Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies

Elbadwi, Fatima A.; Khairy, Elaf A.; Alsamani, Fatima O.; Mahadi, Mariam A.; Abdalrahman, Segood E.; Ahmed, Zain Alsharf M.; Elsayed, Inas; Ibraheem, Walaa; Alzain, Abdulrahim A.

doi:10.1016/j.imu.2021.100725

Cited by 21 publications

(15 citation statements)

References 32 publications

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“…The active site of the TMPRSS2 showed hydrogen bonding with the residues SER460, ASN418, LYN342, THR341, PO4501, GLU299, GLY464, ASP435, ASN343, ASP345, LYS342, TYR337 which played a significant role in binding with the ligands as analyzed from the binding interaction analysis. Similar results with different molecules were shown in different computational and experimental studies [ 36 , 46 , [63] , [64] , [65] , [66] , [67] , [68] , [69] , [70] , [71] ]. In our previous work, GLU299, GLY464, ASP435, PO4501, SER460, SER436, LYS342, ASN418, LYS340, TRP461, PO4 501, THR341 showed H-bond with the ligand [ 46 , 64 ].…”

Section: Discussionsupporting

confidence: 88%

“…Similar results with different molecules were shown in different computational and experimental studies [ 36 , 46 , [63] , [64] , [65] , [66] , [67] , [68] , [69] , [70] , [71] ]. In our previous work, GLU299, GLY464, ASP435, PO4501, SER460, SER436, LYS342, ASN418, LYS340, TRP461, PO4 501, THR341 showed H-bond with the ligand [ 46 , 64 ]. In a work done by Idris M. et al group LYN342, Asp435, SER460, SER436, TRP461, GLY464, LYN342 showed H-bond with the ligand [ 69 ] also Asp435, SER436, TRP461, GLY464, GLU 299, LYS342 showed the same interactions in a work conducted by Kumar V. et al group [ 68 ].…”

Section: Discussionsupporting

confidence: 88%

“…We use the optimization panel of the Jaguar program [ 58 ] to perform DFT calculations for top-3 docking fragments. We chose 6-31G**as the basis set and B3LYP as the level of theory as it is the most used basis set for small organic compounds [ 46 , 47 , 59 , 60 ]. Standard Poisson-Boltzmann (PBF) was used as the solvation model in which water was selected as a solvent, which is included in the calculation as a dielectric continuum with a cavity for the molecule, water is the solvent and the geometries were optimized 100 times.…”

Section: Methodsmentioning

confidence: 99%

“…In our previous studies, TMPRSS2 inhibitors were investigated using in silico drug repurposing and pharmacophore modeling approaches [ 46 , 47 ]. In this article, we used a fragment-based drug design approach to discover novel TMPRSS2 inhibitors to combat COVID-19.…”

Section: Introductionmentioning

confidence: 99%

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Discovery of novel TMPRSS2 inhibitors for COVID-19 using in silico fragment-based drug design, molecular docking, molecular dynamics, and quantum mechanics studies

Alzain

Elbadwi

Alsamani

2022

Informatics in Medicine Unlocked

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The global expansion of COVID-19 and the mutations of severe acute respiratory syndrome coronavirus necessitate quick development of treatment and vaccination. Because the androgen-responsive serine protease TMPRSS2 is involved in cleaving the SARS-CoV-2 spike protein allowing the virus to enter the cell, therefore, direct TMPRSS2 inhibition will inhibit virus activation and disease progression which make it an important target for drug discovery. In this study, a homology model of TMPRSS2 protein was initially developed. Then, we used the fragment-based drug design (FBDD) technique to develop effective TMPRSS2 inhibitors. Over a half-million fragments from the enamine database, were screened for their binding ability to target protein, and then best-scoring fragments were linked to building new molecules with a good binding affinity. XP docking and MM-GBSA studies revealed 10 new-formed molecules with docking score ≤ −14.982 kcal/mol compared to ambroxol (control) with a docking score of −6.464 kcal/mol. Finally, molecular dynamics (MD) and density functional theory (DFT) were calculated for the top 3 molecules.

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Section: Discussionsupporting

confidence: 88%

Section: Discussionsupporting

confidence: 88%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Discovery of novel TMPRSS2 inhibitors for COVID-19 using in silico fragment-based drug design, molecular docking, molecular dynamics, and quantum mechanics studies

Alzain

Elbadwi

Alsamani

2022

Informatics in Medicine Unlocked

Self Cite

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“…The TMPRSS2 enzyme of SARS-CoV-2 is also considered a target for the suppression of virus infection. Elbadwi et al applied structure-based virtual screening to search for drugs with the potential to target SARS-CoV-2 TMPRSS2, and identified 5 commercially available drugs amikacin, isepamicin, butikacin, lividomycin, and paromomycin, possibly having inhibitory abilities against the TMPRSS2 enzyme [ 58 ]. Hamdy et al applied an iterated virtual screening method to re-screened M pro effective compounds against a TMPRSS2 structure (PDB: 2OQ5) using molecular docking [ 59 ].…”

Section: R Epurposed T Herapeutic ...mentioning

confidence: 99%

Computer-aided discovery, design, and investigation of COVID-19 therapeutics

Liou

Chang

Hsu

et al. 2022

Tzu Chi Medical Journal

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A BSTRACT Coronavirus disease 2019 (COVID-19) pandemic is currently the most serious public health threat faced by mankind. Thus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, is being intensively investigated. Several vaccines are now available for clinical use. However, owing to the highly mutated nature of RNA viruses, the SARS-CoV-2 is changing at a rapid speed. Breakthrough infections by SARS-CoV-2 variants have been seen in vaccinated individuals. As a result, effective therapeutics for treating COVID-19 patients is urgently required. With the advance of computer technology, computational methods have become increasingly powerful in the biomedical research and pharmaceutical drug discovery. The applications of these techniques have largely reduced the costs and simplified processes of pharmaceutical drug developments. Intensive and extensive studies on SARS-CoV-2 proteins have been carried out and three-dimensional structures of the major SARS-CoV-2 proteins have been resolved and deposited in the Protein Data Bank. These structures provide the foundations for drug discovery and design using the structure-based computations, such as molecular docking and molecular dynamics simulations. In this review, introduction to the applications of computational methods in the discovery and design of novel drugs and repurposing of existing drugs for the treatments of COVID-19 is given. The examples of computer-aided investigations and screening of COVID-19 effective therapeutic compounds, functional peptides, as well as effective molecules from the herb medicines are discussed.

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Discovery of novel glucosinolates inhibiting advanced glycation end products: Virtual screening and molecular dynamic simulation

et al. 2023

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Protein glycation can result in the formation of advanced glycation end products (AGEs), which pose a potential health risk due to their association with diabetic complications. Natural products are a source of drugs discovery and the search for potential natural inhibitors of AGEs is of great significance. Glucosinolates (GSLs) mainly from cruciferous plants have potential antioxidant, anti‐inflammatory, and anti‐glycation activities. In this study, the inhibitory activity of GSLs on bovine serum albumin (BSA) along with its mechanism was investigated by virtual screening and various computational simulation techniques. Virtual screening revealed that 174 GSLs were screened using Maestro based on the glide score and 89% of the compounds were found to have potential anti‐glycation ability with the docking scores less than −5 kcal/mol. Molecular docking showed that the top 10 GSLs were bound to the IIA structural domain of BSA. Among them, glucohesperin (1) and 2‐hydroxyethyl glucosinolate (2) had the lowest docking scores of −9.428 and −9.333 kcal/mol, respectively, reflecting their good binding affinity. Molecular dynamics simulations of 1 (ΔG = −43.46 kcal/mol) and 2 (ΔG = −43.71 kcal/mol) revealed that the complexes of these two compounds with proteins had good stability. Further binding site analysis suggested that the mechanism of inhibition of protein glycation by these two active ingredients might be through competitive hydrogen bonding to maintain the structural integrity of the protein, thus inhibiting glycation reaction. Moreover, the ADMET values and CYP450 metabolism prediction data were within the recommended values. Therefore, it can be concluded that 1 and 2 may act as potential anti‐glycation agents.

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Identification of novel transmembrane Protease Serine Type 2 drug candidates for COVID-19 using computational studies

Cited by 21 publications

References 32 publications

Discovery of novel TMPRSS2 inhibitors for COVID-19 using in silico fragment-based drug design, molecular docking, molecular dynamics, and quantum mechanics studies

Discovery of novel TMPRSS2 inhibitors for COVID-19 using in silico fragment-based drug design, molecular docking, molecular dynamics, and quantum mechanics studies

Computer-aided discovery, design, and investigation of COVID-19 therapeutics

Discovery of novel glucosinolates inhibiting advanced glycation end products: Virtual screening and molecular dynamic simulation

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