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1.
Computer Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based Approaches ; : 17-55, 2022.
Article in English | Scopus | ID: covidwho-2027799

ABSTRACT

The drug discovery paradigm has been very time-consuming, challenging, and expensive;however, the disease conditions originating from bacteria, virus, protozoa, fungus and other microorganisms are steadily shooting up. For instance, COVID-19 is the latest viral infection that affects millions of people and the world’s economy very severely. Therefore, the quest for discovery of novel and potent drug compounds against deadly pathogens is crucial at the moment. Despite a lot of drawbacks in drug discovery and development and its pertaining technology, the advancement must be taken into account so the time duration and cost would be minimized. In this chapter, basic principles in drug design and discovery have been discussed together with advances in drug development. © 2022 Elsevier Inc. All rights reserved.

2.
Biosensors ; 12(8):574, 2022.
Article in English | ProQuest Central | ID: covidwho-2023153

ABSTRACT

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming procedures. In silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools, a rational design of aptamers is demonstrated. This “smart” SELEX method is experimentally proved by choosing the best five aptamer candidates obtained from the design process and applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of five different aptamers leads to a significant difference in the sensor’s response. This can be explained by considering the aptamers’ conformational change due to their interaction with the target molecule. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were used to confirm the high selectivity of the designed aptamers. The proposed in silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers and potentially be applied to any target molecule.

3.
Front Pharmacol ; 13:961154, 2022.
Article in English | PubMed | ID: covidwho-2022838

ABSTRACT

Background: Due to the constant mutation of virus and the lack of specific therapeutic drugs, the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a huge threat to the health of people, especially those with underlying diseases. Therefore, drug discovery against the SARS-CoV-2 remains of great significance. Methods: With the main protease of virus as the inhibitor target, 9,614 genistein derivatives were virtually screened by LeDock and AutoDock Vina, and the top 20 compounds with highest normalized scores were obtained. Molecular dynamics simulations were carried out for studying interactions between these 20 compounds and the target protein. The drug-like properties, activity, and ADMET of these compounds were also evaluated by DruLiTo software or online server. Results: Twenty compounds, including compound 11, were screened by normalized molecular docking, which could bind to the target through multiple non-bonding interactions. Molecular dynamics simulation results showed that compounds 2, 4, 5, 11, 13, 14, 17, and 18 had the best binding force with the target protein of SARS-CoV-2, and the absolute values of binding free energies all exceeded 50 kJ/mol. The drug-likeness properties indicated that a variety of compounds including compound 11 were worthy of further study. The results of bioactivity score prediction found that compounds 11 and 12 had high inhibitory activities against protease, which indicated that these two compounds had the potential to be further developed as COVID-19 inhibitors. Finally, compound 11 showed excellent predictive ADMET properties including high absorption and low toxicity. Conclusion: These in silico work results show that the preferred compound 11 (ZINC000111282222), which exhibited strong binding to SARS-CoV-2 main protease, acceptable drug-like properties, protease inhibitory activity and ADMET properties, has great promise for further research as a potential therapeutic agent against COVID-19.

4.
FEBS Journal ; : 1, 2022.
Article in English | Academic Search Complete | ID: covidwho-2019259

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) spike protein (S protein) is highly N‐glycosylated, and a “glycan shield” is formed to limit the access of other molecules;however, a small open area coincides with the interface to the host's receptor and also neutralising antibodies. Most of the variants of concern have mutations in this area, which could reduce the efficacy of existing antibodies. In contrast, N‐glycosylation sites are relatively invariant, and some are essential for infection. Here, we observed that the S proteins of the ancestral (Wuhan) and Omicron strains bind with Pholiota squarrosa lectin (PhoSL), a 40‐amino‐acid chemically synthesised peptide specific to core‐fucosylated N‐glycans. The affinities were at a low nanomolar level, which were ~ 1000‐fold stronger than those between PhoSL and the core‐fucosylated N‐glycans at the micromolar level. We demonstrated that PhoSL inhibited infection by both strains at similar submicromolar levels, suggesting its broad‐spectrum effect on SARS‐CoV‐2 variants. Cryogenic electron microscopy revealed that PhoSL caused an aggregation of the S protein, which was likely due to the multivalence of both the trimeric PhoSL and S protein. This characteristic is likely relevant to the inhibitory mechanism. Structural modelling of the PhoSL–S protein complex indicated that PhoSL was in contact with the amino acids of the S protein, which explains the enhanced affinity with S protein and also indicates the significant potential for developing specific binders by the engineering of PhoSL. [ FROM AUTHOR] Copyright of FEBS Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

5.
Struct Chem ; : 1-9, 2022 Jul 26.
Article in English | MEDLINE | ID: covidwho-2014353

ABSTRACT

The novel coronavirus that has affected the whole world is declared a pandemic by the World Health Organization. Since the emergence of this virus, researchers worldwide have searched for potential antivirals against it. Being an RNA virus, it shows a high rate of mutability and variability in its genome. In the present study, all the reported SARS-CoV-2 genomes isolated from diverse regions of the world available in the GISAID database have been considered for phylogenetic analysis. The strain identified at the root is subjected to phylogenetic analysis with genomes of other known human viruses obtained from NCBI for identifying the nearest viral neighbor. Furthermore, the phylogenetic relationship between various human viruses was used to repurpose the known antiviral drugs towards coronavirus using in silico docking approach. The phylogeny reveals the link of the COVID virus with adenovirus. The known drugs against adenovirus are considered in the present study for drug repurposing through molecular docking analysis. The reference inhibitors of the respective targets were also considered in the docking study. The protein targets, namely protease, endoribonuclease, methyltransferase, phosphatase, and spike protein, are considered for screening with the known drug of adenovirus. Ribavirin, known to treat adenoviral infection, shows the best docking score, suggesting its use as a repurposed drug to treat SARS-CoV-2. Furthermore, the potency of the ribavirin drug is analyzed using molecular dynamics studies. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02019-6.

6.
Struct Chem ; : 1-21, 2022 Jul 04.
Article in English | MEDLINE | ID: covidwho-2014346

ABSTRACT

COVID-19 disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) has resulted in tremendous loss of lives across the world and is continuing to do so. Extensive work is under progress to develop inhibitors which can prevent the disease by arresting the virus in its life cycle. One such way is by targeting the main protease of the virus which is crucial for the cleavage and conversion of polyproteins into functional units of polypeptides. In this endeavor, our effort was to identify hit molecule inhibitors for SARS-CoV2 main protease using fragment-based drug discovery (FBDD), based on the available crystal structure of chromene-based inhibitor (PDB_ID: 6M2N). The designed molecules were validated by molecular docking and molecular dynamics simulations. The stability of the complexes was further assessed by calculating their binding free energies, normal mode analysis, mechanical stiffness, and principal component analysis. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-01995-z.

7.
Struct Chem ; : 1-9, 2022 Jun 21.
Article in English | MEDLINE | ID: covidwho-2014345

ABSTRACT

Scientific insights gained from the severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS) outbreaks have been assisting scientists and researchers in the quest of antiviral drug discovery process against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronaviruses and influenza viruses both rely on the host type 2 transmembrane serine protease, TMPRSS2, for entry and propagation. Recent studies report SARS-CoV-2 also uses TMPRSS2 to enter cells. In the current study, we employed structure-based virtual screening of 1,82,651 natural compounds downloaded from the zin database against the homology model of the TMPRSS2 protein, followed by a molecular dynamics-based simulation to identify potential TMPRSS2 hits. The virtual screening yielded 110 hits with docking scores ranging from -8.654 to -6.775 and glide energies ranging from -55.714 to -29.065 kcal/mol. The binding mode analysis revealed that the hit molecules made H-bond, Pi-Pi stacking and salt bridge contacts with the TMPRSS2 active site residues. MD simulations of the top two hits (ZINC000095912839 and ZINC000085597504) revealed to form a stable complex with TMPRSS2, with a minimal RMSD and RMSF fluctuation. Both the hit structures interacted strongly with the Asp180, Gln183, Gly184, Ser186, Gly207 and Gly209, as predicted by Glide XP docking, and formed a significant H-bond interaction with Ser181 in MD simulation. Among these two, ZINC000095912839 was having the most stable binding interaction with TMPRSS2 of the two molecules. The present study successfully identified TMPRSS2 ligands from a database of zinc natural molecules as potential leads for novel SARs-CoV-2 treatment. Supplementary Inform: The online version contains supplementary material available at 10.1007/s11224-022-01991-3.

8.
Struct Chem ; : 1-13, 2022 Jun 15.
Article in English | MEDLINE | ID: covidwho-2014344

ABSTRACT

In the present study, a new category of 1,3,4-thiadiazoles was developed by submitting methyl 2-(4-hydroxy-3-methoxybenzylidene) hydrazine-1-carbodithioate to react with the appropriate hydrazonoyl halides in presence of few drops of diisopropyl ethyl amine. The chemical structures of the newly synthesized derivatives were inferred by means of their micro-analytical and spectral data. Utilizing combined molecular docking and molecular dynamics techniques, the binding affinities and features of the synthesized compounds were evaluated against four SARS-CoV-2 target enzymes, namely, main protease (Mpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), and receptor-binding domain (RBD) of the spike protein. Compound 7 demonstrated promising binding affinities with the target enzymes Mpro, PLpro, RdRp, and RBD with docking scores of -11.4, -9.4, -8.2, and -6.8 kcal/mol, respectively. In addition, compound 7 exhibited MM-GBSA//100 ns MD docking score of -35.9 kcal/mol against Mpro. Structural and energetic analyses revealed the stability of the 7-Mpro complex over 100 ns MD simulations. In addition, compound 7 obeyed Lipinski's rule of five, as it has acceptable absorption, distribution, and oral bioavailability inside the body. Therefore, compound 7 is considered as a promising starting point for designing potential therapeutic agents against Covid-19. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-01985-1.

9.
Biochemistry ; 2022.
Article in English | Web of Science | ID: covidwho-2016509

ABSTRACT

Remdesivir is an adenosine analogue that has a cyano substitution in the C1' position of the ribosyl moiety and a modified base structure to stabilize the linkage of the base to the C1' atom with its strong electron-withdrawing cyano group. Within the replication-transcription complex (RTC) of SARS-CoV-2, the RNA-dependent RNA polymerase nsp12 selects remdesivir monophosphate (RMP) over adenosine monophosphate (AMP) for nucleotide incorporation but noticeably slows primer extension after the added RMP of the RNA duplex product is translocated by three base pairs. Cryo-EM structures have been determined for the RTC with RMP at the nucleotide-insertion (i) site or at the i + 1, i + 2, or i + 3 sites after product translocation to provide a structural basis for a delayed-inhibition mechanism by remdesivir. In this study, we applied molecular dynamics (MD) simulations to extend the resolution of structures to the measurable maximum that is intrinsically limited by MD properties of these complexes. Our MD simulations provide (i) a structural basis for nucleotide selectivity of the incoming substrates of remdesivir triphosphate over adenosine triphosphate and of ribonucleotide over deoxyribonucleotide, (ii) new detailed information on hydrogen atoms involved in H-bonding interactions between the enzyme and remdesivir, and (iii) direct information on the catalytically active complex that is not easily captured by experimental methods. Our improved resolution of interatomic interactions at the nucleotide-binding pocket between remedesivir and the polymerase could help to design a new class of anti-SARS-CoV-2 inhibitors.

10.
Structural Chemistry ; : 1-16, 2022.
Article in English | Academic Search Complete | ID: covidwho-2014356

ABSTRACT

The SARS-CoV-2 proteases Mpro and PLpro are important targets for the development of antivirals against COVID-19. The functional group 1,2,4-thiadiazole has been indicated to inhibit cysteinyl proteases, such as papain and cathepsins. Of note, the 1,2,4-thiadiazole moiety is found in a new class of cephalosporin FDA-approved antibiotics: ceftaroline fosamil, ceftobiprole, and ceftobiprole medocaril. Here we investigated the interaction of these new antibiotics and their main metabolites with the SARS-CoV-2 proteases by molecular docking, molecular dynamics (MD), and density functional theory (DFT) calculations. Our results indicated the PLpro enzyme as a better in silico target for the new antibacterial cephalosporins. The results with ceftaroline fosamil and the dephosphorylate metabolite compounds should be tested as potential inhibitor of PLpro, Mpro, and SARS-CoV-2 replication in vitro. In addition, the data here reported can help in the design of new potential drugs against COVID-19 by exploiting the S atom reactivity in the 1,2,4-thiadiazole moiety. [ FROM AUTHOR] Copyright of Structural Chemistry is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

11.
22nd International Conference on Computational Science and Its Applications , ICCSA 2022 ; 13382 LNCS:264-274, 2022.
Article in English | Scopus | ID: covidwho-2013919

ABSTRACT

A new highly efficient GPU-equipped computing platform for studying the molecular inhibition mechanisms of the Sars-Cov-2 virus by natural compounds and aptamers has been installed and configured. Studies will be carried out by means of molecular dynamics methods and programs. For this reason, we have assembled specific hardware components into a 4U rack, together with a NVIDIA RTX 3060 GPU for speeding up molecular dynamics calculations and visualizing their outcomes. In fact, not only computational resources, in terms of computing power and execution times, are needed by molecular dynamics programs adopted by us, but also a system allowing the rendering and visualization of large biomolecules and their trajectories, such as viruses and proteins, represents a key factor for our work. Details about platform implementation and preliminary tests carried out are discussed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

12.
Proteins ; 2022.
Article in English | PubMed | ID: covidwho-2013734

ABSTRACT

Increased ability to predict protein structures is moving research focus towards understanding protein dynamics. A promising approach is to represent protein dynamics through networks and take advantage of well-developed methods from network science. Most studies build protein dynamics networks from correlation measures, an approach that only works under very specific conditions, instead of the more robust inverse approach. Thus, we apply the inverse approach to the dynamics of protein dihedral angles, a system of internal coordinates, to avoid structural alignment. Using the well-characterized adhesion protein, FimH, we show that our method identifies networks that are physically interpretable, robust, and relevant to the allosteric pathway sites. We further use our approach to detect dynamical differences, despite structural similarity, for Siglec-8 in the immune system, and the SARS-CoV-2 spike protein. Our study demonstrates that using the inverse approach to extract a network from protein dynamics yields important biophysical insights. This article is protected by copyright. All rights reserved.

13.
Frontiers in Immunology ; 13, 2022.
Article in English | EMBASE | ID: covidwho-2009863

ABSTRACT

Background: Deep venous thrombosis (DVT) highly occurs in patients with severe COVID-19 and probably accounted for their high mortality. DVT formation is a time-dependent inflammatory process in which NETosis plays an important role. However, whether ginsenoside Rg5 from species of Panax genus could alleviate DVT and its underlying mechanism has not been elucidated. Methods: The interaction between Rg5 and P2RY12 was studied by molecular docking, molecular dynamics, surface plasmon resonance (SPR), and molecular biology assays. The preventive effect of Rg5 on DVT was evaluated in inferior vena cava stasis–induced mice, and immunocytochemistry, Western blot, and calcium flux assay were performed in neutrophils from bone marrow to explore the mechanism of Rg5 in NETosis via P2RY12. Results: Rg5 allosterically interacted with P2RY12, formed stable complex, and antagonized its activity via residue E188 and R265. Rg5 ameliorated the formation of thrombus in DVT mice;accompanied by decreased release of Interleukin (IL)-6, IL-1β, and tumor necrosis factor-α in plasma;and suppressed neutrophil infiltration and neutrophil extracellular trap (NET) release. In lipopolysaccharide- and platelet-activating factor–induced neutrophils, Rg5 reduced inflammatory responses via inhibiting the activation of ERK/NF-κB signaling pathway while decreasing cellular Ca2+ concentration, thus reducing the activity and expression of peptidyl arginine deiminase 4 to prevent NETosis. The inhibitory effect on neutrophil activity was dependent on P2RY12. Conclusions: Rg5 could attenuate experimental DVT by counteracting NETosis and inflammatory response in neutrophils via P2RY12, which may pave the road for its clinical application in the prevention of DVT-related disorders.

14.
Journal of chemical information and modeling ; 2022.
Article in English | MEDLINE | ID: covidwho-2008239

ABSTRACT

Five major variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged and posed challenges in controlling the pandemic. Among them, the current dominant variant, viz., Omicron, has raised serious concerns about its infectiousness and antibody neutralization. However, few studies pay attention to the effect of the mutations on the dynamic interaction network of Omicron S protein trimers binding to the host angiotensin-converting enzyme 2 (ACE2). In this study, we conducted molecular dynamics (MD) simulations and enzyme linked immunosorbent assay (ELISA) to explore the binding strength and mechanism of wild type (WT), Delta, and Omicron S protein trimers to ACE2. The results showed that the binding capacities of both the two variants' S protein trimers to ACE2 are enhanced in varying degrees, indicating possibly higher cell infectiousness. Energy decomposition and protein-protein interaction network analysis suggested that both the mutational and conserved sites make effects on the increase in the overall affinity through a variety of interactions. The experimentally determined KD values by biolayer interferometry (BLI) and the predicted binding free energies of the RBDs of Delta and Omicron to mAb HLX70 revealed that the two variants may have the high risk of immune evasion from the mAb. These results are not only helpful in understanding the binding strength and mechanism of S protein trimer-ACE2 but also beneficial for drug, especially for antibody development.

15.
Journal of Molecular Structure ; : 134128, 2022.
Article in English | ScienceDirect | ID: covidwho-2007963

ABSTRACT

During the ongoing pandemic, there have been increasing reports of invasive fungal disease (IFD), particularly among immunocompromised populations. Candida albicans is one of the most common clinical pathogenic microorganisms which have become a serious health threat to population either infected with Covid-19 or on treatment with immunosuppressant's/broad-range antibiotics. Currently, benzothiazole is a well explored scaffold for anti-fungal activity, especially mercapto substituted benzothiazoles. It is reported that exploring the 2nd position of benzothiazoles yield improved anti-fungal molecules. Therefore, in the current study, lead optimization approach using bioisosteric replacement protocol was followed to improve the anti-fungal activity of an already reported benzothiazole derivative, N-(1,3-benzothiazole-2-yl)-2-(pyridine-3-ylformohydrazido) acetamide. To rationally identify the putative anti-candida targets of this derivative, network analysis was carried out. Complexes of designed compounds and identified putative targets were further analyzed for the docking interactions and their consequent retention after the completion of exhaustive MD simulations. Top seven designed compounds were synthesized and evaluated for in-vitro anti-fungal property against Candida, which indicated that compounds 1.2c and 1.2f possess improved and comparable anti-fungal activity to N-(1,3-benzothiazole-2-yl)-2-(pyridine-3-ylformohydrazido) acetamide and Nystatin, respectively.

16.
Computational and Structural Biotechnology Journal ; 2022.
Article in English | ScienceDirect | ID: covidwho-2007642

ABSTRACT

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has led to a global pandemic. Deep learning (DL) technology and molecular dynamics (MD) simulation are two mainstream computational approaches to investigate the geometric, chemical and structural features of protein and guide the relevant drug design. Despite a large amount of research papers focusing on drug design for SARS-COV-2 using DL architectures, it remains unclear how the binding energy of the protein-protein/ligand complex dynamically evolves which is also vital for drug development. In addition, traditional deep neural networks usually have obvious deficiencies in predicting the interaction sites as protein conformation changes. In this review, we introduce the latest progresses of the DL and DL-based MD simulation approaches in structure-based drug design (SBDD) for SARS-CoV-2 which could address the problems of protein structure and binding prediction, drug virtual screening, molecular docking and complex evolution. Furthermore, the current challenges and future directions of DL-based MD simulation for SBDD are also discussed.

17.
Computational and Structural Biotechnology Journal ; 2022.
Article in English | ScienceDirect | ID: covidwho-2007640

ABSTRACT

Surfactant protein D (SP-D) is an essential component of the human pulmonary surfactant system, which is crucial in the innate immune response against glycan-containing pathogens, including Influenza A viruses (IAV) and SARS-CoV-2. Previous studies have shown that wild-type (WT) SP-D can bind IAV but exhibits poor antiviral activities. However, a double mutant (DM) SP-D consisting of two point mutations (Asp325Ala and Arg343Val) inhibits IAV more potently. Presently, the structural mechanisms behind the point mutations’ effects on SP-D’s binding affinity with viral surface glycans are not fully understood. Here we use microsecond-scale, full-atomistic molecular dynamics (MD) simulations to understand the molecular mechanism of mutation-induced SP-D’s higher antiviral activity. We find that the Asp325Ala mutation promotes a trimannose conformational change to a more stable state. Arg343Val increases the binding with trimannose by increasing the hydrogen bonding interaction with Glu333. Free energy perturbation (FEP) binding free energy calculations indicate that the Arg343Val mutation contributes more to the increase of SP-D’s binding affinity with trimannose than Asp325Ala. This study provides a molecular-level exploration of how the two mutations increase SP-D binding affinity with trimannose, which is vital for further developing preventative strategies for related diseases.

18.
Computers in Biology and Medicine ; : 106049, 2022.
Article in English | ScienceDirect | ID: covidwho-2007624

ABSTRACT

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections generate approximately one million virions per day, and the majority of available antivirals are ineffective against it due to the virus's inherent genetic mutability. This necessitates the investigation of concurrent inhibition of multiple SARS-CoV-2 targets. We show that fortunellin (acacetin 7-O-neohesperidoside), a phytochemical, is a promising candidate for preventing and treating coronavirus disease (COVID-19) by targeting multiple key viral target proteins. Fortunellin supports protective immunity while inhibiting pro-inflammatory cytokines and apoptosis pathways and protecting against tissue damage. Fortunellin is a phytochemical found in Gojihwadi kwath, an Indian traditional Ayurvedic formulation with an antiviral activity that is effective in COVID-19 patients. The mechanistic action of its antiviral activity, however, is unknown. The current study comprehensively evaluates the potential therapeutic mechanisms of fortunellin in preventing and treating COVID-19. We have used molecular docking, molecular dynamics simulations, free-energy calculations, host target mining of fortunellin, gene ontology enrichment, pathway analyses, and protein-protein interaction analysis. We discovered that fortunellin reliably binds to key targets that are necessary for viral replication, growth, invasion, and infectivity including Nucleocapsid (N-CTD) (−54.62 kcal/mol), Replicase-monomer at NSP-8 binding site (−34.48 kcal/mol), Replicase-dimer interface (−31.29 kcal/mol), Helicase (−30.02 kcal/mol), Papain-like-protease (−28.12 kcal/mol), 2′-O-methyltransferase (−23.17 kcal/mol), Main-protease (−21.63 kcal/mol), Replicase-monomer at dimer interface (−22.04 kcal/mol), RNA-dependent-RNA-polymerase (−19.98 kcal/mol), Nucleocapsid-NTD (−16.92 kcal/mol), and Endoribonuclease (−16.81 kcal/mol). Furthermore, we identify and evaluate the potential human targets of fortunellin and its effect on the SARS-CoV-2 infected tissues, including normal-human-bronchial-epithelium (NHBE) and lung cells and organoids such as pancreatic, colon, liver, and cornea using a network pharmacology approach. Thus, our findings indicate that fortunellin has a dual role;multi-target antiviral activities against SARS-CoV-2 and immunomodulatory capabilities against the host.

19.
Biophysical journal ; 2022.
Article in English | MEDLINE | ID: covidwho-2007564

ABSTRACT

Crucial for mRNA-based vaccines are the composition, structure and properties of lipid nanoparticles (LNPs) as their delivery vehicle. Using all-atom molecular dynamics simulations as a computational microscope, we provide an atomistic view on the structure of the Comirnaty vaccine LNP, its molecular organization, physico-chemical properties and insight in its pH-driven phase transition enabling mRNA release at atomistic resolution. At physiological pH, our simulations suggest an oil-like LNP core that is composed of the aminolipid ALC-0315 and cholesterol (ratio 72:28). It is surrounded by a lipid monolayer formed by distearoylphosphatidylcholine, ALC-0315, PEGylated lipids and cholesterol at a ratio of 22:9:6:63. Protonated aminolipids enveloping mRNA formed inverted micellar structures that provide a shielding and likely protection from environmental factors. In contrast, at low pH, the Comirnaty lipid composition instead spontaneously formed lipid bilayers that display a high degree of elasticity. These pH-dependent lipid phases suggest that a change in pH of the environment upon LNP transfer to the endosome likely acts as trigger for cargo release from the LNP core by turning aminolipids inside out thereby destabilizing both the LNP shell and the endosomal membrane.

20.
Organic Communications ; 2022.
Article in English | Web of Science | ID: covidwho-2006706

ABSTRACT

Pyrimido[4,5-d]pyrimidine conveys antimicrobial activity against various micro pathogens having functionalized properties. As a result, this study has designed to illustrate the antibacterial, antifungal, and antiviral properties of pyrimido[4,5-d]pyrimidine. First of all, these structures have been optimized from the characterization of synthesis for calculating chemical descriptors by DFT. Next, the auto docking and target docking against 12 proteins, such as Pseudomonas aeruginosa (2Y0H), Bacillus cereus (1AH7), Escherichia coli (6DR3), Shigella dysenteriae (3FHH) Salmonella typhi (3FHU), Aspergillus niger (1ACZ), Aspergillus flavus (1XY3), Rhizomucor miehei (4WTP), Candida auris (6U8J), three proteins of SARS-CoV-2 (7T9J, 7T9L, and 7TB4) were performed for the determination of binding sites and binding affinity. One FDA approved drug (Ampicillin) has docked against 12 proteins while the Bacillus cereus (Bacteria), Aspergillus flavus (Fungus), and SARS-CoV-2, 7T9L (Omicron) are obtained the best binding affinity after docking. The most common residues are the PHE-66, ARG-176 and VAL-124 for Bacillus cereus, Aspergillus flavus and SARS-CoV-2, Omicron (7T9L), respectively, as they blocked the active sites by the ligands as inhibitors. It is revealed that this study contained both auto docking and target docking whereas the binding affinity of auto docking is that the binding affinity for auto docking is higher than target docking. Finally, among the nine compounds, three compounds show outstanding results against bacteria, fungus and virus. At last, molecular dynamics were performed to check the stability and validation of the docked complex and quantum calculations obtained the molecular properties, as well as ADMET, pharmacokinetics, Lipinski Rule and QSAR data.

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