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Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations.
Köchl, Katharina; Schopper, Tobias; Durmaz, Vedat; Parigger, Lena; Singh, Amit; Krassnigg, Andreas; Cespugli, Marco; Wu, Wei; Yang, Xiaoli; Zhang, Yanchong; Wang, Welson Wen-Shang; Selluski, Crystal; Zhao, Tiehan; Zhang, Xin; Bai, Caihong; Lin, Leon; Hu, Yuxiang; Xie, Zhiwei; Zhang, Zaihui; Yan, Jun; Zatloukal, Kurt; Gruber, Karl; Steinkellner, Georg; Gruber, Christian C.
  • Köchl K; Innophore GmbH, 8010, Graz, Austria.
  • Schopper T; Austrian Centre of Industrial Biotechnology, 8010, Graz, Austria.
  • Durmaz V; Innophore GmbH, 8010, Graz, Austria.
  • Parigger L; Innophore GmbH, 8010, Graz, Austria.
  • Singh A; Innophore GmbH, 8010, Graz, Austria.
  • Krassnigg A; Innophore GmbH, 8010, Graz, Austria.
  • Cespugli M; Institute of Molecular Bioscience, University of Graz, 8010, Graz, Austria.
  • Wu W; Innophore GmbH, 8010, Graz, Austria.
  • Yang X; Innophore GmbH, 8010, Graz, Austria.
  • Zhang Y; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Wang WW; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Selluski C; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Zhao T; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Zhang X; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Bai C; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Lin L; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Hu Y; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Xie Z; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Zhang Z; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Yan J; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Zatloukal K; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Gruber K; SignalChem Lifesciences Corp., 110-13120 Vanier Place, Richmond, BC, V6V 2J2, Canada.
  • Steinkellner G; Diagnostic- and Research Center for Molecular Biomedicine, Institute of Pathology, Medical University of Graz, 8010, Graz, Austria.
  • Gruber CC; Innophore GmbH, 8010, Graz, Austria.
Sci Rep ; 13(1): 774, 2023 01 14.
Article in English | MEDLINE | ID: covidwho-2186078
ABSTRACT
Treatment of COVID-19 with a soluble version of ACE2 that binds to SARS-CoV-2 virions before they enter host cells is a promising approach, however it needs to be optimized and adapted to emerging viral variants. The computational workflow presented here consists of molecular dynamics simulations for spike RBD-hACE2 binding affinity assessments of multiple spike RBD/hACE2 variants and a novel convolutional neural network architecture working on pairs of voxelized force-fields for efficient search-space reduction. We identified hACE2-Fc K31W and multi-mutation variants as high-affinity candidates, which we validated in vitro with virus neutralization assays. We evaluated binding affinities of these ACE2 variants with the RBDs of Omicron BA.3, Omicron BA.4/BA.5, and Omicron BA.2.75 in silico. In addition, candidates produced in Nicotiana benthamiana, an expression organism for potential large-scale production, showed a 4.6-fold reduction in half-maximal inhibitory concentration (IC50) compared with the same variant produced in CHO cells and an almost six-fold IC50 reduction compared with wild-type hACE2-Fc.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Deep Learning / COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Variants Limits: Animals Language: English Journal: Sci Rep Year: 2023 Document Type: Article Affiliation country: S41598-023-27636-x

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Deep Learning / COVID-19 Type of study: Experimental Studies / Prognostic study Topics: Variants Limits: Animals Language: English Journal: Sci Rep Year: 2023 Document Type: Article Affiliation country: S41598-023-27636-x