scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

2020 ◽  
Vol 32 (11) ◽  
pp. 2839-2845
Author(s):  
R. Hadanau

A quantitative structure activity relationship (QSAR) analysis was performed on several compound and aurone derivatives (1-16) and 17-21 compounds were used as internal and external tests, respectively. Studies have investigated aurone derivatives; however, for aurone compounds, QSAR analysis has not been conducted. The semi-empirical PM3 method of HyperChem for Windows 8.0 was used to optimise the aurone derivative structures to acquire descriptors. For 15 influential descriptors, the multilinear regression MLR analysis was conducted by employing the backward method, and four new QSAR models were obtained. According to statistical criteria, model 2 was the optimum QSAR model for predicting the inhibition concentration (IC50) theoretical value against novel aurone derivatives. The modelling of 40 (22-61) aurone compounds was achieved. Six novel compounds (54, 55, 58, 59, 60, and 61) were synthesized in a laboratory because the IC50 of these compounds was lower than that of chloroquine (IC50 = 0.14 μM).


Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 789
Author(s):  
Mycal Dutta ◽  
Abu Montakim Tareq ◽  
Ahmed Rakib ◽  
Shafi Mahmud ◽  
Saad Ahmed Sami ◽  
...  

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a contemporary coronavirus, has impacted global economic activity and has a high transmission rate. As a result of the virus’s severe medical effects, developing effective vaccinations is vital. Plant-derived metabolites have been discovered as potential SARS-CoV-2 inhibitors. The SARS-CoV-2 main protease (Mpro) is a target for therapeutic research because of its highly conserved protein sequence. Gas chromatography–mass spectrometry (GC-MS) and molecular docking were used to screen 34 compounds identified from Leucas zeylanica for potential inhibitory activity against the SARS-CoV-2 Mpro. In addition, prime molecular mechanics–generalized Born surface area (MM-GBSA) was used to screen the compound dataset using a molecular dynamics simulation. From molecular docking analysis, 26 compounds were capable of interaction with the SARS-CoV-2 Mpro, while three compounds, namely 11-oxa-dispiro[4.0.4.1]undecan-1-ol (−5.755 kcal/mol), azetidin-2-one 3,3-dimethyl-4-(1-aminoethyl) (−5.39 kcal/mol), and lorazepam, 2TMS derivative (−5.246 kcal/mol), exhibited the highest docking scores. These three ligands were assessed by MM-GBSA, which revealed that they bind with the necessary Mpro amino acids in the catalytic groove to cause protein inhibition, including Ser144, Cys145, and His41. The molecular dynamics simulation confirmed the complex rigidity and stability of the docked ligand–Mpro complexes based on the analysis of mean radical variations, root-mean-square fluctuations, solvent-accessible surface area, radius of gyration, and hydrogen bond formation. The study of the postmolecular dynamics confirmation also confirmed that lorazepam, 11-oxa-dispiro[4.0.4.1]undecan-1-ol, and azetidin-2-one-3, 3-dimethyl-4-(1-aminoethyl) interact with similar Mpro binding pockets. The results of our computerized drug design approach may assist in the fight against SARS-CoV-2.


2021 ◽  
Vol 12 (4) ◽  
pp. 5591-5600

In this study, Crocin, Digitoxigenin, Beta-Eudesmol, and Favipiravir were docked in the active site of SARS-CoV-2 main protease (PDB code: 6LU7). The docking study was followed by Molecular Dynamics simulation. The result indicates that Crocin and Digitoxigenin are the structures with the best affinity in the studied enzyme's binding site. Still, Molecular Dynamics simulation showed that Digitoxigenin is the molecule that fits better in the active site of the main protease. Therefore, this molecule could have a more potent antiviral treatment of COVID-19 than the other three studied compounds.


2022 ◽  
Author(s):  
Mrinal Kanti Si

Abstract The 2019-nCoV virus is a human-infectious coronavirus (CoV). Very few treatment options are available to healthcare professionals who are fighting this outbreak at the front. The main warning symptoms of COVID-19, the disease caused by the new coronavirus, are fever, fatigue, and a dry cough, sometimes it also causes cold-like symptoms like a runny nose which are sometimes similar to symptoms of allergies and sometimes difficult to differentiate between COVID-19 and allergies. The anti-allergic drug molecules can behave as good inhibitor against COVID-19. Molecular docking studies have been performed to examine the inhibitor properties of anti-allergic molecules against Covid-19. The searching of better inhibitors have been examined interns of various non-covalent interactions like hydrogen bond, halogen bond, vander waal’s interactions, alkyl-πand π-π interactions between small molecules (Anti-allergic medicines) with main protease of Covid-19 using molecular docking and Molecular Dynamics simulation which reveals that astemizole is best inhibitor among ten Anti-allergic drug molecules.


2018 ◽  
Vol 10 (1) ◽  
pp. 235
Author(s):  
Muhammad Teguh Setiawan ◽  
Arry Yanuar

Objective: This study aimed to find the herbal compounds from the database of Indonesian herbs with potential for use as histone deacetylase 2 (HDAC2)enzyme inhibitors through virtual screening using the LigandScout program.Methods: Virtual screening was conducted using LigandScout 4.09.3, AutodockZN, and AutoDockTools.Results: The virtual screening process resulted in 10 compounds with the highest pharmacophore fit score rating, from which five compounds withthe best criteria for molecular dynamics simulations were selected: Boesenbergin B, pongachalcone I, 6,8-diprenylgenistein, marmin, and mangostin.The ΔG values obtained were, respectively, −8.28, −9.15, −7.05, −9.07, and −7.15. The active crystal ligand N-(2-aminophenyl) benzamide was used asa positive control, with ΔG value of −10.27. Molecular dynamic’s simulations showed that the activity of HDAC2 inhibitors was known to interact inthe amino acid residues His145C, Tyr308C, Zn379C, Leu276C, Phe155C, Phe210C, Leu144C, and Met35C.Conclusions: Based on virtual screening and the molecular dynamics simulations, marmin was considered to provide the best overall activity ofanalysis. Simulation analysis of molecular dynamics from hits compound showed that analysis with MMGBSA gave higher free energy binding valuethan MMPBSA.


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