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Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
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Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Updated: Jan 11, 2026

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Multimodal diffusion for joint design of protein sequence and structure.

Shaowen Zhu1, Siddhant Gulati2, Yuxuan Liu1

  • 1Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, USA.

Protein Science : a Publication of the Protein Society
|November 14, 2025
PubMed
Summary
This summary is machine-generated.

This study presents a new computational method for designing protein sequences and structures together, enabling faster and more functional protein creation. Experimental results show promising functional protein designs, accelerating future applications.

Keywords:
diffusion modelsgenerative modelsmachine learningprotein design

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Area of Science:

  • Protein Engineering
  • Computational Biology
  • Structural Biology

Background:

  • Designing functional proteins computationally is crucial for both basic science and practical applications.
  • Existing methods often design protein sequence and structure in separate stages, which can be inefficient.

Purpose of the Study:

  • To develop a unified generative framework for co-designing protein sequence and structure simultaneously.
  • To enable cross-modality interactions for coherent and functional protein designs.

Main Methods:

  • A generative framework modeling the joint distribution of protein sequence and structure.
  • Representing residues using three modalities: type, position, and orientation, each modeled by diffusion processes.
  • A unified architecture, ReverseNet, with a graph attention encoder and separate projectors for multimodal integration.

Main Results:

  • The proposed models (JointDiff and JointDiff-x) achieve comparable or better designability for monomer structures than two-stage models.
  • Models are 1-2 orders of magnitude faster, supporting rapid iterative design.
  • Experimental validation on green fluorescent protein (GFP) designs yielded novel, functional variants with measurable fluorescence.

Conclusions:

  • Joint sequence-structure generation is feasible and can accelerate functional protein design.
  • The framework provides a foundation for future advancements in computational protein engineering.
  • Open-source code and models are available for further research and application.