About: The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site and assed their druggability. These pockets can aid in virtual screening efforts to identify a protease inhibitor for the treatment of COVID-19.

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About: The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site and assed their druggability. These pockets can aid in virtual screening efforts to identify a protease inhibitor for the treatment of COVID-19. Goto Sponge NotDistinct Permalink

An Entity of Type : fabio:Abstract, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	abstract
value	The SARS-CoV-2 pandemic has rapidly spread across the globe, posing an urgent health concern. Many quests to computationally identify treatments against the virus rely on in silico small molecule docking to experimentally determined structures of viral proteins. One limit to these approaches is that protein dynamics are often unaccounted for, leading to overlooking transient, druggable conformational states. Using Gaussian accelerated molecular dynamics to enhance sampling of conformational space, we identified cryptic pockets within the SARS-CoV-2 main protease, including some within regions far from the active site and assed their druggability. These pockets can aid in virtual screening efforts to identify a protease inhibitor for the treatment of COVID-19.
subject	Virology Classical mechanics 2019 disasters in China
part of	Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease
is abstract of	Elucidation of cryptic and allosteric pockets within the SARS-CoV-2 protease
is hasSource of	covid:ann/target/e8c05f4ca816cb26c1d67722fdb2d29b06f174b4 covid:ann/target/4913ddeac7f8b36eca96b7e48a605aced575e720 covid:ann/target/5c67dd8b2ce51d45326d6e36dc376f5542cb1394 covid:ann/target/45df69507e056c4dbd5bf3b438837b70d2dc6a57 covid:ann/target/6f7d6ac8247c1016ac00a7ec1dd889193cece0f6 »more»

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