Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Kochl, K; Schopper, T; Durmaz, V; Parigger, L; Singh, A; Krassnigg, A; Cespugli, M; Wu, W; Yang, XL; Zhang, YC; Wang, WWS; Selluski, C; Zhao, TH; Zhang, X; Bai, CH; Lin, L; Hu, YX; Xie, ZW; Zhang, ZH; Yan, J; Zatloukal, K; Gruber, K; Steinkellner, G; Gruber, CC.
Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations
SCI REP-UK. 2023; 13(1): 774
Doi: 10.1038/s41598-023-27636-x
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- Co-Autor*innen der Med Uni Graz
- Zatloukal Kurt
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- 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.