BoltzProt-1: Towards Efficient De Novo Binder Design with Good Developability

Abstract

Abstract Designing binders against novel protein targets remains a central challenge in computational drug discovery. Here we introduce BoltzProt-1 , a pipeline for generating protein binders, including nanobodies, with improved hit rates and favorable developability properties. At its core lie a refined iteration of BoltzGen’s generative model and a novel protein-protein interaction prediction model, BoltzPPI . Employing BoltzPPI instead of BoltzGen’s standard structure-prediction confidence metrics to rank nanobody (VHH) designs increases the confirmed-binder hit rate from 3.3% to 8.0% across 10 novel targets. Assessed on 10 additional targets used in prior literature, the BoltzProt-1 pipeline obtains nanobody screening hits for 7 of 10 targets, surpassing the 6 of 10 previously reported by Chai-2. Finally, evaluating the developability of BoltzProt-1-designed nanobodies in terms of stability, aggregation, purity, polyspecificity and hydrophobicity reveals that 58% of its confirmed binders pass every criterion, exceeding both BoltzGen (40%) and clinical-stage VHH controls (21%). Abstract Figure