Docking with GemDock

Bitencourt-Ferreira, Gabriela; Azevedo, Walter Filgueira de

doi:10.1007/978-1-4939-9752-7_11

Cited by 8 publications

(4 citation statements)

References 86 publications

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“…E ligpre penalizes deviations from ligand preferences. This comprehensive approach helps differentiate active compounds, aiding in the selection of potential binding configurations [39] . The key concept of this evolutionary strategy is to create numerous operators that collaborate utilising a family competition model analogous to a local search approach.…”

Section: Theoretical Calculationsmentioning

confidence: 99%

“…This comprehensive approach helps differentiate active compounds, aiding in the selection of potential binding configurations. [39] The key concept of this evolutionary strategy is to create numerous operators that collaborate utilising a family competition model analogous to a local search approach. For each hormone, iGemDock provides the interface and binding pocket within M pro of nCoV for the requisite interactions.…”

Section: Molecular Docking Studiesmentioning

confidence: 99%

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A Theoretical Study To Understand the Impact of Mpro of nCoV on the Hormones

Babu Singh,

Himani,

Yadav

et al. 2024

ChemistrySelect

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Amidst the unprecedented 2019 coronavirus outbreak and the substantial loss of lives due to the scarcity of information about the virus and lack of viable drugs, understanding the impact of the nCoV Main Protease (Mpro) on the endocrine system has emerged as a critical topic to pursue. This study explores the potential interactions between four key hormones (cortisol, cortisone, estradiol, and estrone) and the Mpro of nCoV using various in‐silico methodologies. Density Functional Theory (DFT) calculations scrutinized the electron density delocalization of these hormones. Through molecular docking, the molecular‐level binding of Mpro of nCoV with these hormones was studied, revealing cortisol as the hormone exhibiting the most promising binding affinity (−100.05 kcal/mol). Furthermore, molecular dynamics (MD) simulations, emulating human body conditions at distinct temperatures, were employed to study the implications of these interactions. The study analysed the various trajectories such as root mean square deviation (RMSD), root mean square fluctuations (RMSF), radius of gyration (Rg), and H‐bond trajectories to understand the potential impact on biological systems. The findings demonstrate the binding potential of the Mpro of nCoV with these hormones, raising plausible concerns regarding consequential physiological changes within the human body.

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Section: Theoretical Calculationsmentioning

confidence: 99%

Section: Molecular Docking Studiesmentioning

confidence: 99%

A Theoretical Study To Understand the Impact of Mpro of nCoV on the Hormones

Babu Singh,

Himani,

Yadav

et al. 2024

ChemistrySelect

View full text Add to dashboard Cite

show abstract

“…Docking methods, meanwhile, offer a route to scan large numbers of molecules against target surfaces but are still not strongly developed for molecule–surface rather than molecule–protein systems and in the latter case are known to have significant limitations. 4–6 Consequently, there is a need for alternative methods that allow for rapid evaluation of the binding affinity of molecules to surfaces and screening for optimal adsorbate–adsorbent pairs.…”

Section: Introductionmentioning

confidence: 99%

“…Accurately capturing all the underlying effects in a simple analytical model is not feasible 12 and thus we turn to a machine learning (ML) approach for prediction. Many groups have already approached the problem of the binding of ligands to specific targets using ML techniques, as well as the more general cases of the prediction of PMFs, potentials for complex systems or indeed entire forcefields, 4,13–19 suggesting this is a suitable methodology to apply to the prediction of molecule–surface adsorption.…”

Section: Introductionmentioning

confidence: 99%