Immunoinformatics and MD-simulation data suggest that Omicron spike epitopes are more interacting to IgG via better MHC recognition than Delta variant

Sarkar, Aniket; Santra, Dipannita; Panja, Anindya Sundar; Maiti, Smarajit

doi:10.1016/j.intimp.2023.110636

Cited by 2 publications

(4 citation statements)

References 45 publications

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“…We can change the html file with Java or WebGL according to the requirements. From iMODS, we can analyze the normal mode analysis of proteins, visualizing modes, root-mean-square fluctuations, visualization modes, and morphing protein …”

Section: Materials and Methodsmentioning

confidence: 99%

“…From iMODS, we can analyze the normal mode analysis of proteins, visualizing modes, root-mean-square fluctuations, visualization modes, and morphing protein. 44 …”

Section: Materials and Methodsmentioning

confidence: 99%

“…From iMODS, we can analyze the normal mode analysis of proteins, visualizing modes, rootmean-square fluctuations, visualization modes, and morphing protein. 44 In this study, the protein−ligand output file was subjected to MD simulations through iMODS (online server). 45 The output file of the best protein−ligand interaction was submitted to the server for evaluation of the stability of the complex.…”

Section: Acsmentioning

confidence: 99%

See 2 more Smart Citations

ExploringCitrus sinensisPhytochemicals as Potential Inhibitors for Breast Cancer Genes BRCA1 and BRCA2 Using Pharmacophore Modeling, Molecular Docking, MD Simulations, and DFT Analysis

Zia,

Parveen,

Shafiq

et al. 2024

ACS Omega

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Background: Structure−activity relationship (SAR) is considered to be an effective in silico approach when discovering potential antagonists for breast cancer due to gene mutation. Major challenges are faced by conventional SAR in predicting novel antagonists due to the discovery of diverse antagonistic compounds. Methodologyand Results: In predicting breast cancer antagonists, a multistep screening of phytochemicals isolated from the seeds of the Citrus sinensis plant was applied using feasible complementary methodologies. A three-dimensional quantitative structure−activity relationship (3D-QSAR) model was developed through the Flare project, in which conformational analysis, pharmacophore generation, and compound alignment were done. Ten hit compounds were obtained through the development of the 3D-QSAR model. For exploring the mechanism of action of active compounds against cocrystal inhibitors, molecular docking analysis was done through Molegro software (MVD) to identify lead compounds. Three new proteins, namely, 1T15, 3EU7, and 1T29, displayed the best Moldock scores. The quality of the docking study was assessed by a molecular dynamics simulation. Based on binding affinities to the receptor in the docking studies, three lead compounds (stigmasterol P8, epoxybergamottin P28, and nobiletin P29) were obtained, and they passed through absorption, distribution, metabolism, and excretion (ADME) studies via the SwissADME online service, which proved that P28 and P29 were the most active allosteric inhibitors with the lowest toxicity level against breast cancer. Then, density functional theory (DFT) studies were performed to measure the active compound's reactivity, hardness, and softness with the help of Gaussian 09 software. Conclusions: This multistep screening of phytochemicals revealed high-reliability antagonists of breast cancer by 3D-QSAR using flare, docking analysis, and DFT studies. The present study helps in providing a proper guideline for the development of novel inhibitors of BRCA1 and BRCA2.

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Section: Materials and Methodsmentioning

confidence: 99%

“…From iMODS, we can analyze the normal mode analysis of proteins, visualizing modes, root-mean-square fluctuations, visualization modes, and morphing protein. 44 …”

Section: Materials and Methodsmentioning

confidence: 99%

Section: Acsmentioning

confidence: 99%

See 1 more Smart Citation

ExploringCitrus sinensisPhytochemicals as Potential Inhibitors for Breast Cancer Genes BRCA1 and BRCA2 Using Pharmacophore Modeling, Molecular Docking, MD Simulations, and DFT Analysis

Zia,

Parveen,

Shafiq

et al. 2024

ACS Omega

View full text Add to dashboard Cite

show abstract

“…Subsequently, the protein binding affinities in terms of binding free energy were calculated for the top four conformations obtained from the docking results using the HawkDock Server [108] . HawkDock, based on the MM/GBSA algorithm, has demonstrated superior performance in predicting relative binding free energies [109] and is widely utilized for protein binding affinity calculations [110] , [111] and complex model predictions [112] , [113] . The binding affinities of the top four conformations for each variant receptor pair are shown in Table S4 .…”

Section: Methodsmentioning

confidence: 99%

Multi-omic analysis characterizes molecular susceptibility of receptors to SARS-CoV-2 spike protein

Wu,

Lin,

Han

et al. 2023

Computational and Structural Biotechnology Journal

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Immunoinformatics and MD-simulation data suggest that Omicron spike epitopes are more interacting to IgG via better MHC recognition than Delta variant

Cited by 2 publications

References 45 publications

ExploringCitrus sinensisPhytochemicals as Potential Inhibitors for Breast Cancer Genes BRCA1 and BRCA2 Using Pharmacophore Modeling, Molecular Docking, MD Simulations, and DFT Analysis

ExploringCitrus sinensisPhytochemicals as Potential Inhibitors for Breast Cancer Genes BRCA1 and BRCA2 Using Pharmacophore Modeling, Molecular Docking, MD Simulations, and DFT Analysis

Multi-omic analysis characterizes molecular susceptibility of receptors to SARS-CoV-2 spike protein

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