Scoring close linker analogues in PROTAC ternary complexes: A matched-pose study of VHL-recruiting SHP2 degraders
Year: 2026
Type: preprint
Abstract: Linker optimisation in targeted protein degradation remains largely empirical, and a computational method able to rank close analogues before synthesis would be valuable. Whether current methods can do so has not been tested against the smallest chemical difference that changes potency. Here two VHL-recruiting SHP2 degraders that differ by exactly one methylene, P9 and P10, were compared across 27 ternary complex arrangements generated for both compounds, so that in every comparison the protein–protein geometry was held fixed and only the degrader varied. RxDock interaction scores did not distinguish them (p = 0.66). Prime MM-GBSA favored P9 by 8.1 kcal mol−1, agreeing in direction with the reported potency order (p = 0.040), but the preference was overturned by removing any of twelve individual poses and arose entirely from the generalized-Born solvation term; the nonpolar contribution was zero (−0.01 kcal mol−1, p = 0.97). Interface geometry computed from coordinates alone was indistinguishable between the two ensembles, with buried surface areas differing by 0.23%, and the computed energies were uncorrelated with interface size across a 2.9-fold range (r2 ≤ 0.10). Two further observations emerged: rigid-body docking score did not predict ternary competence, since none of the highest-scoring 1% of arrangements accommodated either degrader, and the longer linker reached ten more arrangements while closing no better within those both could bridge. End-point scoring of single minimized ternary complexes therefore does not resolve a one-methylene linker difference, even when it recovers the correct direction, and conformational averaging rather than a different energy function is the most likely route to improvement. The ternary complex models reported here are the first for this series.
Source: ChemRxiv
Author: Tasniqul Islam
Institution: Northern University Bangladesh
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7215057653