In silico study reveals existing drugs as α-glucosidase inhibitors: Structure-based virtual screening validated by experimental investigation

Wu, Jiaofeng; Hu, Baichun; Sun, Xiaozhu; Wang, Huibin; Huang, Yuzhou; Zhang, Yuting; Liu, Mengxi; Liu, Yuting; Zhao, Yunli; Wang, Jian

doi:10.1016/j.molstruc.2020.128532

Cited by 12 publications

(13 citation statements)

References 46 publications

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“…1 . Compounds with large molecular weight and peptides like molecules have been removed as well as non-ACE2 inhibitors with false activity labels [45] . The remaining set of known active ACE2 inhibitors and their correspondence decoy compounds were retrieved from the enhanced Database of Useful Decoys (DUDE) ( http://dude.docking.org ), which have been used to validate the 3D-interaction feature model.…”

Section: Methodsmentioning

confidence: 99%

“…Advance in silico drug design option tends to decrease the amount of time to develop, design, and optimize a new drug. Over the past few decades, the virtual screening process was engaged to identify the best lead compounds with different structural features for combination with a specific biological target [45] , [46] , [47] . Moreover, the computer-aided drug design by using pharmacophore-based virtual screening (PBVS), molecular docking and dynamics simulation approaches has been identified diverse promising drug targets and hits [14] .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Pokhrel

Bouback

Samad³

et al. 2021

International Journal of Biological Macromolecules

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Angiotensin-converting enzyme 2 (ACE2), also known as peptidyl-dipeptidase A, belongs to the dipeptidyl carboxydipeptidases family has emerged as a potential antiviral drug target against SARS-CoV-2. Most of the ACE2 inhibitors discovered till now are chemical synthesis; suffer from many limitations related to stability and adverse side effects. However, natural, and selective ACE2 inhibitors that possess strong stability and low side effects can be replaced instead of those chemicals' inhibitors. To envisage structurally diverse natural entities as an ACE2 inhibitor with better efficacy, a 3D structure-based-pharmacophore model (SBPM) has been developed and validated by 20 known selective inhibitors with their correspondence 1166 decoy compounds. The validated SBPM has excellent goodness of hit score and good predictive ability, which has been appointed as a query model for further screening of 11,295 natural compounds. The resultant 23 hits compounds with pharmacophore fit score 75.31 to 78.81 were optimized using in-silico ADMET and molecular docking analysis. Four potential natural inhibitory molecules namely D-DOPA (Amb17613565), L-Saccharopine (Amb6600091), D-Phenylalanine (Amb3940754), and L-Mimosine (Amb21855906) have been selected based on their binding affinity (−7.5, −7.1, −7.1, and −7.0 kcal/mol), respectively. Moreover, 250 ns molecular dynamics (MD) simulations confirmed the structural stability of the ligands within the protein. Additionally, MM/GBSA approach also used to support the stability of molecules to the binding site of the protein that also confirm the stability of the selected four natural compounds. The virtual screening strategy used in this study demonstrated four natural compounds that can be utilized for designing a future class of potential natural ACE2 inhibitor that will block the spike (S) protein dependent entry of SARS-CoV-2 into the host cell.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Pokhrel

Bouback

Samad³

et al. 2021

International Journal of Biological Macromolecules

View full text Add to dashboard Cite

show abstract

“…1. Compounds with large molecular weight and peptides like molecules were removed as well as non-ACE2 inhibitors with false activity labels [42]. The remaining set of known active ACE2 inhibitors and their correspondence decoy compounds were retrieved from the enhanced Database of Useful Decoys (DUDE) (http://dude.docking.org), have used to validate the 3D-interaction feature model.…”

Section: Pharmacophore Model Validationmentioning

confidence: 99%

“…Advance in silico drug design option tends to decrease the amount of time to develop, design, and optimize a new drug. Over the past few decades, the virtual screening process was engaged to identify the best lead compounds with different structural features for combination with a speci c biological target [42]. Moreover, the computer-aided drug design by using pharmacophore-based virtual screening (PBVS), molecular docking and dynamics simulation approaches has been identi ed diverse promising drug targets and hits [14].…”

Section: Introductionmentioning

confidence: 99%

Spike Protein Recognizer Receptor ACE2 Targeted Identification of Potential Natural Antiviral Drug Candidates Against SARS-CoV-2

Bouback

Samad

Nur

et al. 2021

Preprint

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Angiotensin-converting enzyme 2 (ACE2), also known as peptidyl-dipeptidase A, belongs to the dipeptidyl carboxydipeptidases family has emerged as a potential antiviral drug target against SARS-CoV-2. Most of the ACE2 inhibitors discovered until now are chemical synthesis; suffer from many limitations related to stability and adverse side effects. However, natural, and selective ACE2 inhibitors that possess strong stability and low side effects can be replaced instead of those chemicals’ inhibitors. To envisage structurally diverse natural entities as an ACE2 inhibitor with better efficacy, a structure-based-pharmacophore model (SBPM) was developed and validated by 20 known selective inhibitors with their correspondence 1166 decoy compounds. The validated SBPM has excellent goodness of hit score and good predictive ability, which has been appointed as a query model for further screening of 11,295 natural compounds. The resultant 23 hits compounds with pharmacophore fit score 75.31 to 78.81 were optimized using in-silico ADMET and molecular docking analysis. Four potential natural inhibitory molecules namely D-DOPA (Amb17613565), L-Saccharopine (Amb6600091), D-Phenylalanine (Amb3940754), and L-Mimosine (Amb21855906) have been selected based onbinding affinity (−7.5, −7.1, −7.1, and −7.0 kcal/mol), respectively. Moreover, 250 ns molecular dynamics (MD) simulations confirmed the structural stability of the ligands within the protein. Additionally, MM/GBSA approach also used to support the stability of molecules to the binding site of the protein that also confirm the stability of the selected four natural compounds. The virtual screening strategy used in this study demonstrated four natural compounds that can be utilized for designing a future class of potential natural ACE2 inhibitor that will block the spike (S) protein dependent entry of SARS-CoV-2 into the host cell.

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“…As a result, improved in silico drug design reduces the time required to develop, design, and optimize a novel drug. The virtual screening approach has been used for decades to find the best lead compounds with various structural properties for use with a given biological target [ 23 ]. Furthermore, computer-aided drug design has been used to find a wide variety of interesting drug applications and hits utilizing virtual screening, molecular docking, and dynamics simulation techniques [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Computer-aided drug design of Azadirachta indica compounds against nervous necrosis virus by targeting grouper heat shock cognate protein 70 (GHSC70): quantum mechanics calculations and molecular dynamic simulation approaches

Islam¹,

Sanjida²,

Mahfuj³

et al. 2022

Genomics Inform

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Nervous necrosis virus (NNV) is a deadly infectious disease that affects several fish species. It has been found that the NNV utilizes grouper heat shock cognate protein 70 (GHSC70) to enter the host cell. Thus, blocking the virus entry by targeting the responsible protein can protect the fishes from disease. The main objective of the study was to evaluate the inhibitory potentiality of 70 compounds of Azadirachta indica (Neem plant) which has been reported to show potential antiviral activity against various pathogens, but activity against the NNV has not yet been reported. The binding affinity of 70 compounds was calculated against the GHSC70 with the docking and molecular dynamics (MD) simulation approaches. Both the docking and MD methods predict 4 (PubChem CID: 14492795, 10134, 5280863, and 11119228) inhibitory compounds that bind strongly with the GHSC70 protein with a binding affinity of –9.7, –9.5, –9.1, and –9.0 kcal/mol, respectively. Also, the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the compounds confirmed the drug-likeness properties. As a result of the investigation, it may be inferred that Neem plant compounds may act as significant inhibitors of viral entry into the host cell. More in-vitro testing is needed to establish their effectiveness.

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In silico study reveals existing drugs as α-glucosidase inhibitors: Structure-based virtual screening validated by experimental investigation

Cited by 12 publications

References 46 publications

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Spike protein recognizer receptor ACE2 targeted identification of potential natural antiviral drug candidates against SARS-CoV-2

Spike Protein Recognizer Receptor ACE2 Targeted Identification of Potential Natural Antiviral Drug Candidates Against SARS-CoV-2

Computer-aided drug design of Azadirachta indica compounds against nervous necrosis virus by targeting grouper heat shock cognate protein 70 (GHSC70): quantum mechanics calculations and molecular dynamic simulation approaches

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