Exploring Trop-2–Nanobody PPI Interactions through Molecular Dynamics Simulations and Biovalidations
Abstract
High Resolution Image Download MS PowerPoint Slide The transmembrane glycoprotein Trop-2 has garnered significant attention as a potential therapeutic target due to its involvement in various malignancies, including breast, lung, and prostate cancers. Specifically, the exploration of Trop-2-specific antibodies and nanobodies has emerged as a promising avenue for innovative treatment strategies. Despite advancements, a comprehensive understanding of the intricate molecular interactions between Trop-2 and specific nanobodies remains elusive. In this study, molecular dynamics (MD) simulations with MM/GBSA were employed to investigate the binding poses, key residues, and detailed interactions between Trop-2 and three distinct nanobodies (Nb60, Nb65, and Nb108), which will further guide the development of Trop-2-targeting nanobodies. Our findings corroborated the docking results, highlighting the reliability of binding pose 1. Additionally, our simulations elucidated key residues involved in the interaction interface, particularly within the C-terminal cysteine-poor domain (CPD) and an α-helix region (S170–Y185) on Trop-2. Furthermore, we identified the critical role of the complementarity-determining region 3 (CDR3) length and the key residues involved in the binding of nanobodies to Trop-2. Potential key residues predicted by MD simulations guided the redesign of the CDR3 region of Nb60, generating variants Nb-6, Nb-7, and Nb-14. Experimental data showed that alterations in the CDR3 significantly impacted binding affinity, with Nb-7 exhibiting the highest affinity ( K d value of 7.931 μM), whereas Nb-6 and Nb-14 showed reduced or no binding. This comprehensive analysis provides valuable insights into the molecular mechanisms governing Trop-2–nanobody interactions, facilitating future nanobody engineering efforts for targeted cancer therapy.
Fields of Study & Subjects
Monoclonal and Polyclonal Antibodies Research
Protein Structure and Dynamics
Computational Drug Discovery Methods
Publication details
- Journal / source
- ACS Omega
- Volume
- 11
- Issue
- 10
- Pages
- 16209–16219
- Publication date
- 5 March 2026
- Language
- EN