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Targeting SARS-CoV-2 main protease by teicoplanin: A mechanistic insight by docking, MM/GBSA and molecular dynamics simulation.

ABSTRACT: First emerged in late December 2019, the outbreak of novel severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) pandemic has instigated public-health emergency around the globe. Till date there is no specific therapeutic agent for this disease and hence, the world is craving to identify potential antiviral agents against SARS-CoV-2. The main protease (M^Pro) is considered as an attractive drug target for rational drug design against SARS-CoV-2 as it is known to play a crucial role in the viral replication and transcription. Teicoplanin is a glycopeptide class of antibiotic which is regularly used for treating Gram-positive bacterial infections, has shown potential therapeutic efficacy against SARS-CoV-2 in vitro. Therefore, in this study, a mechanistic insight of intermolecular interactions between teicoplanin and SARS-CoV-2 M^Pro has been scrutinized by molecular docking. Both monomeric and dimeric forms of M^Pro was used in docking involving blind as well as defined binding site based on the known inhibitor. Binding energies of teicoplanin-M^Pro complexes were estimated by Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) computations from docking and simulated trajectories. The dynamic and thermodynamics constraints of docked drug in complex with target proteins under specific physiological conditions was ascertained by all-atom molecular dynamics simulation of 100 ns trajectory. Root mean square deviation and fluctuation of carbon α chain justified the stability of the bound complex in biological environments. The outcomes of current study are supposed to be fruitful in rational design of antiviral drugs against SARS-CoV-2.

SUBMITTER: Azam F

PROVIDER: S-EPMC8286173 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Alzheimer's disease (AD) leads to gradual memory loss including other compromised cognitive abilities. Acetylcholinesterase (AChE), an important biochemical enzyme from the cholinesterase (ChE) family, is recognized as primary pharmacological target for treating AD. Currently marketed drugs for AD treatment are primarily AChE inhibitors and coumarin derivatives comprising a wide variety of pharmacological activities have proved their efficacy towards AChE inhibition. Ensaculin (KA-672 HCl), a compound that belong to the coumarin family, is a clinical trial candidate for AD treatment. Therefore, a ligand library was prepared with 60 reported coumarin derivatives for field-based 3D-QSAR and pharmacophore modelling. The field-based 3D-QSAR model obtained at partial least square (PLS) factor 7, was the best validated model that predicted activity closer to original activity for each ligand introduced. The contour maps demonstrated spatial distribution of favourable and unfavorable steric, hydrophobic, electrostatic and H-bond donor and acceptor contours around coumarin nucleus. The best pharmacophore model, ADHRR_1 exhibited five essential pharmacophoric features of four different traits for optimum AChE inhibition. Virtual screening through ADHRR_1 accompanied with molecular docking and MM/GBSA identified 10 HITs from a 4,00,000 coumarin derivatives from PubChem database. HITs comprised docking scores ranging from -12.096 kcal/mol to -8.271 kcal/mol and compared with the reference drug Donepezil (-8.271 kcal/mol). ADME properties analysis led into detecting two leads (HIT 1 and HIT 2) among these 10 HITs. Molecular Dynamics Simulation indicated thermodynamic stability of the complex of lead compounds with AChE protein. Finally, thorough survey of the experimental results from 3D-QSAR modelling, pharmacophore modelling and molecular docking interactions led us to develop the lead formula I for future advancements in treating AD through AChE inhibitors.

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Targeting SARS-CoV-2 main protease by teicoplanin: A mechanistic insight by docking, MM/GBSA and molecular dynamics simulation.

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