Computational studies of drug repurposing and synergism of lopinavir, oseltamivir and ritonavir binding with SARS-CoV-2 protease against COVID-19
By Nisha Muralidharan, R. Sakthivel, Devadasan Velmurugan, M. Michael Gromiha. Journal of Biomolecular Structure and Dynamics, 2020
374 citations recorded by the source corpus.
A novel coronavirus (SARS-CoV-2) has caused a major outbreak in humans all over the world, and it is the latest pandemic in the series of other infectious diseases. The concept of drug repurposing has been used successfully for many years for known diseases. Considering the emergency and urgency, drug repurposing concept is being explored for coronavirus disease (COVID-19) as well. Recently, the combination of three known drugs, lopinavir, oseltamivir and ritonavir has been proposed to control the virulence to a great extent in COVID-19 affected patients within 48 hours. Hence, we tried to understand the effect of synergism of these drugs against the SARS-CoV-2 protease using sequential docking studies. As a result, combination of three drugs showed a better binding energy than that of individual drugs. Further, the complex was subjected to molecular dynamics simulations to get insights into the stability of the complex, considering the simultaneous interactions between three drugs and the protein. The protein complexed with three drugs remained stable during the simulations. Hence, these drugs can be explored further for drug repurposing against the successful inhibition of COVID-19.
Subfields: Computational Theory and Mathematics, Infectious Diseases
View Paper: https://www.semanticscholar.org/paper/f516c15e014ad59581fb54f9a19be4909da3ce8a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Theory and Mathematics
In Infectious Diseases
Citations in the corpus
- Using X-ray images and deep learning for automated detection of coronavirus disease (2020, background): “…December 2019 (Aanouz et al., 2020; Elfiky & Azzam, 2020; Elmezayen et al., 2020; Enayatkhani et al., 2020; Fausto et al., 2020; Ghosh et al., 2020; Muralidharan et al., 2020; Phulen et al., 2020; Rajib et al., 2020; Rothan & Byrareddy, 2020; Rowan & Laffey, 2020; Salman et al., 2020; Sourav et…”
- SARS-CoV-2 RNA dependent RNA polymerase (RdRp) targeting: an in silico perspective (2020, background): “…anti-viral drugs and compounds against the coronavirus proteins (Aanouz et al., 2020; Boopathi et al., 2020; Elfiky & Azzam, 2020; Elmezayen et al., 2020; Enayatkhani et al., 2020; Gupta et al., 2020; Khan et al., 2020a, 2020b; Muralidharan et al., 2020; Pant et al., 2020; Sarma et al., 2020).”
- Automated medical diagnosis of COVID-19 through EfficientNet convolutional neural network (2020, methodology): “role in the development of new methods to support virus diagnostics [18,19].”