Potential inhibitors of methionine aminopeptidase type II identified via structure-based pharmacophore modeling

Author(s):  
Safana Albayati ◽  
Abdullahi Ibrahim Uba ◽  
Kemal Yelekçi
2020 ◽  
Vol 16 (4) ◽  
pp. 389-401 ◽  
Author(s):  
Hanane Boucherit ◽  
Abdelouahab Chikhi ◽  
Abderrahmane Bensegueni ◽  
Amina Merzoug ◽  
Jean-Michel Bolla

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.


Author(s):  
Sheema Jb ◽  
Waheeta Hopper

  Objective: Glycogen synthase kinase 3 beta (GSK3β) is one of the main targets for wound healing activity. Our objective is to identify novel inhibitors for GSK3β using in silico approach.Methods: Grid-based molecular docking, energy-based pharmacophore (e-pharmacophore) modeling, and molecular dynamics (MD) studies were performed for phytocompounds with GSK3β and compared with standard drugs using Schrodinger software.Results: The glide scores and the molecular interactions of the phytocompounds were well comparable to the standard drugs. The MD was performed for the target bound to the best scoring ligand, entagenic acid. The pharmacophore features of this docked complex were modeled as e-pharmacophore. The constructed e-pharmacophore model was screened against phytocompounds retrieved from literature to identify the ligands with similar pharmacophore features.Conclusion: The glide scores of fukinolic acid, cimicifugic acid, and linarin were −10.99, −8.28, and −7.25 kcal/mol, respectively. The further 50 nanoseconds MD study determined the stability of GSK3β-linarin complex. Nitrofurazone and sulfathiazole drugs can lead to systemic side effects. Hence, it is concluded that linarin could be a potent wound healing compound against GSK3β.


2006 ◽  
Vol 16 (13) ◽  
pp. 3574-3577 ◽  
Author(s):  
Megumi Kawai ◽  
Nwe Y. BaMaung ◽  
Steve D. Fidanze ◽  
Scott A. Erickson ◽  
Jason S. Tedrow ◽  
...  

2012 ◽  
Vol 90 (8) ◽  
pp. 675-692 ◽  
Author(s):  
Premlata K. Ambre ◽  
Raghuvir R. S. Pissurlenkar ◽  
Evans C. Coutinho ◽  
Radhakrishnan P. Iyer

Inhibition of checkpoint kinase-1 (Chk1) by small molecules is of great therapeutic interest in the field of oncology and for understanding cell-cycle regulations. This paper presents a model with elements from docking, pharmacophore mapping, the 3D-QSAR approaches CoMFA, CoMSIA and CoRIA, and virtual screening to identify novel hits against Chk1. Docking, 3D-QSAR (CoRIA, CoMFA and CoMSIA), and pharmacophore studies delineate crucial site points on the Chk1 inhibitors, which can be modified to improve activity. The docking analysis showed residues in the proximity of the ligands that are involved in ligand–receptor interactions, whereas CoRIA models were able to derive the magnitude of these interactions that impact the activity. The ligand-based 3D-QSAR methods (CoMFA and CoMSIA) highlight key areas on the molecules that are beneficial and (or) detrimental for activity. The docking studies and 3D-QSAR models are in excellent agreement in terms of binding-site interactions. The pharmacophore hypotheses validated using sensitivity, selectivity, and specificity parameters is a four-point model, characterized by a hydrogen-bond acceptor (A), hydrogen-bond donor (D), and two hydrophobes (H). This map was used to screen a database of 2.7 million druglike compounds, which were pruned to a small set of potential inhibitors by CoRIA, CoMFA, and CoMSIA models with predicted activity in the range of 8.5–10.5 log units.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zeynab Fakhar ◽  
Shama Khan ◽  
Suliman Y. AlOmar ◽  
Afrah Alkhuriji ◽  
Aijaz Ahmad

AbstractA new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide and become pandemic with thousands new deaths and infected cases globally. To address coronavirus disease (COVID-19), currently no effective drug or vaccine is available. This necessity motivated us to explore potential lead compounds by considering drug repurposing approach targeting main protease (Mpro) enzyme of SARS-CoV-2. This enzyme considered to be an attractive drug target as it contributes significantly in mediating viral replication and transcription. Herein, comprehensive computational investigations were performed to identify potential inhibitors of SARS-CoV-2 Mpro enzyme. The structure-based pharmacophore modeling was developed based on the co-crystallized structure of the enzyme with its biological active inhibitor. The generated hypotheses were applied for virtual screening based PhaseScore. Docking based virtual screening workflow was used to generate hit compounds using HTVS, SP and XP based Glide GScore. The pharmacological and physicochemical properties of the selected lead compounds were characterized using ADMET. Molecular dynamics simulations were performed to explore the binding affinities of the considered lead compounds. Binding energies revealed that compound ABBV-744 binds to the Mpro with strong affinity (ΔGbind −45.43 kcal/mol), and the complex is more stable in comparison with other protein–ligand complexes. Our study classified three best compounds which could be considered as promising inhibitors against main protease SARS-CoV-2 virus.


Sign in / Sign up

Export Citation Format

Share Document