scholarly journals Structure-Based Virtual Screening Reveals Ibrutinib and Zanubrutinib as Potential Repurposed Drugs against COVID-19

2021 ◽  
Vol 22 (13) ◽  
pp. 7071
Author(s):  
Satyavani Kaliamurthi ◽  
Gurudeeban Selvaraj ◽  
Chandrabose Selvaraj ◽  
Sanjeev Kumar Singh ◽  
Dong-Qing Wei ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Viral Entry ◽  
Md Simulations ◽  
High Binding Energy ◽  
Nonstructural Proteins ◽  
Generalized Born ◽  
Replication Stage ◽  
Repurposed Drugs ◽  
Potential Inhibitors ◽  
Btk Inhibitors

Coronavirus disease (COVID)-19 is the leading global health threat to date caused by a severe acute respiratory syndrome coronavirus (SARS-CoV-2). Recent clinical trials reported that the use of Bruton’s tyrosine kinase (BTK) inhibitors to treat COVID-19 patients could reduce dyspnea and hypoxia, thromboinflammation, hypercoagulability and improve oxygenation. However, the mechanism of action remains unclear. Thus, this study employs structure-based virtual screening (SBVS) to repurpose BTK inhibitors acalabrutinib, dasatinib, evobrutinib, fostamatinib, ibrutinib, inositol 1,3,4,5-tetrakisphosphate, spebrutinib, XL418 and zanubrutinib against SARS-CoV-2. Molecular docking is conducted with BTK inhibitors against structural and nonstructural proteins of SARS-CoV-2 and host targets (ACE2, TMPRSS2 and BTK). Molecular mechanics-generalized Born surface area (MM/GBSA) calculations and molecular dynamics (MD) simulations are then carried out on the selected complexes with high binding energy. Ibrutinib and zanubrutinib are found to be the most potent of the drugs screened based on the results of computational studies. Results further show that ibrutinib and zanubrutinib could exploit different mechanisms at the viral entry and replication stage and could be repurposed as potential inhibitors of SARS-CoV-2 pathogenesis.

scholarly journals Phytochemicals from Selective Plants Have Promising Potential against SARS-CoV-2: Investigation and Corroboration through Molecular Docking, MD Simulations, and Quantum Computations

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Kafila Kousar ◽  
Arshia Majeed ◽  
Farkhanda Yasmin ◽  
Waqar Hussain ◽  
Nouman Rasool
Keyword(s):  
Md Simulations ◽  
Viral Pathogenesis ◽  
Positive Polarity ◽  
Nonstructural Proteins ◽  
Sesquiterpene Glycoside ◽  
Dynamics Simulations ◽  
Potential Inhibitors ◽  
High Binding Affinity

Coronaviruses have been reported previously due to their association with the severe acute respiratory syndrome (SARS). After SARS, these viruses were known to be causing Middle East respiratory syndrome (MERS) and caused 35% evanescence amid victims pursuing remedial care. Nowadays, beta coronaviruses, members of Coronaviridae, family order Nidovirales, have become subjects of great importance due to their latest pandemic originating from Wuhan, China. The virus named as human-SARS-like coronavirus-2 contains four structural as well as sixteen nonstructural proteins encoded by single-stranded ribonucleic acid of positive polarity. As there is no vaccine available to treat the infection caused by these viruses, there is a dire need for taking necessary steps against this virus. Herein, we have targeted two nonstructural proteins of SARS-CoV-2, namely, methyltransferase (nsp16) and helicase (nsp13), respectively, due to their substantial activity in viral pathogenesis. A total of 2035 compounds were analyzed for their pharmacokinetics and pharmacological properties. The screened 108 compounds were docked against both targeted proteins and were compared with previously reported known compounds. Compounds with high binding affinity were analyzed for their reactivity through DFT analysis, and binding was analyzed using molecular dynamics simulations. Through the analyses performed in this study, it is concluded that EryvarinM, Silydianin, Osajin, and Raddeanine can be considered potential inhibitors for MTase, while TomentodiplaconeB, Osajin, Sesquiterpene Glycoside, Rhamnetin, and Silydianin for helicase after these compounds are validated thoroughly using in vitro and in vivo protocols.

scholarly journals Potential Inhibitors of Fascin From A Database of Marine Natural Products: A Virtual Screening and Molecular Dynamics Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Lirui Lin ◽  
Kai Lin ◽  
Xiaodong Wu ◽  
Jia Liu ◽  
Yinwei Cheng ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Natural Products ◽  
Virtual Screening ◽  
Marine Natural Products ◽  
Pharmacophore Model ◽  
Binding Affinities ◽  
Dynamic Interactions ◽  
Generalized Born ◽  
Accelerated Molecular Dynamics ◽  
Potential Inhibitors

Marine nature products are unique compounds that are produced by the marine environment including plants, animals, and microorganisms. The wide diversity of marine natural products have great potential and are versatile in terms of drug discovery. In this paper, we use state-of-the-art computational methods to discover inhibitors from marine natural products to block the function of Fascin, an overexpressed protein in various cancers. First, virtual screening (pharmacophore model and molecular docking) was carried out based on a marine natural products database (12015 molecules) and provided eighteen molecules that could potentially inhibit the function of Fascin. Next, molecular mechanics generalized Born surface area (MM/GBSA) calculations were conducted and indicated that four molecules have higher binding affinities than the inhibitor NP-G2-029, which was validated experimentally. ADMET analyses of pharmacokinetics demonstrated that one of the four molecules does not match the criterion. Finally, ligand Gaussian accelerated molecular dynamics (LiGaMD) simulations were carried out to validate the three inhibitors binding to Fascin stably. In addition, dynamic interactions between protein and ligands were analyzed systematically. Our study will accelerate the development of the cancer drugs targeting Fascin.

scholarly journals Identification of saquinavir as a potent inhibitor of dimeric SARS-CoV2 main protease through MM/GBSA

2020 ◽  
Author(s):  
Bello Martiniano ◽  
Martínez-Muñoz Alberto ◽  
Balbuena-Rebolledo Irving
Keyword(s):  
Md Simulation ◽  
Potent Inhibitor ◽  
Drug Repurposing ◽  
Md Simulations ◽  
Generalized Born ◽  
Main Protease ◽  
Promising Target ◽  
Approved Drugs ◽  
Potential Inhibitors ◽  
Fda Approved Drugs

Abstract Among targets selected for studies aimed to identify potential inhibitors against COVID-19, SARS-CoV2 main proteinase (Mpro) is highlighted. Mpro is indispensable for virus replication, and is a promising target of potential inhibitors of COVID-19. Recently, monomeric SARS-CoV2 Mpro, drug repurposing and docking methods have facilitated the identification of several potential inhibitors. Results were refined through the assessment of dimeric SARS-CoV2 Mpro, which represents the functional state of enzyme. Docking and molecular dynamics (MD) simulations combined with molecular mechanics/generalized Born surface area (MM/GBSA) studies indicated that dimeric Mpro most significantly impacts binding affinity tendency compared with the monomeric state, which suggesting that dimeric state is most useful when performing studies aimed to identify drugs targeting Mpro. In this study, we extend previous research by performing docking and MD simulation studies coupled with an MM/GBSA approach to assess binding of dimeric SARS-CoV2 Mpro to 12 FDA-approved drugs (darunavir, indinavir, saquinavir, tipranavir, diosmin, hesperidin, rutin, raltegravir, velpatasvir, ledipasvir, rosuvastatin and bortezomib), which were identified as the best candidates for treatment of COVID-19 in some previous dockings studies involving monomeric SARS-CoV2 Mpro. This analysis identified saquinavir as a potent inhibitor of dimeric SARS-CoV2 Mpro, therefore, the compound may have clinical utility against COVID-19.

The Research of New Inhibitors of Bacterial Methionine Aminopeptidase by Structure Based Virtual Screening Approach of ZINC DATABASE and In Vitro Validation

2020 ◽  
Vol 16 (4) ◽  
pp. 389-401 ◽  
Author(s):  
Hanane Boucherit ◽  
Abdelouahab Chikhi ◽  
Abderrahmane Bensegueni ◽  
Amina Merzoug ◽  
Jean-Michel Bolla
Keyword(s):  
Virtual Screening ◽  
Bacterial Survival ◽  
Methionine Aminopeptidase ◽  
Bacterial Strains ◽  
Microdilution Method ◽  
Zinc Database ◽  
Promising Target ◽  
New Antibiotics ◽  
Potential Inhibitors

Background: The great emergence of multi-resistant bacterial strains and the low renewal of antibiotics molecules are leading human and veterinary medicine to certain therapeutic impasses. Therefore, there is an urgent need to find new therapeutic alternatives including new molecules in the current treatments of infectious diseases. Methionine aminopeptidase (MetAP) is a promising target for developing new antibiotics because it is essential for bacterial survival. Objective: To screen for potential MetAP inhibitors by in silico virtual screening of the ZINC database and evaluate the best potential lead molecules by in vitro studies. Methods: We have considered 200,000 compounds from the ZINC database for virtual screening with FlexX software to identify potential inhibitors against bacterial MetAP. Nine chemical compounds of the top hits predicted were purchased and evaluated in vitro. The antimicrobial activity of each inhibitor of MetAP was tested by the disc-diffusion assay against one Gram-positive (Staphylococcus aureus) and two Gram-negative (Escherichia coli & Pseudomonas aeruginosa) bacteria. Among the studied compounds, compounds ZINC04785369 and ZINC03307916 showed promising antibacterial activity. To further characterize their efficacy, the minimum inhibitory concentration was determined for each compound by the microdilution method which showed significant results. Results: These results suggest compounds ZINC04785369 and ZINC03307916 as promising molecules for developing MetAP inhibitors. Conclusion: Furthermore, they could therefore serve as lead molecules for further chemical modifications to obtain clinically useful antibacterial agents.

scholarly journals Identification of New Potential Inhibitors of Quorum Sensing through a Specialized Multi-Level Computational Approach

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2600
Author(s):  
Fábio G. Martins ◽  
André Melo ◽  
Sérgio F. Sousa
Keyword(s):  
Virtual Screening ◽  
Quorum Sensing ◽  
In Silico ◽  
Bacterial Infections ◽  
Extracellular Polymeric Substances ◽  
Free Energy Calculations ◽  
Ligand Docking ◽  
Screening Tests ◽  
Scoring Functions ◽  
Potential Inhibitors

Biofilms are aggregates of microorganisms anchored to a surface and embedded in a self-produced matrix of extracellular polymeric substances and have been associated with 80% of all bacterial infections in humans. Because bacteria in biofilms are less amenable to antibiotic treatment, biofilms have been associated with developing antibiotic resistance, a problem that urges developing new therapeutic options and approaches. Interfering with quorum-sensing (QS), an important process of cell-to-cell communication by bacteria in biofilms is a promising strategy to inhibit biofilm formation and development. Here we describe and apply an in silico computational protocol for identifying novel potential inhibitors of quorum-sensing, using CviR—the quorum-sensing receptor from Chromobacterium violaceum—as a model target. This in silico approach combines protein-ligand docking (with 7 different docking programs/scoring functions), receptor-based virtual screening, molecular dynamic simulations, and free energy calculations. Particular emphasis was dedicated to optimizing the discrimination ability between active/inactive molecules in virtual screening tests using a target-specific training set. Overall, the optimized protocol was used to evaluate 66,461 molecules, including those on the ZINC/FDA-Approved database and to the Mu.Ta.Lig Virtual Chemotheca. Multiple promising compounds were identified, yielding good prospects for future experimental validation and for drug repurposing towards QS inhibition.

VERIFICATION OF THE GENERALIZED BORN MODEL AT SHORT DISTANCES

2013 ◽  
Vol 13 (06) ◽  
pp. 1340020
Author(s):  
XIAOCHUAN TANG ◽  
YONG DUAN
Keyword(s):  
Analytical Solutions ◽  
Md Simulations ◽  
Solvation Energy ◽  
Implicit Solvent ◽  
Generalized Born ◽  
Simple Description ◽  
Born Model ◽  
Solvent Models ◽  
Potential Methods ◽  
Gb Model

The generalized Born (GB) model, one of the implicit solvent models, is widely applied in molecular dynamics (MD) simulations as a simple description of the solvation effect. In the GB model, an empirical function called the Still's formula, with the algorithmic simplicity, is utilized to calculate the solvation energy due to the polarization, termed as ΔG pol . Applications of the GB model have exhibited reasonable accuracy and high computational efficiency. However, there is still room for improvements. Most of the attempts to improve the GB model focus on optimizing effective Born radii. Contrarily, limited researches have been performed to improve the feasibility of the Still's formula. In this paper, analytical methods was applied to investigate the validity of the Still's formula at short distance. Taking advantage of the toroidal coordinates and Mehler–Fock transform, the analytical solutions of the GB model at short distances was derived explicitly for the first time. Additionally, the solvation energy was numerically computed using proper algorithms based on the analytical solutions and compared with ΔG pol calculated in the GB model. With the analysis on the deficiencies of the Still's formula at short distances, potential methods to improve the validity of the GB model were discussed.

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