Discontinuous Epitope Fragments as Sufficient Target Templates for Efficient Binder Design

Zhenfeng Deng, Ruijie Hou, Ningrui Xie, Mike Tyers, Michał Koziarski

Track: Track 1: Original Research/Position/Education/Attention Track

Keywords: Drug Discovery, Biophysics

TL;DR: Binder design can be performed with only epitope fragments—the discontinuous, non-self-folding residues surrounding the binding interface, which can yield up to 80% higher in silico success and up to forty-fold gain in design efficiency.

Abstract:

Recent advances in structure-based protein design have accelerated $\textit{de novo}$ binder generation, yet interfaces on large domains or spanning multiple domains remain challenging due to high computational cost and declining success with increasing target size.
We hypothesized that protein folding neural networks (PFNNs) operate in a “local-first” manner, prioritizing local interactions while displaying limited sensitivity to global foldability. Guided by this hypothesis, we propose an epitope-only strategy that retains only the discontinuous surface residues surrounding the binding site. Compared to intact-domain workflows, this approach improves $\textit{in silico}$ success rates by up to 80% and reduces the average time per successful design by up to forty-fold, enabling binder design against previously intractable targets such as ClpP and ALS3. Building on this foundation, we further developed a tailored pipeline that incorporates a Monte Carlo–based evolution step to overcome local minima and a position-specific biased inverse folding step to refine sequence patterns. Together, these advances not only establish a generalizable framework for efficient binder design against structurally large and otherwise inaccessible targets, but also support the broader “local-first” hypothesis as a guiding principle for PFNN-based design.

Submission Number: 297