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SymFold integrates evolutionary and structural priors for protein inverse folding

By PulseAugur Editorial · [1 sources] ·

Researchers have developed SymFold, a novel approach to protein inverse folding that integrates evolutionary and structural information. This method utilizes a symmetric dual-path architecture, combining pre-trained language models (PLMs) for evolutionary knowledge and multimodal protein language models (MPLMs) for structural insights. Through iterative guidance, SymFold achieves state-of-the-art performance on standard benchmarks, outperforming previous methods and demonstrating the effectiveness of its symmetric design. AI

IMPACT This research advances AI's capability in biological applications, potentially accelerating drug discovery and enzyme engineering.

RANK_REASON The cluster contains a research paper detailing a new method for protein inverse folding. [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 →

SymFold integrates evolutionary and structural priors for protein inverse folding

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The cluster contains a research paper detailing a new method for protein inverse folding. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Handong Wang, Jiaxin Qi, Baisheng Lai, Jianqiang Huang ·

    SymFold: Synergizing Evolutionary and Structural Priors for Accurate Protein Inverse Folding

    arXiv:2609.01353v1 Announce Type: new Abstract: Protein inverse folding aims to recover amino acid sequences for a given 3D protein structure, underpinning broad applications such as enzyme engineering and drug discovery.Current methods often follow a serial pipeline, in which a …

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