Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent <i>Betacoronavirus</i> strains

Rynkiewicz, Patrick; Lynch, Miranda L.; Cui, Feng; Hudson, André O.; Babbitt, Gregory A.

doi:10.1080/07391102.2021.1953604

Cited by 10 publications

(16 citation statements)

References 69 publications

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“…The B.1.1.7 (alpha) variant has a higher infectivity because of an increased affinity for its prime human epithelial receptor, the ACE2 receptor ( 5 ). One could also hypothesize that a lower viral burden of the B.1.1.7 (alpha) variant (compared to that of non-B.1.1.7 variants) leads to human infections, with a consequently decreased sensitivity of the Ag test.…”

Section: Discussionmentioning

confidence: 99%

Comparison of the Performance of the PanBio COVID-19 Antigen Test in SARS-CoV-2 B.1.1.7 (Alpha) Variants versus non-B.1.1.7 Variants

et al. 2021

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Section: Discussionmentioning

confidence: 99%

Comparison of the Performance of the PanBio COVID-19 Antigen Test in SARS-CoV-2 B.1.1.7 (Alpha) Variants versus non-B.1.1.7 Variants

et al. 2021

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“… Button runs site-wise statistical tests, and R plot ( Figure 3 ) will appear to show positional atom fluctuations along protein sequence for both models, differences in atom fluctuation along the sequence (as dFLUX = signed symmetric Kullback-Leibler or KL divergence), and statistical significance of these dynamic differences along the sequence (as determined via 2 sample Kolmogorov-Smirnov or KS test). See Equation 3 in ( Babbitt et al., 2020a ), Equation 4 in ( Babbitt et al., 2020b ), and Figure 2 from ( Rynkiewicz et al., 2021 ) Button to open GUI for molecular visualization of these results. Optional button to exit DROIDS.…”

Section: Step-by-step Methods Detailsmentioning

confidence: 99%

“…See our software note for details regarding the different metric. Please refer to ( Babbitt et al., 2018 , 2020a , 2020b ; Rynkiewicz et al., 2021 ) (CHECKBOXES) Select protein visual model, color scheme, statistical attributes, and color scaling mode for visualization of DROIDS results in UCSF ChimeraX window. (BUTTON: ‘edit image control file’) - edits DROIDS.ctl with the options selected here.…”

Section: Step-by-step Methods Detailsmentioning

confidence: 99%

“…One can also select to analyze correlations of the motion at these downstream sites to the given amino acid site/position. See Equation 4 from ( Babbitt et al., 2020a ) and Figure 3 from ( Rynkiewicz et al., 2021 ). Push the buttons on the maxDemon GUI in the order in which they are numbered ( Figure 5 ).…”

Section: Step-by-step Methods Detailsmentioning

confidence: 99%

“…For complete details on the use and execution of this profile, please refer to Babbitt et al. (2020b , 2020a , 2018) and Rynkiewicz et al. (2021) .…”

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Statistical machine learning for comparative protein dynamics with the DROIDS/maxDemon software pipeline

et al. 2022

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Design and development of novel potential inhibitors of the human USP21 enzyme using a pharmacophore‐based virtual screening technique

Roy

Luharuka

Paul

et al. 2023

J of Molecular Recognition

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An overexpression and increase have been observed in the concentration and activity of the ubiquitin‐specific protease 21 (USP21) enzyme in many cancers, necessitating the need for the development of new inhibitor drugs against the same. The current study attempts to discover one such novel potential inhibitor of USP21 by the application of various bioinformatics techniques which include molecular modeling, pharmacophore mapping, pharmacophore‐based virtual screening, molecular docking, and ADMET prediction followed by molecular dynamics simulations. Following this inverted funnel‐like approach, we finally ended up with one ligand–ZINC02422616 which displays a very high binding affinity toward the USP21 domain. This ligand contains all the pharmacophoric features displayed by the compounds that are potential inhibitors of the USP21 domain. Moreover, it shows a favorable pharmacokinetic, pharmacodynamic, and ADMET profile, along with strong hydrophobic interaction and hydrogen bonding with the domain. Simulation studies showed that the complex remains stable over time, with the bound protein displaying a more constrained motion in the conformational space compared to the unbound form. The ligand showed a highly favorable free energy landscape/surface, forming several energy minima's in contrast to the unbound domain in which most conformations occupied a relatively higher energy state. Moreover, the ligand also displayed a Kd of 422.8 nM and a free energy of binding ΔG of −8.6 kcal/mol, both of which indicate a very high affinity toward the target domain. This potential drug candidate can then be used as a viable treatment method for many types of cancers caused by USP21.

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Functional binding dynamics relevant to the evolution of zoonotic spillovers in endemic and emergent Betacoronavirus strains

Cited by 10 publications

References 69 publications

Comparison of the Performance of the PanBio COVID-19 Antigen Test in SARS-CoV-2 B.1.1.7 (Alpha) Variants versus non-B.1.1.7 Variants

Comparison of the Performance of the PanBio COVID-19 Antigen Test in SARS-CoV-2 B.1.1.7 (Alpha) Variants versus non-B.1.1.7 Variants

Statistical machine learning for comparative protein dynamics with the DROIDS/maxDemon software pipeline

Design and development of novel potential inhibitors of the human USP21 enzyme using a pharmacophore‐based virtual screening technique

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