In Silico Structure-Based Repositioning of Approved Drugs for Spike Glycoprotein S2 Domain Fusion Peptide of SARS-CoV-2: Rationale from Molecular Dynamics and Binding Free Energy Calculations
| Autor: | Hardeep Kaur, Anupam Raja, Harvinder Singh, Subodh Kumar, Phulen Sarma, Pramod Avti, Ajay Prakash, Bikash Medhi, Nishant Shekhar, Saurabh Sharma, Anusuya Bhattacharya, Manisha Prajapat |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
Physiology In silico coronavirus repurposing Computational biology spike protein Biochemistry Microbiology Molecular mechanics molecular mechanics/generalized Born model and solvent accessibility drug discovery 03 medical and health sciences Molecular dynamics 0302 clinical medicine Modelling and Simulation Genetics Binding site Molecular Biology Ecology Evolution Behavior and Systematics repositioning S2 fusion peptide-containing domain Drug discovery Chemistry Therapeutics and Prevention Fusion protein Small molecule free energy QR1-502 molecular dynamics Computer Science Applications 030104 developmental biology molecular dynamics simulation Docking (molecular) Modeling and Simulation docking fusion peptide 030217 neurology & neurosurgery Research Article severe acute respiratory syndrome coronavirus 2 |
| Zdroj: | mSystems mSystems, Vol 5, Iss 5 (2020) |
| ISSN: | 2379-5077 |
| Popis: | The present study provides the structural identification of the viable binding residues of the SARS-CoV-2 S2 fusion peptide region, which holds prime importance in the virus’s host cell fusion and entry mechanism. The classical molecular mechanics simulations were set on values that mimic physiological standards for a good approximation of the dynamic behavior of selected drugs in biological systems. The drug molecules screened and analyzed here have relevant antiviral properties, which are reported here and which might hint toward their utilization in the coronavirus disease 2019 (COVID-19) pandemic owing to their attributes of binding to the fusion protein binding region shown in this study. The membrane-anchored spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a pivotal role in directing the fusion of the virus particle mediated by the host cell receptor angiotensin-converting enzyme 2 (ACE-2). The fusion peptide region of the S protein S2 domain provides SARS-CoV-2 with the biological machinery needed for direct fusion to the host lipid membrane. In our present study, computer-aided drug design strategies were used for the identification of FDA-approved small molecules using the optimal structure of the S2 domain, which exhibits optimal interaction ratios, structural features, and energy variables, which were evaluated based on their performances in molecular docking, molecular dynamics simulations, molecular mechanics/generalized Born model and solvent accessibility binding free energy calculations of molecular dynamics trajectories, and statistical inferences. Among the 2,625 FDA-approved small molecules, chloramphenicol succinate, imipenem, and imidurea turned out to be the molecules that bound the best at the fusion peptide hydrophobic pocket. The principal interactions of the selected molecules suggest that the potential binding site at the fusion peptide region is centralized amid the Lys790, Thr791, Lys795, Asp808, and Gln872 residues. IMPORTANCE The present study provides the structural identification of the viable binding residues of the SARS-CoV-2 S2 fusion peptide region, which holds prime importance in the virus’s host cell fusion and entry mechanism. The classical molecular mechanics simulations were set on values that mimic physiological standards for a good approximation of the dynamic behavior of selected drugs in biological systems. The drug molecules screened and analyzed here have relevant antiviral properties, which are reported here and which might hint toward their utilization in the coronavirus disease 2019 (COVID-19) pandemic owing to their attributes of binding to the fusion protein binding region shown in this study. |
| Databáze: | OpenAIRE |
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