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

Babbitt, Gregory A.; Fokoué, Ernest; Srivastava, Harsh; Callahan, Breanna; Rajendran, Madhusudan

doi:10.1016/j.xpro.2022.101194

Cited by 6 publications

(15 citation statements)

References 10 publications

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“…Significance tests and p -values for these site-wise differences were calculated in DROIDS 4.0 using two-sample Kolmogorov-Smirnov tests with the Benjamini-Hochberg multiple test correction in DROIDS 4.0. The mathematical details of DROIDS 4.0 site-wise comparative protein dynamics analysis were published previously by our group and can be found here [30–32]. This code is available at our GitHub web landing: , which is also available at our GitHub repository .…”

Section: Methodsmentioning

confidence: 99%

“…We have recently introduced new statistical applications for comparing the divergence of short-term rapid MD of proteins in functionally relevant molecular binding states (i.e. comparing the divergence of atom fluctuation between bound versus unbound protein states) [30][31][32]. We have applied this computational method to study of the evolution of emergent and endemic viral strains related to SARS-CoV-2 [33] and to the study of the evolution of antibody-binding escape mutations as well [34].…”

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confidence: 99%

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Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

Rajendran

Babbitt

2022

R. Soc. open sci.

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Widespread human transmission of SARS-CoV-2 highlights the substantial public health, economic and societal consequences of virus spillover from wildlife and also presents a repeated risk of reverse spillovers back to naive wildlife populations. We employ comparative statistical analyses of a large set of short-term molecular dynamic (MD) simulations to investigate the potential human-to-bat (genus Rhinolophus ) cross-species infectivity allowed by the binding of SARS-CoV-2 receptor-binding domain (RBD) to angiotensin-converting enzyme 2 (ACE2) across the bat progenitor strain and emerging human strain variants of concern (VOC). We statistically compare the dampening of atom motion across protein sites upon the formation of the RBD/ACE2 binding interface using various bat versus human target receptors (i.e. bACE2 and hACE2). We report that while the bat progenitor viral strain RaTG13 shows some pre-adaption binding to hACE2, it also exhibits stronger affinity to bACE2. While early emergent human strains and later VOCs exhibit robust binding to both hACE2 and bACE2, the delta and omicron variants exhibit evolutionary adaption of binding to hACE2. However, we conclude there is a still significant risk of mammalian cross-species infectivity of human VOCs during upcoming waves of infection as COVID-19 transitions from a pandemic to endemic status.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

Rajendran

Babbitt

2022

R. Soc. open sci.

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“…Molecular dynamic simulation protocols MD simulation protocol was followed as previously described, with slight modifications [30][31][32]41]. Briefly, for each MD comparison, large replicate sets of accelerated MD simulations were prepared and then conducted using the particle mesh Ewald method implemented on the graphical processor unit (GPU) hardware by pmemd.cuda (Amber20) [42][43][44].…”

Section: Model Glycosylationmentioning

confidence: 99%

“…Significance tests and p-values for these site-wise differences were calculated in DROIDS 4.0 using two-sample Kolmogorov-Smirnov tests with the Benjamini-Hochberg multiple test correction in DROIDS 4.0. The mathematical details of DROIDS 4.0 site-wise comparative protein dynamics analysis were published previously by our group and can be found here [30][31][32]. This code is available at our GitHub web landing: https://gbabbitt.github.io/DROIDS-4.0-comparativeprotein-dynamics/ , which is also available at our GitHub repository https://github.com/gbabbitt/DROIDS-4.0comparative-protein-dynamics.…”

Section: Model Glycosylationmentioning

confidence: 99%

“…We have recently introduced new statistical applications for comparing the divergence of short-term rapid MD of proteins in functionally relevant molecular binding states (i.e. comparing the divergence of atom fluctuation between bound vs. unbound protein states) [30][31][32] and applied this to study of the evolution of emergent and endemic viral strains related to SARS-CoV-2 [33]. We have also recently applied this method to the study of the evolution of antibody binding escape mutations as well [34].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

Rajendran

Babbitt

2022

Preprint

Self Cite

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Widespread human transmission of SARS-CoV-2 highlights the substantial public health, economic, and societal consequences of virus spillover from wildlife and also presents a repeated risk of reverse spillovers back to naïve wildlife populations. We employ comparative statistical analyses of a large set of short-term molecular dynamic (MD) simulations to investigate potential human to bat (Rhinolophus macrotis) cross-species infectivity allowed by the binding of SARS-CoV-2 receptor-binding domain (RBD) to angiotensin-converting enzyme 2 (ACE2) across the bat progenitor strain and emerging human strain variants of concern (VOC). We statistically compare the dampening of atom motion during binding across protein sites upon the formation of the RBD/ACE2 binding interface using bat vs. human target receptors (i.e. bACE2 and hACE2). We report that while the bat progenitor viral strain RaTG13 shows some pre-adaption to binding hACE2, it also exhibits stronger overall affinity to bACE2. However, while the early emergent human strains and later VOC’s exhibit robust binding to both hACE2 and bACE2, the delta and omicron variants exhibit evolutionary adaption of binding to hACE2. However, we conclude there is a still significant risk of mammalian cross-species infectivity of human VOC’s during upcoming waves of infection as COVID-19 transitions from a pandemic to endemic status.

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ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison

Babbitt,

Rajendran,

Lynch

et al. 2024

Biophysical Journal

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

Cited by 6 publications

References 10 publications

Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

Persistent cross-species SARS-CoV-2 variant infectivity predicted via comparative molecular dynamics simulation

ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison

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