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1.
Molecules ; 27(5)2022 Mar 07.
Article in English | MEDLINE | ID: covidwho-1732131

ABSTRACT

The angiotensin-converting enzyme II (ACE2) is a multifunctional protein in both health and disease conditions, which serves as a counterregulatory component of RAS function in a cardioprotective role. ACE2 modulation may also have relevance to ovarian cancer, diabetes, acute lung injury, fibrotic diseases, etc. Furthermore, since the outbreak of the coronavirus disease in 2019 (COVID-19), ACE2 has been recognized as the host receptor of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The receptor binding domain of the SARS-CoV-2 S-protein has a strong interaction with ACE2, so ACE2 may be a potent drug target to prevent the virus from invading host cells for anti-COVID-19 drug discovery. In this study, structure- and property-based virtual screening methods were combined to filter natural product databases from ChemDiv, TargetMol, and InterBioScreen to find potential ACE2 inhibitors. The binding affinity between protein and ligands was predicted using both Glide SP and XP scoring functions and the MM-GBSA method. ADME properties were also calculated to evaluate chemical drug-likeness. Then, molecular dynamics (MD) simulations were performed to further explore the binding modes between the highest-potential compounds and ACE2. Results showed that the compounds 154-23-4 and STOCK1N-07141 possess potential ACE2 inhibition activities and deserve further study.


Subject(s)
Angiotensin-Converting Enzyme 2/antagonists & inhibitors , Biological Products/chemistry , Protease Inhibitors/chemistry , Angiotensin-Converting Enzyme 2/metabolism , Binding Sites , Biological Products/metabolism , Biological Products/therapeutic use , COVID-19/drug therapy , COVID-19/virology , Databases, Chemical , Humans , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/metabolism , Protease Inhibitors/therapeutic use , Protein Binding , SARS-CoV-2/isolation & purification , Structure-Activity Relationship , Thermodynamics
2.
Eur J Med Res ; 26(1): 152, 2021 Dec 20.
Article in English | MEDLINE | ID: covidwho-1632541

ABSTRACT

BACKGROUND: COVID-19 and its related anti-inflammatory treatment (steroids, immunomodulators) may induce the reactivation of latent bacterial, parasitic, and viral infections. According to our knowledge, no case of disseminated HHV-8-related Kaposi sarcoma (KS) after COVID-19 and its treatment has been described so far. Only one case of cutaneous KS concurrently with COVID-19 has been previously reported. CASE PRESENTATION: We describe a case of disseminated KS in a 61-year-old immunocompetent Albanian man after hospitalization for COVID-19. METHODS FOR LITERATURE RESEARCH: We used PubMed as biomedical database for the literature research. We selected keyword combinations including "Kaposi sarcoma," "HHV-8," "immunocompetent," "COVID-19," "SARS-CoV-2," and "steroids." No time or language limitation was set. Titles and abstracts of selected articles were systematically screened. Articles were included in the examination if they were published under free access through the digital library of the University of Brescia (Italy), and provided full text. Articles were excluded if the topic was beyond the aim of our study. Finally, we selected 15 articles. RESULTS: We describe a case of KS in COVID-19 patient and postulate that Interleukin-6 (IL-6) activity and steroid-induced immunodeficiency may play a major role in KS emergence. No published case of disseminated KS following COVID-19 in otherwise healthy individuals was found through the systematic literature review, despite the high incidence of COVID-19 in areas with medium-high prevalence of HHV-8 infection. This observation might be explained by the role of individual genetic susceptibility factors. CONCLUSIONS: SARS-CoV-2 infection and its treatment may lead to reactivation of several latent infections, including HHV-8 and its related clinical syndrome, Kaposi sarcoma.


Subject(s)
COVID-19/genetics , SARS-CoV-2/genetics , Sarcoma, Kaposi/drug therapy , COVID-19/diagnosis , COVID-19/drug therapy , Databases, Chemical , Humans , Interleukin-6/metabolism , Language , Male , Middle Aged , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , Sarcoma, Kaposi/complications , Sarcoma, Kaposi/genetics
3.
PLoS Comput Biol ; 17(12): e1009675, 2021 12.
Article in English | MEDLINE | ID: covidwho-1619980

ABSTRACT

Identifying the epitope of an antibody is a key step in understanding its function and its potential as a therapeutic. Sequence-based clonal clustering can identify antibodies with similar epitope complementarity, however, antibodies from markedly different lineages but with similar structures can engage the same epitope. We describe a novel computational method for epitope profiling based on structural modelling and clustering. Using the method, we demonstrate that sequence dissimilar but functionally similar antibodies can be found across the Coronavirus Antibody Database, with high accuracy (92% of antibodies in multiple-occupancy structural clusters bind to consistent domains). Our approach functionally links antibodies with distinct genetic lineages, species origins, and coronavirus specificities. This indicates greater convergence exists in the immune responses to coronaviruses than is suggested by sequence-based approaches. Our results show that applying structural analytics to large class-specific antibody databases will enable high confidence structure-function relationships to be drawn, yielding new opportunities to identify functional convergence hitherto missed by sequence-only analysis.


Subject(s)
Antigens, Viral/chemistry , COVID-19/immunology , COVID-19/virology , Epitopes, B-Lymphocyte/chemistry , SARS-CoV-2/chemistry , SARS-CoV-2/immunology , Amino Acid Sequence , Animals , Antibodies, Neutralizing/chemistry , Antibodies, Neutralizing/genetics , Antibodies, Viral/chemistry , Antibodies, Viral/genetics , Antibodies, Viral/metabolism , Antibody Specificity , Antigen-Antibody Complex/chemistry , Antigen-Antibody Complex/genetics , Antigen-Antibody Reactions/genetics , Antigen-Antibody Reactions/immunology , Computational Biology , Coronavirus/chemistry , Coronavirus/genetics , Coronavirus/immunology , Databases, Chemical , Epitope Mapping , Epitopes, B-Lymphocyte/genetics , Humans , Mice , Models, Molecular , Pandemics , SARS-CoV-2/genetics , Single-Domain Antibodies/immunology
4.
Int J Mol Sci ; 23(1)2021 Dec 30.
Article in English | MEDLINE | ID: covidwho-1580695

ABSTRACT

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.


Subject(s)
Antiviral Agents/chemistry , Drug Design/methods , High-Throughput Screening Assays/methods , Protease Inhibitors/chemistry , Protein Interaction Domains and Motifs , SARS-CoV-2/chemistry , Small Molecule Libraries/chemistry , Databases, Chemical , Humans , Molecular Docking Simulation , Protease Inhibitors/metabolism , SARS-CoV-2/metabolism
5.
J Comput Biol ; 28(12): 1228-1247, 2021 12.
Article in English | MEDLINE | ID: covidwho-1545879

ABSTRACT

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was used to screen the antiviral molecules from two antiviral libraries (Life Chemicals [LC] and ASINEX) against RdRP. Here, we report six antiviral molecules (F3407-4105, F6523-2250, F6559-0746 from LC and BDG 33693278, BDG 33693315, LAS 34156196 from ASINEX), which show substantial interactions with key amino acid residues of the active site of SARS-CoV-2 RdRP and exhibit higher binding affinity (>7.5 kcalmol-1) than Galidesivir, an Food and Drug Administration-approved inhibitor of the same. Further, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area results confirmed that identified molecules with RdRP formed higher stable RdRP-inhibitor(s) complex than RdRP-Galidesvir complex. Our findings suggest that these molecules could be potential inhibitors of SARS-CoV-2 RdRP. However, further in vitro and preclinical experiments would be required to validate these potential inhibitors of SARS-CoV-2 protein.


Subject(s)
Antiviral Agents/pharmacology , COVID-19/drug therapy , Computational Chemistry/methods , Coronavirus RNA-Dependent RNA Polymerase/antagonists & inhibitors , Drug Discovery/methods , Drug Evaluation, Preclinical/methods , Pandemics , SARS-CoV-2/drug effects , Amino Acid Motifs , Amino Acid Sequence , Antiviral Agents/chemistry , Antiviral Agents/pharmacokinetics , Catalytic Domain/drug effects , Coronavirus RNA-Dependent RNA Polymerase/chemistry , Databases, Chemical , Molecular Docking Simulation , Molecular Dynamics Simulation , Molecular Structure , Protein Binding , Protein Conformation , SARS-CoV-2/enzymology , Sequence Alignment , Sequence Homology, Amino Acid , Small Molecule Libraries
6.
J Nat Prod ; 84(11): 3001-3007, 2021 11 26.
Article in English | MEDLINE | ID: covidwho-1483081

ABSTRACT

The pressing need for SARS-CoV-2 controls has led to a reassessment of strategies to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. This review article addresses how contemporary approaches involving computational chemistry, natural product (NP) and protein databases, and mass spectrometry (MS) derived target-ligand interaction analysis can be utilized to expedite the interrogation of NP structures while minimizing the time and expense of extraction, purification, and screening in BioSafety Laboratories (BSL)3 laboratories. The unparalleled structural diversity and complexity of NPs is an extraordinary resource for the discovery and development of broad-spectrum inhibitors of viral genera, including Betacoronavirus, which contains MERS, SARS, SARS-CoV-2, and the common cold. There are two key technological advances that have created unique opportunities for the identification of NP prototypes with greater efficiency: (1) the application of structural databases for NPs and target proteins and (2) the application of modern MS techniques to assess protein-ligand interactions directly from NP extracts. These approaches, developed over years, now allow for the identification and isolation of unique antiviral ligands without the immediate need for BSL3 facilities. Overall, the goal is to improve the success rate of NP-based screening by focusing resources on source materials with a higher likelihood of success, while simultaneously providing opportunities for the discovery of novel ligands to selectively target proteins involved in viral infection.


Subject(s)
Antiviral Agents/pharmacology , Betacoronavirus/drug effects , Biological Products/pharmacology , Drug Discovery , Computational Biology , Databases, Chemical , Databases, Protein , Ligands , Mass Spectrometry , Protein Interaction Mapping , SARS-CoV-2/drug effects
7.
Molecules ; 26(20)2021 Oct 14.
Article in English | MEDLINE | ID: covidwho-1470936

ABSTRACT

The SARS-CoV-2 virus is highly contagious to humans and has caused a pandemic of global proportions. Despite worldwide research efforts, efficient targeted therapies against the virus are still lacking. With the ready availability of the macromolecular structures of coronavirus and its known variants, the search for anti-SARS-CoV-2 therapeutics through in silico analysis has become a highly promising field of research. In this study, we investigate the inhibiting potentialities of triazole-based compounds against the SARS-CoV-2 main protease (Mpro). The SARS-CoV-2 main protease (Mpro) is known to play a prominent role in the processing of polyproteins that are translated from the viral RNA. Compounds were pre-screened from 171 candidates (collected from the DrugBank database). The results showed that four candidates (Bemcentinib, Bisoctrizole, PYIITM, and NIPFC) had high binding affinity values and had the potential to interrupt the main protease (Mpro) activities of the SARS-CoV-2 virus. The pharmacokinetic parameters of these candidates were assessed and through molecular dynamic (MD) simulation their stability, interaction, and conformation were analyzed. In summary, this study identified the most suitable compounds for targeting Mpro, and we recommend using these compounds as potential drug molecules against SARS-CoV-2 after follow up studies.


Subject(s)
Antiviral Agents/chemistry , Coronavirus 3C Proteases/antagonists & inhibitors , Protease Inhibitors/chemistry , SARS-CoV-2/enzymology , Triazoles/chemistry , Antiviral Agents/metabolism , Antiviral Agents/therapeutic use , Benzocycloheptenes/chemistry , Benzocycloheptenes/metabolism , Binding Sites , COVID-19/drug therapy , COVID-19/virology , Coronavirus 3C Proteases/metabolism , Databases, Chemical , Half-Life , Humans , Ligands , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/metabolism , Protease Inhibitors/therapeutic use , Protein Binding , Quantitative Structure-Activity Relationship , SARS-CoV-2/isolation & purification , Triazoles/metabolism , Triazoles/therapeutic use
8.
Int J Mol Sci ; 22(20)2021 Oct 15.
Article in English | MEDLINE | ID: covidwho-1470891

ABSTRACT

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new pathogen from the family of Coronaviridae that caused a global pandemic of COVID-19 disease. In the absence of effective antiviral drugs, research of novel therapeutic targets such as SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) becomes essential. This viral protein is without a human counterpart and thus represents a unique prospective drug target. However, in vitro biological evaluation testing on RdRp remains difficult and is not widely available. Therefore, we prepared a database of commercial small-molecule compounds and performed an in silico high-throughput virtual screening on the active site of the SARS-CoV-2 RdRp using ensemble docking. We identified a novel thioether-amide or guanidine-linker class of potential RdRp inhibitors and calculated favorable binding free energies of representative hits by molecular dynamics simulations coupled with Linear Interaction Energy calculations. This innovative procedure maximized the respective phase-space sampling and yielded non-covalent inhibitors representing small optimizable molecules that are synthetically readily accessible, commercially available as well as suitable for further biological evaluation and mode of action studies.


Subject(s)
Antiviral Agents/chemistry , Enzyme Inhibitors/chemistry , RNA-Dependent RNA Polymerase/antagonists & inhibitors , SARS-CoV-2/enzymology , Viral Proteins/antagonists & inhibitors , Amides/chemistry , Antiviral Agents/metabolism , Antiviral Agents/therapeutic use , Binding Sites , COVID-19/drug therapy , COVID-19/virology , Catalytic Domain , Databases, Chemical , Drug Design , Enzyme Inhibitors/metabolism , Enzyme Inhibitors/therapeutic use , Guanidine/chemistry , Humans , Molecular Docking Simulation , Molecular Dynamics Simulation , RNA-Dependent RNA Polymerase/metabolism , SARS-CoV-2/isolation & purification , Structure-Activity Relationship , Sulfides/chemistry , Thermodynamics , Viral Proteins/metabolism
9.
Expert Rev Clin Pharmacol ; 14(10): 1305-1315, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1322577

ABSTRACT

BACKGROUND: The high transmission and pathogenicity of SARS-CoV-2 has led to a pandemic that has halted the world's economy and health. The newly evolved strains and scarcity of vaccines has worsened the situation. The main protease (Mpro) of SARS-CoV-2 can act as a potential target due to its role in viral replication and conservation level. METHODS: In this study, we have enlisted more than 1100 phytochemicals from Asian plants based on deep literature mining. The compounds library was screened against the Mpro of SARS-CoV-2. RESULTS: The selected three ligands, Flemichin, Delta-Oleanolic acid, and Emodin 1-O-beta-D-glucoside had a binding energy of -8.9, -8.9, -8.7 KJ/mol respectively. The compounds bind to the active groove of the main protease at; Cys145, Glu166, His41, Met49, Pro168, Met165, Gln189. The multiple descriptors from the simulation study; root mean square deviation, root mean square fluctuation, radius of gyration, hydrogen bond, solvent accessible surface area confirms the stable nature of the protein-ligand complexes. Furthermore, post-md analysis confirms the rigidness in the docked poses over the simulation trajectories. CONCLUSIONS: Our combinatorial drug design approaches may help researchers to identify suitable drug candidates against SARS-CoV-2.


Subject(s)
Antiviral Agents/pharmacology , Drug Discovery , Phytochemicals/pharmacology , SARS-CoV-2/enzymology , Viral Proteases/metabolism , Antiviral Agents/chemistry , Databases, Chemical , Gene Expression Regulation, Viral/drug effects , Molecular Docking Simulation , Molecular Structure , Phytochemicals/chemistry , Viral Proteases/genetics
10.
Future Med Chem ; 13(16): 1353-1366, 2021 08.
Article in English | MEDLINE | ID: covidwho-1282697

ABSTRACT

Background: The new coronavirus pandemic has had a significant impact worldwide, and therapeutic treatment for this viral infection is being strongly pursued. Efforts have been undertaken by medicinal chemists to discover molecules or known drugs that may be effective in COVID-19 treatment - in particular, targeting the main protease (Mpro) of the virus. Materials & methods: We have employed an innovative strategy - application of ligand- and structure-based virtual screening - using a special compilation of an approved and diverse set of SARS-CoV-2 crystallographic complexes that was recently published. Results and conclusion: We identified seven drugs with different original indications that might act as potential Mpro inhibitors and may be preferable to other drugs that have been repurposed. These drugs will be experimentally tested to confirm their potential Mpro inhibition and thus their effectiveness against COVID-19.


Subject(s)
Antiviral Agents/chemistry , COVID-19/drug therapy , Protease Inhibitors/chemistry , SARS-CoV-2/drug effects , Small Molecule Libraries/chemistry , Viral Proteases/metabolism , Antiviral Agents/pharmacology , Databases, Chemical , Drug Evaluation, Preclinical , Humans , Ligands , Molecular Docking Simulation , Molecular Structure , Protease Inhibitors/pharmacology , Protein Binding , Small Molecule Libraries/pharmacology , Structure-Activity Relationship
11.
Molecules ; 26(12)2021 Jun 21.
Article in English | MEDLINE | ID: covidwho-1282542

ABSTRACT

The discovery of drugs capable of inhibiting SARS-CoV-2 is a priority for human beings due to the severity of the global health pandemic caused by COVID-19. To this end, repurposing of FDA-approved drugs such as NSAIDs against COVID-19 can provide therapeutic alternatives that could be utilized as an effective safe treatment for COVID-19. The anti-inflammatory activity of NSAIDs is also advantageous in the treatment of COVID-19, as it was found that SARS-CoV-2 is responsible for provoking inflammatory cytokine storms resulting in lung damage. In this study, 40 FDA-approved NSAIDs were evaluated through molecular docking against the main protease of SARS-CoV-2. Among the tested compounds, sulfinpyrazone 2, indomethacin 3, and auranofin 4 were proposed as potential antagonists of COVID-19 main protease. Molecular dynamics simulations were also carried out for the most promising members of the screened NSAID candidates (2, 3, and 4) to unravel the dynamic properties of NSAIDs at the target receptor. The conducted quantum mechanical study revealed that the hybrid functional B3PW91 provides a good description of the spatial parameters of auranofin 4. Interestingly, a promising structure-activity relationship (SAR) was concluded from our study that could help in the future design of potential SARS-CoV-2 main protease inhibitors with expected anti-inflammatory effects as well. NSAIDs may be used by medicinal chemists as lead compounds for the development of potent SARS-CoV-2 (Mpro) inhibitors. In addition, some NSAIDs can be selectively designated for treatment of inflammation resulting from COVID-19.


Subject(s)
Anti-Inflammatory Agents, Non-Steroidal/chemistry , Anti-Inflammatory Agents, Non-Steroidal/therapeutic use , COVID-19/drug therapy , Drug Repositioning/methods , Anti-Inflammatory Agents, Non-Steroidal/metabolism , Antiviral Agents/chemistry , Antiviral Agents/pharmacology , Auranofin/chemistry , Auranofin/pharmacology , Binding Sites , COVID-19/complications , Computational Biology , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/chemistry , Cytokine Release Syndrome/drug therapy , Cytokine Release Syndrome/etiology , Databases, Chemical , Humans , Indomethacin/chemistry , Indomethacin/pharmacology , Ligands , Models, Molecular , Molecular Docking Simulation , Molecular Dynamics Simulation , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , Protein Binding , SARS-CoV-2/chemistry , SARS-CoV-2/drug effects , Structure-Activity Relationship , Sulfinpyrazone/chemistry , Sulfinpyrazone/pharmacology , United States , United States Food and Drug Administration
12.
J Pharm Pharm Sci ; 24: 277-291, 2021.
Article in English | MEDLINE | ID: covidwho-1262713

ABSTRACT

PURPOSE: Remdesivir, a drug originally developed against Ebola virus, is currently recommended for patients hospitalized with coronavirus disease of 2019 (COVID-19). In spite of United States Food and Drug Administration's recent assent of remdesivir as the only approved agent for COVID-19, there is limited information available about the physicochemical, metabolism, transport, pharmacokinetic (PK), and drug-drug interaction (DDI) properties of this drug. The objective of this in silico simulation work was to simulate the biopharmaceutical and DDI behavior of remdesivir and characterize remdesivir PK properties in special populations which are highly affected by COVID-19. METHODS: The Spatial Data File format structures of remdesivir prodrug (GS-5734) and nucleoside core (GS-441524) were obtained from the PubChem database to upload into the GastroPlus software 9.8 version (Simulations Plus Inc., USA). The Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) Predictor and PKPlus modules of GastroPlus were used to simulate physicochemical and PK properties, respectively, in healthy and predisposed patients. Physiologically based pharmacokinetic (PBPK) modeling of GastroPlus was used to simulate different patient populations based on age, weight, liver function, and renal function status. Subsequently, these data were used in the Drug-Drug Interaction module to simulate drug interaction potential of remdesivir with other COVID-19 drug regimens and with agents used for comorbidities. RESULTS: Remdesivir nucleoside core (GS-441524) is more hydrophilic than the inactive prodrug (GS-5734) with nucleoside core demonstrating better water solubility. GS-5734, but not GS-441524, is predicted to be metabolized by CYP3A4. Remdesivir is bioavailable and its clearance is achieved through hepatic and renal routes. Differential effects of renal function, liver function, weight, or age were observed on the PK profile of remdesivir. DDI simulation study of remdesivir with perpetrator drugs for comorbidities indicate that carbamazepine, phenytoin, amiodarone, voriconazole, diltiazem, and verapamil have the potential for strong interactions with victim remdesivir, whereas agents used for COVID-19 treatment such as chloroquine and ritonavir can cause weak and strong interactions, respectively, with remdesivir. CONCLUSIONS: GS-5734 (inactive prodrug) appears to be a superior remdesivir derivative due to its hepatic stability, optimum hydrophilic/lipophilic balance, and disposition properties. Remdesivir disposition can potentially be affected by different physiological and pathological conditions, and by drug interactions from COVID-19 drug regimens and agents used for comorbidities.


Subject(s)
Adenosine Monophosphate/analogs & derivatives , Alanine/analogs & derivatives , Antiviral Agents/pharmacokinetics , COVID-19/drug therapy , Computer Simulation , Prodrugs/pharmacokinetics , SARS-CoV-2/drug effects , Adenosine/analogs & derivatives , Adenosine Monophosphate/administration & dosage , Adenosine Monophosphate/adverse effects , Adenosine Monophosphate/pharmacokinetics , Alanine/administration & dosage , Alanine/adverse effects , Alanine/pharmacokinetics , Antiviral Agents/administration & dosage , Antiviral Agents/adverse effects , COVID-19/diagnosis , COVID-19/virology , Databases, Chemical , Drug Interactions , Furans/pharmacokinetics , Humans , Prodrugs/administration & dosage , Prodrugs/adverse effects , Pyrroles/pharmacokinetics , Risk Assessment , Risk Factors , SARS-CoV-2/pathogenicity , Triazines/pharmacokinetics
13.
Int J Mol Sci ; 22(8)2021 Apr 12.
Article in English | MEDLINE | ID: covidwho-1178287

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) encodes the papain-like protease (PLpro). The protein not only plays an essential role in viral replication but also cleaves ubiquitin and ubiquitin-like interferon-stimulated gene 15 protein (ISG15) from host proteins, making it an important target for developing new antiviral drugs. In this study, we searched for novel, noncovalent potential PLpro inhibitors by employing a multistep in silico screening of a 15 million compound library. The selectivity of the best-scored compounds was evaluated by checking their binding affinity to the human ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), which, as a deubiquitylating enzyme, exhibits structural and functional similarities to the PLpro. As a result, we identified 387 potential, selective PLpro inhibitors, from which we retrieved the 20 best compounds according to their IC50 values toward PLpro estimated by a multiple linear regression model. The selected candidates display potential activity against the protein with IC50 values in the nanomolar range from approximately 159 to 505 nM and mostly adopt a similar binding mode to the known, noncovalent SARS-CoV-2 PLpro inhibitors. We further propose the six most promising compounds for future in vitro evaluation. The results for the top potential PLpro inhibitors are deposited in the database prepared to facilitate research on anti-SARS-CoV-2 drugs.


Subject(s)
Antiviral Agents/chemistry , Antiviral Agents/metabolism , Coronavirus Papain-Like Proteases/antagonists & inhibitors , Protease Inhibitors/chemistry , Protease Inhibitors/metabolism , SARS-CoV-2/enzymology , Animals , Antiviral Agents/toxicity , Computer Simulation , Crystallography, X-Ray , Databases, Chemical , Databases, Protein , Drug Evaluation, Preclinical , Humans , Inhibitory Concentration 50 , Lethal Dose 50 , Ligands , Mutagenicity Tests , Protease Inhibitors/toxicity , Quantitative Structure-Activity Relationship , Rats , Ubiquitin Thiolesterase/chemistry , Ubiquitin Thiolesterase/metabolism
14.
Glycobiology ; 31(8): 975-987, 2021 09 09.
Article in English | MEDLINE | ID: covidwho-1169667

ABSTRACT

Coronavirus disease 2019 (COVID-19) has spread rapidly throughout the globe. The spectrum of disease is broad but among hospitalized patients with COVID-19, respiratory failure from acute respiratory distress syndrome is the leading cause of mortality. There is an urgent need for an effective treatment. The current focus has been developing novel therapeutics, including antivirals, protease inhibitors, vaccines and targeting the overactive cytokine response with anti-cytokine therapy. The overproduction of early response proinflammatory cytokines results in what has been described as a "cytokine storm" is leading eventually to death when the cells fail to terminate the inflammatory response. Accumulating evidence shows that inflammatory cytokines induce selectin ligands that play a crucial role in the pathogenesis of inflammatory diseases by mediating leukocyte migration from the blood into the tissue. Thus, the selectins and selectin ligands represent a promising therapeutic target for the treatment of COVID-19. In this paper, potential pan-selectin inhibitors were identified employing a virtual screening using a docking procedure. For this purpose, the Asinex and ZINC databases of ligands, including approved drugs, biogenic compounds and glycomimetics, altogether 923,602 compounds, were screened against the P-, L- and E-selectin. At first, the experimentally confirmed inhibitors were docked into all three selectins' carbohydrate recognition domains to assess the suitability of the screening procedure. Finally, based on the evaluation of ligands binding, we propose 10 purchasable pan-selectin inhibitors to develop COVID-19 therapeutics.


Subject(s)
Antiviral Agents/chemistry , Biomimetic Materials/chemistry , COVID-19/drug therapy , Computer Simulation , Databases, Chemical , SARS-CoV-2/chemistry , Selectins/chemistry , Drug Evaluation, Preclinical , Humans , SARS-CoV-2/metabolism
15.
Bioorg Med Chem ; 38: 116119, 2021 05 15.
Article in English | MEDLINE | ID: covidwho-1157155

ABSTRACT

In response to the pandemic caused by SARS-CoV-2, we constructed a hybrid support vector machine (SVM) classification model using a set of publicly posted SARS-CoV-2 pseudotyped particle (PP) entry assay repurposing screen data to identify novel potent compounds as a starting point for drug development to treat COVID-19 patients. Two different molecular descriptor systems, atom typing descriptors and 3D fingerprints (FPs), were employed to construct the SVM classification models. Both models achieved reasonable performance, with the area under the curve of receiver operating characteristic (AUC-ROC) of 0.84 and 0.82, respectively. The consensus prediction outperformed the two individual models with significantly improved AUC-ROC of 0.91, where the compounds with inconsistent classifications were excluded. The consensus model was then used to screen the 173,898 compounds in the NCATS annotated and diverse chemical libraries. Of the 255 compounds selected for experimental confirmation, 116 compounds exhibited inhibitory activities in the SARS-CoV-2 PP entry assay with IC50 values ranged between 0.17 µM and 62.2 µM, representing an enrichment factor of 3.2. These 116 active compounds with diverse and novel structures could potentially serve as starting points for chemistry optimization for COVID-19 drug discovery.


Subject(s)
Antiviral Agents/pharmacology , SARS-CoV-2/drug effects , Support Vector Machine/statistics & numerical data , Virus Internalization/drug effects , Area Under Curve , Databases, Chemical/statistics & numerical data , Drug Repositioning , HEK293 Cells , Humans , Microbial Sensitivity Tests , ROC Curve , Small Molecule Libraries/pharmacology
16.
Molecules ; 26(5)2021 Mar 07.
Article in English | MEDLINE | ID: covidwho-1136523

ABSTRACT

With the emergence and global spread of the COVID-19 pandemic, the scientific community worldwide has focused on search for new therapeutic strategies against this disease. One such critical approach is targeting proteins such as helicases that regulate most of the SARS-CoV-2 RNA metabolism. The purpose of the current study was to predict a library of phytochemicals derived from diverse plant families with high binding affinity to SARS-CoV-2 helicase (Nsp13) enzyme. High throughput virtual screening of the Medicinal Plant Database for Drug Design (MPD3) database was performed on SARS-CoV-2 helicase using AutoDock Vina. Nilotinib, with a docking value of -9.6 kcal/mol, was chosen as a reference molecule. A compound (PubChem CID: 110143421, ZINC database ID: ZINC257223845, eMolecules: 43290531) was screened as the best binder (binding energy of -10.2 kcal/mol on average) to the enzyme by using repeated docking runs in the screening process. On inspection, the compound was disclosed to show different binding sites of the triangular pockets collectively formed by Rec1A, Rec2A, and 1B domains and a stalk domain at the base. The molecule is often bound to the ATP binding site (referred to as binding site 2) of the helicase enzyme. The compound was further discovered to fulfill drug-likeness and lead-likeness criteria, have good physicochemical and pharmacokinetics properties, and to be non-toxic. Molecular dynamic simulation analysis of the control/lead compound complexes demonstrated the formation of stable complexes with good intermolecular binding affinity. Lastly, affirmation of the docking simulation studies was accomplished by estimating the binding free energy by MMPB/GBSA technique. Taken together, these findings present further in silco investigation of plant-derived lead compounds to effectively address COVID-19.


Subject(s)
Methyltransferases/antagonists & inhibitors , Methyltransferases/metabolism , RNA Helicases/antagonists & inhibitors , RNA Helicases/metabolism , SARS-CoV-2/enzymology , Viral Nonstructural Proteins/antagonists & inhibitors , Viral Nonstructural Proteins/metabolism , Antiviral Agents/chemistry , Antiviral Agents/metabolism , Antiviral Agents/pharmacokinetics , Antiviral Agents/toxicity , Binding Sites , Biological Availability , COVID-19/drug therapy , Computational Biology/methods , Databases, Chemical , Drug Design , Humans , Hydrogen Bonding , Methyltransferases/chemistry , Molecular Docking Simulation , Molecular Dynamics Simulation , Phytochemicals/chemistry , Phytochemicals/metabolism , Plants, Medicinal/chemistry , Protein Binding , Protein Domains/drug effects , Pyrimidines/chemistry , Pyrimidines/metabolism , Pyrimidines/pharmacokinetics , Pyrimidines/toxicity , RNA Helicases/chemistry , Structure-Activity Relationship , Thermodynamics , Viral Nonstructural Proteins/chemistry
17.
Molecules ; 26(5)2021 Mar 05.
Article in English | MEDLINE | ID: covidwho-1129757

ABSTRACT

In late 2019, a global pandemic occurred. The causative agent was identified as a member of the Coronaviridae family, called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we present an analysis on the substances identified in the human metabolome capable of binding the active site of the SARS-CoV-2 main protease (Mpro). The substances present in the human metabolome have both endogenous and exogenous origins. The aim of this research was to find molecules whose biochemical and toxicological profile was known that could be the starting point for the development of antiviral therapies. Our analysis revealed numerous metabolites-including xenobiotics-that bind this protease, which are essential to the lifecycle of the virus. Among these substances, silybin, a flavolignan compound and the main active component of silymarin, is particularly noteworthy. Silymarin is a standardized extract of milk thistle, Silybum marianum, and has been shown to exhibit antioxidant, hepatoprotective, antineoplastic, and antiviral activities. Our results-obtained in silico and in vitro-prove that silybin and silymarin, respectively, are able to inhibit Mpro, representing a possible food-derived natural compound that is useful as a therapeutic strategy against COVID-19.


Subject(s)
Antiviral Agents/pharmacology , Coronavirus 3C Proteases/metabolism , Metabolome , Protease Inhibitors/pharmacology , SARS-CoV-2/enzymology , Silymarin/pharmacology , Antiviral Agents/chemistry , Antiviral Agents/metabolism , Binding Sites , COVID-19/drug therapy , Catalytic Domain/drug effects , Computer Simulation , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/chemistry , Databases, Chemical , Drug Discovery , Enzyme Assays , Humans , Ligands , Molecular Docking Simulation , Protease Inhibitors/chemistry , Protease Inhibitors/metabolism , SARS-CoV-2/drug effects , Silymarin/chemistry , Silymarin/metabolism , Software
18.
Molecules ; 26(4)2021 Feb 19.
Article in English | MEDLINE | ID: covidwho-1090312

ABSTRACT

Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC50 values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R2 = 0.897, Q2LOO = 0.854, and Q2ext = 0.876 and complying with all the parameters established in the validation Tropsha's test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC50 value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC50 values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes.


Subject(s)
Antiviral Agents/chemistry , COVID-19/enzymology , Coronavirus 3C Proteases , Cysteine Proteinase Inhibitors/chemistry , Databases, Chemical , Molecular Docking Simulation , Molecular Dynamics Simulation , RNA-Dependent RNA Polymerase , SARS-CoV-2/enzymology , Antiviral Agents/therapeutic use , COVID-19/drug therapy , Coronavirus 3C Proteases/antagonists & inhibitors , Coronavirus 3C Proteases/chemistry , Cysteine Proteinase Inhibitors/therapeutic use , Drug Evaluation, Preclinical , Quantitative Structure-Activity Relationship , RNA-Dependent RNA Polymerase/antagonists & inhibitors , RNA-Dependent RNA Polymerase/chemistry
19.
J Chem Inf Model ; 60(12): 5832-5852, 2020 12 28.
Article in English | MEDLINE | ID: covidwho-1065780

ABSTRACT

We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.


Subject(s)
Antiviral Agents/chemistry , COVID-19/drug therapy , SARS-CoV-2/drug effects , Viral Nonstructural Proteins/chemistry , Artificial Intelligence , Binding Sites , Computer Simulation , Databases, Chemical , Drug Design , Drug Evaluation, Preclinical , Humans , Molecular Docking Simulation , Protein Conformation , Spike Glycoprotein, Coronavirus/chemistry , Structure-Activity Relationship
20.
Molecules ; 26(3)2021 Jan 28.
Article in English | MEDLINE | ID: covidwho-1055086

ABSTRACT

SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, -8.7 kcal/mol), PLpro (binding energy, -7.9 kcal/mol), and Nucleocapsid (binding energy, -7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, -24.42 kcal/mol and MMPBSA, -10.80 kcal/mol), PLpro (MMGBSA, -48.69 kcal/mol and MMPBSA, -38.17 kcal/mol) and Nucleocapsid (MMGBSA, -30.05 kcal/mol and MMPBSA, -25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, -22.44 kcal/mol), PLpro (mean, -25.46 kcal/mol), and Nucleocapsid (mean, -23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection.


Subject(s)
Antiviral Agents/chemistry , Databases, Chemical , Drug Delivery Systems , Drug Design , Molecular Docking Simulation , Molecular Dynamics Simulation , Phytochemicals/chemistry , SARS-CoV-2/chemistry , Viral Proteins/chemistry , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/epidemiology , Humans , Pandemics , Phytochemicals/therapeutic use , SARS-CoV-2/metabolism , Viral Proteins/antagonists & inhibitors
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