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ABSTRACT

MViewEMA, a single-model EMA method that leverages a multi-view representation learning framework to integrate residue–residue interaction features from micro-environment, meso-environment, and macro-environment levels for global accuracy assessment of protein complex models. Benchmark results demonstrate that MViewEMA outperforms state-of-the-art EMA methods in global accuracy assessment, achieving over 10-fold improvement in computational efficiency compared to our previous method, DeepUMQA3. Integrating MViewEMA into modern prediction frameworks, such as AlphaFold-Multimer, AlphaFold3, and DiffDock-PP, can enhance the accuracy of complex structure prediction. This method facilitates efficient selection of high-quality protein complex models from large-scale structural datasets and demonstrated top performance in model selection tracks during the CASP16 blind test.


INPUT
Protein Complex Structural Models
Input the complex structure model in PDB format (mandatory, Click for example input or example output ).
Tip: Different chains need to be separated by 'TER', otherwise they will be treated as one chain. It is recommended to refer to the PDB format before submitting your job.

Or, upload the complex structure model file (ends with ".pdb"):

Or, upload multiple models of the same protein:
 
Or, upload a zip file containing all models of the same protein (each model file ends with ".pdb"):

Option:

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Enter your jobname (optional):


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