Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation

Aziz, Shahkaar; Waqas, Muhammad; Mohanta, Tapan Kumar; Halim, Sobia Ahsan; Iqbal, Aqib; Ali, Amjad; Khalid, Asaad; Abdalla, Ashraf N.; Khan, Ajmal; Al‐Harrasi, Ahmed

doi:10.1016/j.jiph.2023.02.009

Cited by 11 publications

(1 citation statement)

References 92 publications

(102 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Molecular dynamics simulation is yet another in silico technique for investigating drug-receptor interactions. In order to predict the dynamic behavior of the protein-ligand complex, this method simulates the movement and behavior of atoms and molecules throughout the simulation time [57]. The molecular dynamics simulation approach also reveals the interatomic interaction mechanisms and the binding energy of complexes.…”

Section: In Silico Studies For Drug Discoverymentioning

confidence: 99%

Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors

Mushebenge,

Ugbaja,

Mbatha

et al. 2023

IJMS

View full text Add to dashboard Cite

The COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, and transmembrane protease serine 2 (TMPRSS2). In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat Mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of the drug candidates to target receptors, providing insight into their potential efficacy. This study is aimed at assessing the useful contributions of the application of computational instruments in the discovery of receptors targeted in SARS-CoV-2. It further highlights some identified advantages and limitations of these studies, thereby revealing some complementary experimental validation to ensure the efficacy and safety of identified drug candidates.

show abstract

Section: In Silico Studies For Drug Discoverymentioning

confidence: 99%

Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors

Mushebenge,

Ugbaja,

Mbatha

et al. 2023

IJMS

View full text Add to dashboard Cite

show abstract

Computational Screening of FDA‐Approved Hepatitis C Drugs for Inhibition of VEGFR2 in Liver Cancer

Roney,

Issahaku,

Tufail

et al. 2024

ChemistrySelect

View full text Add to dashboard Cite

Liver cancer (LC) is one of the most common tumours and the leading cause of cancer‐related death globally. Amidst the problems associated with existing treatments, such as hepatotoxicity, recurrence, drug resistance, and other adverse effects, researchers are under pressure to find alternatives. Towards a comprehensive rationalisation of the search for new anti‐LC drugs among approved ones, we employed an in‐silico approach to accelerate the selection of the most efficacious LC drugs. The FDA‐approved hepatitis C virus (HCV) drugs were docked with the LC protein using the AutoDock Vina software. Compared to the control compound, two FDA‐approved HCV drugs (DB09102 and DB09027) were selected based on their binding energies and interactions with the target protein, which showed comparable binding energies. Furthermore, these compounds were then subjected to molecular dynamic simulation, principle component analysis, and MMGBSA using the AMBER20 software, and the results showed stable complexes compared to the control complex. All things considered, this study will help the scientific community and society find a novel drug to treat LC.

show abstract

Structure-Based Drug Design of RdRp Inhibitors against SARS-CoV-2

Shehzadi

Saba

et al. 2023

Top Curr Chem (Z)

View full text Add to dashboard Cite

Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation

Cited by 11 publications

References 92 publications

Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors

Assessing the Potential Contribution of In Silico Studies in Discovering Drug Candidates That Interact with Various SARS-CoV-2 Receptors

Computational Screening of FDA‐Approved Hepatitis C Drugs for Inhibition of VEGFR2 in Liver Cancer

Structure-Based Drug Design of RdRp Inhibitors against SARS-CoV-2

Contact Info

Product

Resources

About