Evidence map›Paper›PMID 42056694›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Proteome-wide Ab Initio Structural Analysis of Viral Evolution.

Muhammad Asif Ali, Gustavo Caetano-Anollés

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Muhammad Asif AliDepartment of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.
Gustavo Caetano-AnollésDepartment of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA. gca@illinois.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid advancement of sequencing technologies has outpaced experimental protein structure determination. AI-driven tools like AlphaFold now enable the prediction of near-experimental-quality atomic structures. However, certain protein regions-such as intrinsically disordered segments or those with transient or context-dependent conformations-may not be fully captured by experimental methods like NMR or cryo-EM. Here, we use AlphaFold to model a reference structure and bridge gaps in experimental models within a comparative framework for assessing structural deviations in sequences yet to be experimentally resolved. To achieve an accurate depiction of changes in protein structure, these regions are analyzed for their flexibility and biochemical properties. This approach provides a systematic strategy for refining structural interpretations of proteins in evolving viral populations, aiding in functional annotation, and improving our understanding of interactions and evolution of viral proteins.

Indexed as

Computational BiologyEvolution, MolecularProteomeViral ProteinsVirusesModels, MolecularProtein ConformationProteomeViral ProteinsBioinformaticsEpidemiologyMutationProteomeSeasonality

Identifiers

What Socratic holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.