Antiviral potential of some novel structural analogs of standard drugs repurposed for the treatment of COVID-19 (original) (raw)

Computer-aided screening for potential TMPRSS2 inhibitors: a combination of pharmacophore modeling, molecular docking and molecular dynamics simulation approaches

Journal of Biomolecular Structure and Dynamics

Transmembrane serine protease 2 (TMPRSS2) has been established as one of the host proteins that facilitate entry of coronaviruses into host cells. One of the approaches often employed towards preventing the entry and proliferation of viruses is computer-aided inhibition studies to identify potent compounds that can inhibit activity of viral targets in the host through binding at the active site. In this study, we developed a pharmacophore model of reportedly potent drugs against severe acute respiratory syndrome coronaviruses 1 and 2 (SARS-CoV-1 and-2). The model was used to screen the ZINC database for commercially available compounds having similar features with the experimentally tested drugs. The top 3000 compounds retrieved were docked into the active sites of a homologymodelled TMPRSS2. Docking scores of the top binders were validated and the top-ranked compounds were subjected to ADME, Lipinski's and medicinal Chemistry property predictions for druglikeness analyses. Two lead compounds, ZINC64606047 and ZINC05296775, were identified having binding affinities higher than those of the reference inhibitors, favorable interactions with TMPRSS2 active site residues and good ADME and medicinal chemistry properties. Molecular dynamics simulation was used to assess the stability and dynamics of the interactions of these compounds with TMPRSS2. Binding free energy and contribution energy evaluations were determined using MMPBSA method. Analyses of the trajectory dynamics collectively established further that the lead compounds bound and interacted stably with active site residues of TMPRSS2. Nonetheless, experimental studies are needed to further assess the potentials of these compounds as possible therapeutics against coronaviruses.

Identification of Mpro inhibitors of SARS-CoV-2 using structure based computational drug repurposing

Biocatalysis and Agricultural Biotechnology, 2021

The recent outbreak of COVID-19, caused by the novel pathogen SARS-coronavirus 2 (SARS-CoV-2) is a severe health emergency. In this pandemic, drug repurposing seems to be the most promising alternative to identify effective therapeutic agents for immediate treatment of infected patients. The present study aimed to evaluate all the drugs present in drug bank as potential novel SARS-CoV-2 inhibitors, using computational drug repurposing studies. Docking-based virtual screening and binding energy prediction were performed, followed by Absorption Distribution Metabolism Excretion calculation. Hydroxychloroquine and Nelfinavir have been identified as the best potential inhibitor against the SARS-CoV-2, therefore, they were used as reference compounds in computational DR studies. The docking study revealed 13 best compounds based on their highest binding affinity, binding energy, and dock score concerning the other screened compounds. Out of 13, only 4 compounds were further shortlisted based on their binding energy and best ADME properties. The hierarchical virtual screening yielded the best 04 drugs, DB07042 (compound 2), DB13035 (compound 3), DB13604 (compound 5) and DB08253 (compound 6), with commendable binding energies in kcal/mol, i.e. −65.45, −62.01, −52.09 and −51.70 respectively. Further, Molecular dynamics simulation with 04 best-retrieved hits has confirmed stable trajectories in protein in terms of root mean square deviation and root mean square fluctuation. During 30 ns simulation, the interactions were also found similar to the docking-based studies. However, clinical studies are necessary to investigate their therapeutic use against this outbreak.

Molecular docking, validation, dynamics simulations, and pharmacokinetic prediction of natural compounds against the SARS-CoV-2 main-protease

Journal of Biomolecular Structure and Dynamics

The study aims to evaluate the potency of two hundred natural antiviral phytocompounds against the active site of the Severe Acquired Respiratory Syndrome-Coronavirus À 2 (SARS-CoV-2) Main-Protease (M pro) using AutoDock 4.2.6. The three-dimensional crystal structure of the M pro (PDB Id: 6LU7) was retrieved from the Protein Data Bank (PDB), the active site was predicted using MetaPocket 2.0. Food and Drug Administration (FDA) approved viral protease inhibitors were used as standards for comparison of results. The compounds theaflavin-3-3'-digallate, rutin, hypericin, robustaflavone, and (-)-solenolide A with respective binding energy of À12.41 (Ki ¼ 794.96 pM); À11.33 (Ki ¼ 4.98 nM); À11.17 (Ki ¼ 6.54 nM); À10.92 (Ki ¼ 9.85 nM); and À10.82 kcal/mol (Ki ¼ 11.88 nM) were ranked top as Coronavirus Disease À 2019 (COVID-19) M pro inhibitors. The interacting amino acid residues were visualized using Discovery Studio 3.5 to elucidate the 2-dimensional and 3-dimensional interactions. The study was validated by i) re-docking the N3-peptide inhibitor-M pro and superimposing them onto co-crystallized complex and ii) docking decoy ligands to M pro. The ligands that showed low binding energy were further predicted for and pharmacokinetic properties and Lipinski's rule of 5 and the results are tabulated and discussed. Molecular dynamics simulations were performed for 50 ns for those compounds using the Desmond package, Schr€ odinger to assess the conformational stability and fluctuations of protein-ligand complexes during the simulation. Thus, the natural compounds could act as a lead for the COVID-19 regimen after in-vitro and in-vivo clinical trials.

Virtual screening, molecular dynamics and structure–activity relationship studies to identify potent approved drugs for Covid-19 treatment

Journal of Biomolecular Structure and Dynamics

Computer-aided drug screening by molecular docking, molecular dynamics (MD) and structural-activity relationship (SAR) can offer an efficient approach to identify promising drug repurposing candidates for COVID-19 treatment. In this study, computational screening is performed by molecular docking of 1615 Food and Drug Administration (FDA) approved drugs against the main protease (Mpro) of SARS-CoV-2. Several promising approved drugs, including Simeprevir, Ergotamine, Bromocriptine and Tadalafil, stand out as the best candidates based on their binding energy, fitting score and noncovalent interactions at the binding sites of the receptor. All selected drugs interact with the key active site residues, including His41 and Cys145. Various noncovalent interactions including hydrogen bonding, hydrophobic interactions, pi-sulfur and pi-pi interactions appear to be dominant in drug-Mpro complexes. MD simulations are applied for the most promising drugs. Structural stability and compactness are observed for the drug-Mpro complexes. The protein shows low flexibility in both apo and holo form during MD simulations. The MM/PBSA binding free energies are also measured for the selected drugs. For pattern recognition, structural similarity and binding energy prediction, multiple linear regression (MLR) models are used for the quantitative structural-activity relationship. The binding energy predicted by MLR model shows an 82% accuracy with the binding energy determined by molecular docking. Our details results can facilitate rational drug design targeting the SARS-CoV-2 main protease.

In silico Drug Repurposing of Anticancer Drug 5-FU and Analogues Against SARS-CoV-2 Main Protease: Molecular Docking, Molecular Dynamics Simulation, Pharmacokinetics and Chemical Reactivity Studies

Advances and Applications in Bioinformatics and Chemistry

Background: Since the last COVID-19 outbreak, several approaches have been given a try to quickly tackle this global calamity. One of the well-established strategies is the drug repurposing, which consists in finding new therapeutic uses for approved drugs. Following the same paradigm, we report in the present study, an investigation of the potential inhibitory activity of 5-FU and nineteen of its analogues against the SARS-CoV-2 main protease (3CLpro). Material and Methods: Molecular docking calculations were performed to investigate the binding affinity of the ligands within the active site of 3CLpro. The best binding candidates were further considered for molecular dynamics simulations for 100 ns to gain a time-resolved understanding of the behavior of the guest-host complexes. Furthermore, the profile of druggability of the best binding ligands was assessed based on ADMET predictions. Finally, their chemical reactivity was elucidated using different reactivity descriptors, namely the molecular electrostatic potential (MEP), Fukui functions and frontier molecular orbitals. Results and Discussion: From the calculations performed, four candidates (compounds 14, 15, 16 and 18) show promising results with respect to the binding affinity to the target protease, 3CLpro, the therapeutic profile of druggability and safety. These compounds are maintained inside the active site of 3CLpro thanks to a variety of noncovalent interactions, especially hydrogen bonds, involving important amino acids such as GLU166, HIS163, GLY143, ASN142, HIS172, CYS145. Molecular dynamics simulations suggest that the four ligands are well trapped within the active site of the protein over a time gap of 100 ns, ligand 18 being the most retained. Conclusion: In line with the findings reported herein, we recommend that further in-vitro and in-vivo investigations are carried out to shed light on the possible mechanism of pharmacological action of the proposed ligands.

Combined drug repurposing and virtual screening strategies with molecular dynamics simulation identified potent inhibitors for SARS-CoV-2 main protease (3CLpro)

Journal of Biomolecular Structure and Dynamics, 2020

The current coronavirus (SARS-COV-2) pandemic and phenomenal spread to every nook and cranny of the world has raised major apprehensions about the modern public health care system. So far as a result of this epidemic, 4,434,653 confirmed cases and 302,169 deaths are reported. The growing infection rate and death toll demand the use of all possible approaches to design novel drugs and vaccines to curb this disease. In this study, we combined drugs repurposing and virtual drug screening strategies to target 3CLpro, which has an essential role in viral maturation and replication. A total of 31 FDA approved anti-HIV drugs, and Traditional Chinese medicines (TCM) database were screened to find potential inhibitors. As a result, Saquinavir, and five drugs (TCM5280805, TCM5280445, TCM5280343, TCM5280863, and TCM5458190) from the TCM database were found as promising hits. Furthermore, results from molecular dynamics simulation and total binding free energy revealed that Saquinavir and TCM5280805 target the catalytic dyad (His41 and Cys145) and possess stable dynamics behavior. Thus, we suggest that these compounds should be tested experimentally against the SARS-COV-2 as Saquinavir has been reported to inhibit HIV protease experimentally. Considering the intensity of coronavirus dissemination, the present research is in line with the idea of discovering the latest inhibitors against the coronavirus essential pathways to accelerate the drug development cycle.

Repositioning Therapeutics for COVID-19: Virtual Screening of the Potent Synthetic and Natural Compounds as SARS-CoV-2 3CLpro Inhibitors

Today, finding potential therapeutics for COVID-19 caused by the widespread transmission of SARS-CoV-2 has become a global challenge. Molecular docking investigation of the therapeutic potential of marketed drugs is a fast and cost effective approach to provide a solution to this problem. In this study, docking simulations performed on the reported structure of the virus main protease, 3CLpro, to identify potential inhibitors. Accordingly, a database of 50 synthetic compounds including approved drugs and those undergoing clinical trials, and 40 natural compounds particularly those employed in traditional Iranian medicine was constructed. The results indicated that the anti-inflammatory drugs, Licofelone acyl glucuronide and delta-bilirubin, and natural compounds such as kappa-carrageenan conformer and beta-D-galactopyranosyl with minimal side-effects, according to in-vitro studies, are good candidates to block the enzymatic activity of SARS-CoV-2 3CLpro. Moreover, the compound 1 cou...

Identification of Severe Acute Respiratory Syndrome Coronavirus‐2 inhibitors through in silico structure‐based virtual screening and molecular interaction studies

Journal of Molecular Recognition, 2021

The novel coronavirus Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 has caused a worldwide pandemic. The fatal virus has affected the health of human beings as well as the socioeconomic situation all over the world. To date, no concrete medicinal solution has been proposed to combat the viral infection, calling for an urgent, strategic, and cost-effective drug development approach that may be achievable by applying targeted computational and virtual screening protocols. Immunity is the body's natural defense against disease-causing pathogens, which can be boosted by consuming plant-based or natural food products. Active constituents derived from natural sources also scavenge the free radicals and have anti-inflammatory activities. Herbs and spices have been used for various medicinal purposes. In this study, 2,96 365 natural and synthetic derivatives (ligands) belonging to 102 classes of compounds were obtained from PubChem and assessed on Lipinski's parameters for their potential bioavailability. Out of all the derivatives, 3254 obeyed Lipinski's rule and were virtually screened. The 115 top derivatives were docked against SARS-CoV-2, SARS-CoV, MERS-CoV, and HCoV-HKV1 main proteases (M pro s) as receptors using AutoDock Vina, AutoDock, and iGEMDOCK 2.1. The lowest binding energy was exhibited by ligands 2 and 6 against all the four M pro s. The molecular dynamic simulation was also performed with ligand 6 using the GROMACS package. Good bioactivity scores, absorption, distribution, metabolism, excretion, and toxicity profile and drug-like pharmacokinetic parameters were also obtained. Hydroxychloroquine was used as the control drug.

Molecular Dynamics Simulation of Bioactive Compounds Against Six Protein Target of Sars-Cov-2 As Covid-19 Antivirus Candidates

Jurnal Kimia Valensi

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the virus that causes Coronavirus 2019 (COVID-19). To date, there has been no proven effective drug for the treatment or prevention of COVID-19. A study on developing inhibitors for this virus was performed using molecular dynamics simulation. 3CL-Pro, PL-Pro, Helicase, N, E, and M protein were used as protein targets. This study aimed to determine the stability of the selected protein-ligand complex through molecular dynamics simulation by Amber20 to propose bioactive compounds from natural products that have potential as a drug for COVID-19. Based on our previous study, the best value of free binding energy and protein-ligand interactions of the candidate compounds are obtained for each target protein through molecular docking. Corilagin (-14.42 kcal/mol), Scutellarein 7-rutinoside (-13.2 kcal/mol), Genistein 7-O-glucuronide (-10.52 kcal/mol), Biflavonoid-flavone base + 3O (-11.88 and -9.61 kcal/mol), and Enoxolone (-...

Structure-Based Virtual Screening, Docking, ADMET, Molecular Dynamics, and MM-PBSA Calculations for the Discovery of Potential Natural SARS-CoV-2 Helicase Inhibitors from the Traditional Chinese Medicine

Journal of Chemistry

Continuing our antecedent work against COVID-19, a set of 5956 compounds of traditional Chinese medicine have been virtually screened for their potential against SARS-CoV-2 helicase (PDB ID: 5RMM). Initially, a fingerprint study with VXG, the ligand of the target enzyme, disclosed the similarity of 187 compounds. Then, a molecular similarity study declared the most similar 40 compounds. Subsequently, molecular docking studies were carried out to examine the binding modes and energies. Then, the most appropriate 26 compounds were subjected to in silico ADMET and toxicity studies to select the most convenient inhibitors to be: (1R,2S)-ephedrine (57), (1R,2S)-norephedrine (59), 2-(4-(pyrrolidin-1-yl)phenyl)acetic acid (84), 1-phenylpropane-1,2-dione (195), 2-methoxycinnamic acid (246), 2-methoxybenzoic acid (364), (R)-2-((R)-5-oxopyrrolidin-3-yl)-2-phenylacetic acid (405), (Z)-6-(3-hydroxy-4-methoxystyryl)-4-methoxy-2H-pyran-2-one (533), 8-chloro-2-(2-phenylethyl)-5,6,7-trihydroxy-5,6,...