A quantifiable fraction of human proteins have experimentally solved 3D structures.

the verdict

SUPPORTED

the evidence backs this

Recorded sources

3 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

A quantifiable fraction of human proteins possess experimentally solved 3D structures, forming a substantial baseline of structural coverage that has recently been complemented by high-accuracy computational predictions.

The analysis

The claim states that a quantifiable fraction of human proteins have experimentally solved 3D structures. This is specific, empirical, and verifiable. The retrieved literature clearly supports this, noting that historical experimental and template-based methods covered a significant portion of the human proteome (e.g., around 48% as a baseline before AlphaFold) and thousands of experimental structures are actively curated in the Protein Data Bank. Therefore, the claim is supported.

Evidence for · 3

Can Predicted Protein 3D Structures Provide Reliable Insights into whether Missense Variants Are Disease Associated?

Recorded source metadata

Sirawit Ittisoponpisan, S. Islam, Tarun Khanna, Eman Alhuzimi, A. David, M. Sternberg. Can Predicted Protein 3D Structures Provide Reliable Insights into whether Missense Variants Are Disease Associated?. 2019. https://doi.org/10.1016/j.jmb.2019.04.009

Paper 0 notes that baseline experimental structural coverage accounts for a substantial fraction of the human proteome before adding homology predictions.

Source citation format

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More for · 2

The structural coverage of the human proteome before and after AlphaFold

Recorded source metadata

Eduard Porta-Pardo, Victoria Ruiz-Serra, Samuel Valentini, Alfonso Valencia. The structural coverage of the human proteome before and after AlphaFold. 2021. https://doi.org/10.1101/2021.08.03.454980

Paper 5 reports that the baseline structural coverage of the human proteome from experimentally derived or template-based models was already at 48% prior to the inclusion of AlphaFold predictions.

Source citation format

RCSB Protein Data Bank (PDB): Driving Research and Education Using Experimentally-Determined Structures and Computed Structure Models from Artificial Intelligence/Machine Learning

Recorded source metadata

Yuhe Liang, Christine Zardecki. RCSB Protein Data Bank (PDB): Driving Research and Education Using Experimentally-Determined Structures and Computed Structure Models from Artificial Intelligence/Machine Learning. 2025. https://doi.org/10.1063/4.0000914

Paper 7 details how the RCSB Protein Data Bank houses hundreds of thousands of experimentally determined 3D macromolecular structures alongside computed models.

Source citation format

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first checked01 Aug 2026

judged → SUPPORTED · 9201 Aug 2026

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