave a lot of promising results in terms of its efficacy against different viral infections. In this work, molecular modeling, docking, and dynamics simulations are used to build a model for the viral protein RNA-dependent RNA polymerase (RdRp) and test its binding affinity to some clinically approved drugs and drug candidates. Molecular dynamics is used to equilibrate the system upon binding calculations to ensure the successful reproduction of previous results, to include the dynamics of the RdRp, and to understand how it affects the binding. The results show the effectiveness of Sofosbuvir, Ribavirin, Galidesivir, Remdesivir, Favipiravir, Cefuroxime, Tenofovir, and Hydroxychloroquine, in binding to SARS-CoV-2 RdRp. Additionally, Setrobuvir, YAK, and IDX-184, show better results, while four novel IDX-184 derivatives show promising results in attaching to the SARS-CoV-2 RdRp. There is an urgent need to specify drugs that can selectively bind and subsequently inhibit SARS-CoV-2 proteins. The availability of a punch of FDA-approved anti-viral drugs can help us in this mission, aiming to reduce the danger of COVID-19. The compounds 2 and 3 may tightly bind to the SARS-CoV-2 RdRp and so may be successful in the treatment of COVID-19.

Nelfinavir was predicted to be a potential inhibitor of 2019 nCov main protease by an integrative approach combining homology modelling, molecular docking and binding free energy calculation

Abstract: 2019-nCov has caused more than 80 deaths as of 27 January 2020 in China, and infection cases have been reported in more than 10 countries. However, there is no approved drug to treat the disease. 2019-nCov Mpro is a potential drug target to combat the virus. We built homology models based on SARS Mpro structures, and docked 1903 small molecule drugs to the models. Based on the docking score and the 3D similarity of the binding mode to the known Mpro ligands, 4 drugs were selected for binding free energy calculations. Both MM/GBSA and SIE methods voted for nelfinavir, with the binding free energy of -24.69±0.52 kcal/mol and -9.42±0.04 kcal/mol, respectively. Therefore, we suggested that nelfinavir might be a potential inhibitor against 2019-nCov Mpro.

Essential Oils as Antiviral Agents. Potential of Essential Oils to Treat SARS-CoV-2 Infection: An In-Silico Investigation.

Abstract: Essential oils have shown promise as antiviral agents against several pathogenic viruses. In this work we hypothesized that essential oil components may interact with key protein targets of the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A molecular docking analysis was carried out using 171 essential oil components with SARS-CoV-2 main protease (SARS-CoV-2 Mpro), SARS-CoV-2 endoribonucleoase (SARS-CoV-2 Nsp15/NendoU), SARS-CoV-2 ADP-ribose-1″-phosphatase (SARS-CoV-2 ADRP), SARS-CoV-2 RNA-dependent RNA polymerase (SARS-CoV-2 RdRp), the binding domain of the SARS-CoV-2 spike protein (SARS-CoV-2 rS), and human angiotensin−converting enzyme (hACE2). The compound with the best normalized docking score to SARS-CoV-2 Mpro was the sesquiterpene hydrocarbon (E)-β-farnesene. The best docking ligands for SARS−CoV Nsp15/NendoU were (E,E)-α-farnesene, (E)-β-farnesene, and (E,E)−farnesol. (E,E)−Farnesol showed the most exothermic docking to SARS-CoV-2 ADRP. Unfortunately, the docking energies of (E,E)−α-farnesene, (E)-β-farnesene, and (E,E)−farnesol with SARS-CoV-2 targets were relatively weak compared to docking energies with other proteins and are, therefore, unlikely to interact with the virus targets. However, essential oil components may act synergistically, essential oils may potentiate other antiviral agents, or they may provide some relief of COVID-19 symptoms.

Structure-based drug designing for potential antiviral activity of selected natural products from Ayurveda against SARS-CoV-2 spike glycoprotein and its cellular receptor

Abstract: The recent outbreak of COVID-19 caused by SARS-CoV-2 brought a great global public health and economic concern. SARS-CoV-2 is an enveloped RNA virus, from the genus Betacoronavirus. Although few molecules have been tested and shown some efficacy against SARS-CoV-2 in humans but a safe and cost-effective attachment inhibitors are still required for the treatment of COVID-19. Natural products are gaining attention because of the large therapeutic window and potent antiviral, immunomodulatory, anti-inflammatory, and antioxidant properties. Therefore, this study was planned to screen natural products from Ayurveda that have the potential to modulate host immune system as well as block the virus entry in host cells by interfering its interaction with cellular receptor and may be used to develop an effective and broad-spectrum strategy for the management of COVID-19 as well as other coronavirus infections in coming future. To decipher the antiviral activity of the selected natural products, molecular docking was performed. Further, the drug-likeness, pharmacokinetics and toxicity parameters of the selected natural products were determined. Docking results suggest that curcumin and nimbin exhibits highest interaction with spike glycoprotein (MolDock score − 141.36 and − 148.621 kcal/mole) and ACE2 receptor (MolDock score − 142.647 and − 140.108 kcal/mole) as compared with other selected natural products/drugs and controls. Also, the pharmacokinetics data illustrated that all selected natural products have better pharmacological properties (low molecular weight; no violation of Lipinski rule of five, good absorption profiles, oral bioavailability, good blood–brain barrier penetration, and low toxicity risk). Our study exhibited that curcumin, nimbin, withaferin A, piperine, mangiferin, thebaine, berberine, and andrographolide have significant binding affinity towards spike glycoprotein of SARS-CoV-2 and ACE2 receptor and may be useful as a therapeutic and/or prophylactic agent for restricting viral attachment to the host cells. However, few other natural products like resveratrol, quercetin, luteolin, naringenin, zingiberene, and gallic acid has the significant binding affinity towards ACE2 receptor only and therefore may be used for ACE2-mediated attachment inhibition of SARS-CoV-2.

In silico study the inhibition of angiotensin converting enzyme 2 receptor of COVID-19 by Ammoides verticillata components harvested from Western Algeria.

Abstract: The objective of this present study is to focus on the in silico study to screen for an alternative drug that can block the activity of the angiotensin converting enzyme 2 (ACE2) as a receptor for SARS-CoV-2, potential therapeutic target of the COVID-19 virus using natural compounds (Isothymol, Thymol, Limonene, P-cymene and γ-terpinene) derived from the essential oil of the antiviral and antimicrobial plant Ammoides verticillata (Desf.) Briq. which is located in the occidental Algeria areas. This study reveals that Isothymol, a major component of this plant, gives the best docking scores, compared to, the co-crystallized inhibitor β-D-mannose of the enzyme ACE2, to Captropil drug as good ACE2 inhibitor and to Chloroquine antiviral drug also involved in other mechanisms as inhibition of ACE2 cellular receptor. In silico (ADME), drug-likeness, PASS & P450 site of metabolism prediction, pharmacophore Mapper showed that the compound Isothymol has given a good tests results compared to the β-D-mannose co-crystallized inhibitor, to Captopril and Chloroquine drugs. Also the other natural compounds gave good results. The Molecular Dynamics Simulation study showed good result for the Isotymol- ACE2 docked complex. This study revealed for the first time that Isothymol is a functional inhibitor of angiotensin converting enzyme 2 activity and the components of essential oils Ammoides verticillata can be used as potential inhibitors to the ACE2 receptor of SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Virtual Screening of Natural Products against Type II Transmembrane Serine Protease (TMPRSS2), the Priming Agent of Coronavirus 2 (SARS-CoV-2).

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused about 2 million infections and is responsible for more than 100,000 deaths worldwide. To date, there is no specific drug registered to combat the disease it causes, named coronavirus disease 2019 (COVID-19). In the current study, we used an in silico approach to screen natural compounds to find potent inhibitors of the host enzyme transmembrane protease serine 2 (TMPRSS2). This enzyme facilitates viral particle entry into host cells, and its inhibition blocks virus fusion with angiotensin-converting enzyme 2 (ACE2). This, in turn, restricts SARS-CoV-2 pathogenesis. A three-dimensional structure of TMPRSS2 was built using SWISS-MODEL and validated by RAMPAGE. The natural compounds library Natural Product Activity and Species Source (NPASS), containing 30,927 compounds, was screened against the target protein. Two techniques were used in the Molecular Operating Environment (MOE) for this purpose, i.e., a ligand-based pharmacophore approach and a molecular docking-based screening. In total, 2140 compounds with pharmacophoric features were retained using the first approach. Using the second approach, 85 compounds with molecular docking comparable to or greater than that of the standard inhibitor (camostat mesylate) were identified. The top 12 compounds with the most favorable structural features were studied for physicochemical and ADMET (absorption, distribution, metabolism, excretion, toxicity) properties. The low-molecular-weight compound NPC306344 showed significant interaction with the active site residues of TMPRSS2, with a binding energy score of -14.69. Further in vitro and in vivo validation is needed to study and develop an anti-COVID-19 drug based on the structures of the most promising compounds identified in this study.

COVID-19 Docking Server: A meta server for docking small molecules, peptides and antibodies against potential targets of COVID-19.

Abstract: MOTIVATION The coronavirus disease 2019 (COVID-19) caused by a new type of coronavirus has been emerging from China and led to thousands of death globally since December 2019. Despite many groups have engaged in studying the newly emerged virus and searching for the treatment of COVID-19, the understanding of the COVID-19 target-ligand interactions represents a key challenge. Herein, we introduce COVID-19 Docking Server, a web server that predicts the binding modes between COVID-19 targets and the ligands including small molecules, peptides and antibodies. RESULTS Structures of proteins involved in the virus life cycle were collected or constructed based on the homologs of coronavirus, and prepared ready for docking. The meta-platform provides a free and interactive tool for the prediction of COVID-19 target-ligand interactions and following drug discovery for COVID-19. AVAILABILITY AND IMPLEMENTATION http://ncov.schanglab.org.cn. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Investigation of Some Antiviral N -Heterocycles as COVID 19 Drug: Molecular Docking and DFT Calculations.

Abstract: The novel coronavirus, COVID-19, caused by SARS-CoV-2, is a global health pandemic that started in December 2019. The effective drug target among coronaviruses is the main protease Mpro, because of its essential role in processing the polyproteins that are translated from the viral RNA. In this study, the bioactivity of some selected heterocyclic drugs named Favipiravir (1), Amodiaquine (2), 2'-Fluoro-2'-deoxycytidine (3), and Ribavirin (4) was evaluated as inhibitors and nucleotide analogues for COVID-19 using computational modeling strategies. The density functional theory (DFT) calculations were performed to estimate the thermal parameters, dipole moment, polarizability, and molecular electrostatic potential of the present drugs; additionally, Mulliken atomic charges of the drugs as well as the chemical reactivity descriptors were investigated. The nominated drugs were docked on SARS-CoV-2 main protease (PDB: 6LU7) to evaluate the binding affinity of these drugs. Besides, the computations data of DFT the docking simulation studies was predicted that the Amodiaquine (2) has the least binding energy (-7.77 Kcal/mol) and might serve as a good inhibitor to SARS-CoV-2 comparable with the approved medicines, hydroxychloroquine, and remdesivir which have binding affinity -6.06 and -4.96 Kcal/mol, respectively. The high binding affinity of 2 was attributed to the presence of three hydrogen bonds along with different hydrophobic interactions between the drug and the critical amino acids residues of the receptor. Finally, the estimated molecular electrostatic potential results by DFT were used to illustrate the molecular docking findings. The DFT calculations showed that drug 2 has the highest of lying HOMO, electrophilicity index, basicity, and dipole moment. All these parameters could share with different extent to significantly affect the binding affinity of these drugs with the active protein sites.

Potential of Plant Bioactive Compounds as SARS-CoV-2 Main Protease (Mpro) and Spike (S) Glycoprotein Inhibitors: A Molecular Docking Study.

Abstract: Since the outbreak of the COVID-19 (coronavirus disease 19) pandemic, researchers have been trying to investigate several active compounds found in plants that have the potential to inhibit the proliferation of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). The present study aimed to evaluate bioactive compounds found in plants using a molecular docking approach to inhibit the main protease (Mpro) and spike (S) glycoprotein of SARS-CoV-2. The evaluation was performed on the docking scores calculated using AutoDock Vina (AV) as a docking engine. A rule of five (Ro5) was calculated to determine whether a compound meets the criteria as an active drug orally in humans. The determination of the docking score was performed by selecting the best conformation of the protein-ligand complex that had the highest affinity (most negative Gibbs’ free energy of binding/ ). As a comparison, nelfinavir (an antiretroviral drug), chloroquine, and hydroxychloroquine sulfate (antimalarial drugs recommended by the FDA as emergency drugs) were used. The results showed that hesperidin, nabiximols, pectolinarin, epigallocatechin gallate, and rhoifolin had better poses than nelfinavir, chloroquine, and hydroxychloroquine sulfate as spike glycoprotein inhibitors. Hesperidin, rhoifolin, pectolinarin, and nabiximols had about the same pose as nelfinavir but were better than chloroquine and hydroxychloroquine sulfate as Mpro inhibitors. This finding implied that several natural compounds of plants evaluated in this study showed better binding free energy compared to nelfinavir, chloroquine, and hydroxychloroquine sulfate, which so far are recommended in the treatment of COVID-19. From quantum chemical DFT calculations, the ascending order of chemical reactivity of selected compounds was pectolinarin > hesperidin > rhoifolin > morin > epigallocatechin gallate. All isolated compounds’ C=O regions are preferable for an electrophilic attack, and O-H regions are suitable for a nucleophilic attack. Furthermore, Homo-Lumo and global descriptor values indicated a satisfactory remarkable profile for the selected compounds. As judged by the RO5 and previous study by others, the compounds kaempferol, herbacetin, eugenol, and 6-shogaol have good oral bioavailability, so they are also seen as promising candidates for the development of drugs to treat infections caused by SARS-CoV-2. The present study identified plant-based compounds that can be further investigated in vitro and in vivo as lead compounds against SARS-CoV-2.

Highly Flexible Ligand Docking: Benchmarking of the DockThor Program on the LEADS-PEP Protein-Peptide Data Set.

Abstract: Protein-peptide interactions play a crucial role in many cellular and biological functions, which justify the increasing interest in the development of peptide-based drugs. However, predicting experimental binding modes and affinities in protein-peptide docking remains a great challenge for most docking programs due to some particularities of this class of ligands, such as the high degree of flexibility. In this paper, we present the performance of the DockThor program on the LEADS-PEP data set, a benchmarking set composed of 53 diverse protein-peptide complexes with peptides ranging from 3 to 12 residues and with up to 51 rotatable bonds. The DockThor performance for pose prediction on redocking studies was compared with some state-of-the-art docking programs that were also evaluated on the LEADS-PEP data set, AutoDock, AutoDock Vina, Surflex, GOLD, Glide, rDock, and DINC, as well as with the task-specific docking protocol HPepDock. Our results indicate that DockThor could dock 40% of the cases with an overall backbone RMSD below 2.5 A when the top-scored docking pose was considered, exhibiting similar results to Glide and outperforming other protein-ligand docking programs, whereas rDock and HPepDock achieved superior results. Assessing the docking poses closest to the crystal structure (i.e., best-RMSD pose), DockThor achieved a success rate of 60% in pose prediction. Due to the great overall performance of handling peptidic compounds, the DockThor program can be considered as suitable for docking highly flexible and challenging ligands, with up to 40 rotatable bonds. DockThor is freely available as a virtual screening Web server at https://www.dockthor.lncc.br/ .

Potential bioactive glycosylated flavonoids as SARS-CoV-2 main protease inhibitors: A molecular docking and simulation studies.

Abstract: 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.

Potential Therapeutic Agents for COVID-19 Based on the Analysis of Protease and RNA Polymerase Docking

Abstract: The outbreak of novel coronavirus (COVID-19) infections in 2019 is in dire need of finding potential therapeutic agents. In this study, we used molecular docking to repurpose HIV protease inhibitors and nucleoside analogues for COVID-19, with evaluations based on docking scores calculated by AutoDock Vina and RosettaCommons. Our results suggest that Indinavir and Remdesivir possess the best docking scores, and comparison of the docking sites of the two drugs reveal a near perfect dock in the overlapping region of the protein pockets. After further investigation of the functional regions inferred from the proteins of SARS coronavirus, we discovered that Indinavir does not dock on any active sites of the protease, which may give rise to concern in regards to the efficacy of Indinavir. On the other hand, the docking site of Remdesivir is not compatible with any known functional regions, including template binding motifs, polymerization motifs and nucleoside triphosphate (NTP) binding motifs. However, when we tested the active form (CHEMBL2016761) of Remdesivir, the docking site revealed a perfect dock in the overlapping region of the NTP binding motif. This result suggests that Remdesivir could be a potential therapeutic agent. Clinical trials still must be done in order to confirm the curative effect of these drugs. Introduction In the concluding weeks of 2019, an outbreak of novel coronavirus (COVID-19) infections occurred in Wuhan, China. As of February 25, 2020, more than 80,000 cases and 2,700 deaths have been reported. With no proven antiviral agent available, medical professionals have resorted to supportive care to contain the infection. However, current research now suggests that certain drugs with the appropriate viral restraining mechanisms can yield promising results. At the Rajavithi Hospital in Thailand, the infectious disease team used a combination of Oseltamivir (anti-influenza agent) and Lopinavir/Ritonavir (anti-HIV agent) to successfully improve patients with severe conditions. Lopinavir and Ritonavir are both HIV protease inhibitors that suppress the cleaving of a polyprotein into multiple functional proteins1. Likewise, various clinical trials are also Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 29 February 2020 © 2020 by the author(s). Distributed under a Creative Commons CC BY license. doi:10.20944/preprints202002.0242.v2

Small‐molecule inhibitors of METTL3, the major human epitranscriptomic writer

Abstract: The RNA methylase METTL3 catalyzes the transfer of a methyl group from the cofactor S-adenosyl-L-methionine (SAM) to the N6 atom of adenine. We have screened a library of 4000 analogues and derivatives of the adenosine moiety of SAM by high-throughput docking into METTL3. Two series of adenine derivatives were identified in silico, and the binding mode of six of the predicted inhibitors was validated by protein crystallography. Two compounds, one for each series, show good ligand efficiency. We propose a route for their further development into potent and selective inhibitors of METTL3.

Targeting SARS-CoV-2 Spike Protein of COVID-19 with Naturally Occurring Phytochemicals: An in Silco Study for Drug Development

Abstract: Spike glycoprotein found on the surface of SARS-CoV-2 (SARS-CoV-2S) is a class I fusion protein which helps the virus in its initial attachment with human Angiotensin converting enzyme 2 (ACE2) receptor and its consecutive fusion with the host cells. The attachment is mediated by the S1 subunit of the protein via its receptor binding domain. Upon binding with the receptor the protein changes its conformation from a pre-fusion to a post-fusion form. The membrane fusion and internalization of the virus is brought about by the S2 domain of the spike protein. From ancient times people have relied on naturally occurring substances like phytochemicals to fight against diseases and infection. Among these phytochemicals, flavonoids and non-flavonoids have been found to be the active source of different anti-microbial agents. Recently, studies have shown that these phytochemicals have essential anti-viral activities. We performed a molecular docking study using 10 potential naturally occurring flavonoids/non-flavonoids against the SARS-CoV-2 spike protein and compared their affinity with the FDA approved drug hydroxychloroquine (HCQ). Interestingly, the docking analysis suggested that C-terminal of S1 domain and S2 domain of the spike protein are important for binding with these compounds. Kamferol, curcumin, pterostilbene, and HCQ interact with the C-terminal of S1 domain with binding energies of -7.4, -7.1, -6.7 and -5.6 Kcal/mol, respectively. Fisetin, quercetin, isorhamnetin, genistein, luteolin, resveratrol and apigenin on the other hand, interact with the S2 domain of spike protein with the binding energies of -8.5, -8.5, -8.3, -8.2, -8.2, -7.9, -7.7 Kcal/mol, respectively. Our study suggested that, these flavonoid and non-flavonoid moieties have significantly high binding affinity for the two main important domains of the spike protein which is responsible for the attachment and internalization of the virus in the host cell and their binding affinities are much higher compared to that of HCQ. In addition, ADME (absorption, distribution, metabolism and excretion) analysis also suggested that these compounds consist of drug likeness property which may help for further explore as anti-SARS-CoV-2 agents. Further, in vitro and in vivo study of these compounds will provide a clear path for the development of novel compounds that would most likely prevent the receptor binding or internalization of the SARS-CoV-2 spike protein and therefore could be used as drugs for COVID-19 therapy.

Application of MM-PBSA Methods in Virtual Screening

Abstract: Computer-aided drug design techniques are today largely applied in medicinal chemistry. In particular, receptor-based virtual screening (VS) studies, in which molecular docking represents the gold standard in silico approach, constitute a powerful strategy for identifying novel hit compounds active against the desired target receptor. Nevertheless, the need for improving the ability of docking in discriminating true active ligands from inactive compounds, thus boosting VS hit rates, is still pressing. In this context, the use of binding free energy evaluation approaches can represent a profitable tool for rescoring ligand-protein complexes predicted by docking based on more reliable estimations of ligand-protein binding affinities than those obtained with simple scoring functions. In the present review, we focused our attention on the Molecular Mechanics-Poisson Boltzman Surface Area (MM-PBSA) method for the calculation of binding free energies and its application in VS studies. We provided examples of successful applications of this method in VS campaigns and evaluation studies in which the reliability of this approach has been assessed, thus providing useful guidelines for employing this approach in VS.

In silico identification of potential inhibitors of key SARS-CoV-2 3CL hydrolase (Mpro) via molecular docking, MMGBSA predictive binding energy calculations, and molecular dynamics simulation.

Abstract: The incidence of 2019 novel corona virus (SARS-CoV-2) has created a medical emergency throughout the world. Various efforts have been made to develop the vaccine or effective treatments against the disease. The discovery of crystal structure of SARS-CoV-2 main protease has made the in silico identification of its inhibitors possible. Based on its critical role in viral replication, the viral protease can prove to be a promising "target" for antiviral drug therapy. We have systematically screened an in-house library of 15,754 natural and synthetic compounds, established at International Center for Chemical and Biological Sciences, University of Karachi. The in silico search for potential viral protease inhibitors resulted in nine top ranked ligands (compounds 1-9) against SARS-CoV-2 main protease (PDB ID: 6LU7) based on docking scores, and predictive binding energies. The in silico studies were updated via carrying out the docking, and predictive binding energy estimation, with a recently reported crystal structure of main protease (PDB ID: 6Y2F) at a better resolution i.e., 1.95 A. Compound 2 (molecular bank code AAA396) was found to have highest negative binding energy of -71.63 kcal/mol for 6LU7. While compound 3 (molecular bank code AAD146) exhibited highest negative binding energy of -81.92 kcal/mol for 6Y2F. The stability of the compounds- in complex with viral protease was analyzed by Molecular Dynamics simulation studies, and was found to be stable over the course of 20 ns simulation time. Compound 2, and 3 were predicted to be the significant inhibitors of SARS-CoV-2 3CL hydrolase (Mpro) among the nine short listed compounds.

Discovery of New Hydroxyethylamine Analogs Against 3CLpro Protein Target of SARS-CoV-2: Molecular Docking, Molecular Dynamics Simulation and Structure-Activity Relationship Studies

Abstract: The novel coronavirus, SARS-CoV-2, has caused a recent pandemic called COVID-19 and a severe health threat around the world. In the current situation, the virus is rapidly spreading worldwide, and the discovery of a vaccine and potential therapeutics are critically essential. The crystal structure for the main protease (Mpro) of SARS-CoV-2, 3-chymotrypsin-like cysteine protease (3CLpro), was recently made available and is considerably similar to the previously reported SARS-CoV. Due to its essentiality in viral replication, it represents a potential drug target. Herein, a computer-aided drug design (CADD) approach was implemented for the initial screening of 13 approved antiviral drugs. Molecular docking of 13 antivirals against the 3-chymotrypsin-like cysteine protease (3CLpro) enzyme was accomplished, and indinavir was described as a lead drug with a docking score of -8.824 and a XP Gscore of -9.466 kcal/mol. Indinavir possesses an important pharmacophore, hydroxyethylamine (HEA), and thus, a new library of HEA compounds (>2500) was subjected to virtual screening that led to 25 hits with a docking score more than indinavir. Exclusively, compound 16 with a docking score of -8.955 adhered to drug-like parameters, and the structure-activity relationship (SAR) analysis was demonstrated to highlight the importance of chemical scaffolds therein. Molecular dynamics (MD) simulation analysis performed at 100 ns supported the stability of 16 within the binding pocket. Largely, our results supported that this novel compound 16 binds with domains I and II, and the domain II-III linker of the 3CLpro protein, suggesting its suitability as a strong candidate for therapeutic discovery against COVID-19.

Anti-HIV drug repurposing against SARS-CoV-2

Abstract: A novel severe acute respiratory syndrome human coronavirus (SARS HCoV) was identified from respiratory illness patients (named SARS-CoV-2 by ICTV) in December 2019 and has recently emerged as a serious threat to world public health. However, no approved drugs have been found to effectively inhibit the virus. Since it has been reported that HIV protease inhibitors can be used as anti-SARS drugs by targeting SARS-CoV-1 3CLpro, we chose six approved anti-HIV drugs and investigated their binding interactions with 3CLpro to evaluate their potential to become clinical drugs for the new coronavirus pneumonia (COVID-19) caused by SARS-CoV-2 infection. The molecular docking results indicate that the 3CLpro of SARS-CoV-2 has a higher binding affinity for all the studied inhibitors than does SARS-CoV-1. Two docking complexes (indinavir and darunavir) with high docking scores were further subjected to MM-PBSA binding free energy calculations to detail the molecular interactions between these two protease inhibitors and SARS HCoV 3CLpro. Our results show that, among the inhibitors tested, darunavir has the highest binding affinity with SARS-CoV-2 and SARS-CoV-1 3CLpro, indicating that it may have the potential to be used as an anti-COVID-19 clinical drug. The mechanism behind the increased binding affinity of HIV protease inhibitors toward SARS-CoV-2 3CLpro (as compared to SARS-CoV-1) was investigated by MD simulations. Our study provides insight into the possible role of structural flexibility during interactions between SARS HCoV 3CLpro and inhibitors and sheds light on structure-based design of anti-COVID-19 drugs targeting SARS-CoV-2 3CLpro.