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bioRxiv · 10.64898/2026.09.15.751854

Two Comparators May Be All We Need

Abstract

A compound in a cell meets a spectrum of proteins drawn from many families at once, while screening most often interrogates one target at a time. Two questions asked many times in a rank ordering workflow ultimately guide decisions on what gets made and what gets counter-screened, and both are comparative: which of two targets does a compound prefer, and which of two compounds does a target prefer. We built one model for each: the target comparison over a roster of 2,279 human proteins in 34 protein families, the compound comparison over 2,079 in 32. Each model is given two chemical structures and a sequence, or two sequences and a chemical structure, and returns which member of the pair is preferred together with how firmly it holds that view. No conformational analysis, protein structure, binding site or docked pose is used. Asked which of two targets a compound prefers, the model is correct 0.75 of the time over 8,689 held-out comparisons setting two families against each other, and 0.78 of the time over 32,738 comparisons between two targets of one family, rising to 0.94 and 0.95 on the most confident third of each. Asked which of two compounds a single target prefers, it is correct 0.71 of the time over 65,725 held-out comparisons, rising to 0.96 on the most confidently held. Neither compound in any of those comparisons appeared anywhere in training. Accuracy follows the gap between the two measurements. Where they sit within half a log unit the models are right 0.57 to 0.64 of the time, and where they differ by more than two logs, 0.90 to 0.92. The compound result holds across 31 protein families, not only the best-measured one. Within the chemistry and the targets they were built on, these models rank compounds and rank targets well. Both models can be explored and downloaded at familyfoundationmodel.com. Keywords: target preference; compound preference; pairwise comparison; polypharmacology; off-target triage; ESM2; random forest; structure-free prediction; ChEMBL

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BibTeXRIS

Muskal, S. M.. 2026-09-21. Two Comparators May Be All We Need. https://doi.org/10.64898/2026.09.15.751854

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