Engineering Nanobodies as Selective Binders Targeting CD44 Isoforms

The aberrant expression of CD44 variants has been associated with malignancy of various cancer cells, including glioblastoma, for which effective treatments are unavailable. Moreover, CD44 is a promising therapeutic target for hyaluronic acid (HA)-based drug delivery carriers.

However, an effective stratification based on CD44 isoforms population remains challenging, and deep understanding of isoform-specific HA binding is still lacking. This research aims to develop in-silico binders specifically designed towards different variants of CD44. This will contribute towards the understanding of the link between CD44 variants on the malignancy of cancer cells, and to the development of variant-specific HA-based drug carriers. Finally, this will enable personalised cancer treatment, targeting specific CD44 populations.

The project proposes an in-silico design of antibody fragments (VHH) capable of binding specifically pre-determined paratopes of CD44 isoforms. Our in-house optimisation protocol performs random single point mutation on VHHs, which is followed by conformational sampling with MD simulations to obtain better prediction of binding affinity based on a selection of optimum scoring functions. This protocol could significantly be accelerated with HPC, by enabling many simultaneous MD simulations corresponding to as many mutations. As such, a selection of optimised binders can be obtained more rapidly and proceed towards experimental validation.