GC-MS analysis of phytoconstituents from <i>Ruellia prostrata</i> and <i>Senna tora</i> and identification of potential anti-viral activity against SARS-CoV-2

Alam, Rahat; Imon, Raihan Rahman; Talukder, Md. Enamul Kabir; Akhter, Shahin; Hossain, Md. Alam; Ahammad, Foysal; Rahman, Md. Shahedur

doi:10.1039/d1ra06842c

Cited by 24 publications

(16 citation statements)

References 71 publications

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“…Other existing drugs, such as lopinavir, oseltamivir, ritonavir, atazanavir, darunavir, plitidepsin, testosterone, progesterone, hydroxychloroquine, tetracyclines, flaviolin, hydroxyethylamine analogs, buriti oil (mauritia flexuosa L.) like inhibitors, etc., were also investigated specifically by docking and MD simulations. 397 , 614 , 1048 − 1073 …”

Section: Methods and Approachesmentioning

confidence: 99%

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Gao¹,

Wang²,

Chen³

et al. 2022

Chem. Rev.

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Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein–protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

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Section: Methods and Approachesmentioning

confidence: 99%

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Gao¹,

Wang²,

Chen³

et al. 2022

Chem. Rev.

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“…Compound pharmacokinetics and compound pharmacodynamics are used in such models. COVID-19, an infectious viral disease, is the most recent example of how mathematical models are employed in drug discovery [36].…”

Section: Mathematical Models In Drug Designmentioning

confidence: 99%

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

Hasan

Alsaiari

Fakhurji³

et al. 2022

Molecules

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The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure–activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.

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“…A prior study has used GC-MS analysis to identify fifty-six bioactive compounds from a methanolic extract of Tinospora crispa, in which the top nine hits showed a strong affinity with the SARS-CoV-2 main protease (Mpro) enzyme [22]. Similarly, a recent study has found that Ruellia prostrata and Senna tora extracts contained a total of forty-three and fifty-three phytochemicals, respectively, identified through the GC-MS analytical method, in which the best four compounds were selected for future drug development based on molecular docking and MD simulation analyses [23]. The plant metabolites including terpenoids, polyphenols, and phytosterols of natural origin have potential pharmacological and medicinal applications in various stages of basic and clinical research.…”

Section: Gc-ms Analysis Of Moringa Oleifera Leafmentioning

confidence: 99%

Interaction of Bioactive Compounds of Moringa oleifera Leaves with SARS-CoV-2 Proteins to Combat COVID-19 Pathogenesis: a Phytochemical and In Silico Analysis

Siddiqui

Upadhyay

Ahmad

et al. 2022

Appl Biochem Biotechnol

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Novel SARS-CoV-2 claimed a large number of human lives. The main proteins for viral entry into host cells are SARS-CoV-2 spike glycoprotein (PDB ID: 6VYB) and spike receptor-binding domain bound with ACE2 (spike RBD-ACE2; PDB ID: 6M0J). Currently, specific therapies are lacking globally. This study was designed to investigate the bioactive components from Moringa oleifera leaf (MOL) extract by gas chromatographymass spectroscopy (GC-MS) and their binding interactions with spike glycoprotein and spike RBD-ACE2 protein through computational analysis. GC-MS-based analysis unveiled the presence of thirty-seven bioactive components in MOL extract, viz. polyphenols, fatty acids, terpenes/triterpenes, phytosterols/steroids, and aliphatic hydrocarbons. These bioactive phytoconstituents showed potential binding with SARS-CoV-2 spike glycoprotein and spike RBD-ACE2 protein through the AutoDock 4.2 tool. Further by using AutoDock 4.2 and AutoDock Vina, the top sixteen hits (binding energy ≥ − 6.0 kcal/mol) were selected, and these might be considered as active biomolecules. Moreover, molecular dynamics simulation was determined by the Desmond module. Interestingly two biomolecules, namely β-tocopherol with spike glycoprotein and β-sitosterol with spike RBD-ACE2, displayed the best interacting complexes and low deviations during 100-ns simulation, implying their strong stability and compactness. Remarkably, both β-tocopherol and β-sitosterol also showed the drug-likeness with no predicted toxicity. In conclusion, these findings suggested that both compounds β-tocopherol and β-sitosterol may be developed as anti-SARS-CoV-2 drugs. The current findings of in silico approach need to be optimized using in vitro and clinical studies to prove the effectiveness of phytomolecules against SARS-CoV-2.

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GC-MS analysis of phytoconstituents from Ruellia prostrata and Senna tora and identification of potential anti-viral activity against SARS-CoV-2

Abstract: Protease (Mpro) of SARS-CoV-2 has been identified as being able to hinder the replication process of the virus. Using GC-MS analytical methods, phytochemicals were identified from different medicinal plants that resulted in inhibitory activity of the molecules against Mpro.

Cited by 24 publications

References 71 publications

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

Interaction of Bioactive Compounds of Moringa oleifera Leaves with SARS-CoV-2 Proteins to Combat COVID-19 Pathogenesis: a Phytochemical and In Silico Analysis

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