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TorchCraft framework uses AlphaFold 3 to design molecular binders

By PulseAugur Editorial · [1 sources] ·

Researchers have developed TorchCraft, a new framework for designing molecular binders by inverting an all-atom structure predictor. This method leverages pretrained weights from AlphaFold 3 and is implemented in TorchFold, combining various objectives like confidence, contact, and geometric priors. TorchCraft has demonstrated success in generating minibinders and VHHs that exhibit experimentally verified binding across multiple targets, and it shows potential for designing cyclic peptides and ligand-binding proteins. AI

IMPACT This framework could accelerate drug discovery and protein engineering by enabling more efficient and accurate design of molecular binders.

RANK_REASON The cluster describes a new scientific paper detailing a novel computational framework for molecular design. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

TorchCraft framework uses AlphaFold 3 to design molecular binders

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The cluster describes a new scientific paper detailing a novel computational framework for molecular design. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · TorchCraft Team, Yu Liu, Zhouhanyu Shen, Zhengyi Li, Xikun Huang, Jiaqi Liu, Shuxian Gao, Qilin Yu, Xiayan Qin, Yucheng Zhang, Mingchen Chen ·

    TorchCraft: Unified binder design by inverting an all-atom structure predictor

    arXiv:2609.19770v1 Announce Type: new Abstract: All-atom structure predictors model diverse molecular interactions, but using their learned structural priors for binder design remains challenging. Here we present TorchCraft, a unified binder-design framework that optimizes sequen…

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