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Single-Sequence Deep Learning Delivers Crystal-Quality Models of Covalent K-Ras G12 Hotspot Complexes - PubMed

2 hours ago
  • #KRAS
  • #Deep Learning
  • #Covalent Inhibitors
  • Chai-1 predicts covalent K-Ras(G12C) complex structures accurately without MSA.
  • Achieves pocket-aligned RMSDs < 2 Å for diverse inhibitors (ARS-853 to BBO-8520).
  • Successfully models binding poses for K-Ras(G12D) and K-Ras(G12S) inhibitors.
  • Limitations include handling leaving groups, bond properties, and stereochemistry.
  • Provides ~40-fold higher throughput than AlphaFold3 with comparable accuracy.
  • Offers an efficient tool for accelerating covalent drug discovery beyond cysteine.