Biology subjects

Pallara, C.

Publications and source records attributed to Pallara, C..

2 recordsLinked to original sources

bioRxiv2025

Characterization of PROTACs by Ternary Complex Landscape Exploration using Monte Carlo simulations

PROTACs (Proteolysis-Targeting Chimeras) have emerged as a powerful modality for targeted protein degradation, yet their optimization still relies heavily on trial-and-error methods. A key factor in PROTAC degradation efficiency is the formation of the ternary complex (TC) between the PROTAC and its target proteins. However, due to their dynamic nature, PROTAC-mediated TCs can adopt multiple conformations, making their characterization challenging. Computational methods that account for this flexibility can provide more accurate predictions aligned with experimental results. Here, we explore the dynamic nature of TCs by analyzing their energy landscapes using protein-protein docking coupled with Monte Carlo sampling. This approach enables the identification of energetically relevant TC conformations, including those observed in experimental crystal structures, and allows estimation of thermodynamic and kinetic stability, as shown for a set of VHL-WDR5 PROTACs. Insights from these landscapes could support the screening and optimization of tens of similar PROTACs based on TC stability.

biophysics↗

bioRxiv2025

Efficient Design of Affilin(R) Protein Binders for HER3

Engineered scaffold-based proteins that bind to concrete targets with high affinity offer significant advantages over traditional antibodies in theranostic applications. Their development often relies on display methods, where large libraries of variants are physically contacted with the desired target protein and pools of binding variants can be selected. Herein, we use a combined artificial intelligence/physics-based computational framework and phage display approach to obtain ubiquitin based Affilin(R) proteins targeting the HER3 extracellular domain, a relevant tumor target. We demonstrate that the developed in silico pipeline can generate de novo Affilin(R) proteins with high experimental success rate using a small training set of sequences (<1000 sequences). The classical phage display yielded primary candidates with low nanomolar affinities. These binders could be further optimized by phage display and computational maturation alike. These combined efforts resulted in four HER3 ligands with high affinity, cell binding, and serum stability that have theranostic potential.

biochemistry↗