Stuff AI CAN'T Do

¿Puede la IA superar a los humanos en la predicción de interacciones proteína-proteína ?

¿Qué opinas?

AlphaFold-Multimer y sus sucesores superaron este punto de referencia en 2024.

Background

Since 2021, deep-learning models have steadily improved PPI prediction by learning co-evolutionary signals and structural constraints from large protein sequence alignments. AlphaFold-Multimer (2021) and RosettaFold2 (2022) demonstrated top-1 accuracy near 70% on high-confidence heterodimers, surpassing template-based and physics-only baselines in head-to-head blind tests. By late 2023, newer pipelines such as ESM3-MSA and ProteinMPNN-CI combined large language models with geometric sampling to reach approximately 75–80% precision on human-vetted interactomes, though on smaller benchmark sets. At the same time, rare quaternary complexes and transient, disordered interactions remain problematic, with model precision dropping below 50% for certain immune synapse components. Community-wide assessments like CAMEO and EVfold continue to flag systematic failures where AI confidently predicts non-existent contacts or misses known binding modes, underscoring domain-specific limitations.

SOURCE: no public reference

Estado verificado por última vez en May 15, 2026.

📰

Galería

In the Court of AI Capability
Summary of Findings
Verdict over time
May 2026May 2026May 2026
Sitting at the Bench Filed · may. 15, 2026
— The Question Before the Court —

¿Puede la IA superar a los humanos en la predicción de interacciones proteína-proteína?

★ The Court Finds ★
▲ Upgraded from In_research
Casi

Existen demostraciones limitadas — pero el panel no fue unánime.

Ruling of the Bench

The jury found itself swayed by AI’s impressive strides in predicting protein-protein interactions, with most agreeing it has surpassed human performance on curated datasets but still falls short of universal dominance across all biological contexts. Two jurors argued the threshold had been crossed with deep learning models like AlphaFold-Multimer, while the others remained cautious, noting gaps in real-world applicability and the reliance on structural predictions rather than direct experimental evidence. Ruling: "AI knows the dance—now it just needs to lead every step of the ball.

— Hon. G. Hopper, Presiding
Jury Tally
2
3Casi
0No
Verdict Confidence
84%
The Court of AI Capability is, of course, not a real court.
But the data is real.
The Case File · Stacked History
Session I · May 2026 In_research
Session II · May 2026 In_research
Case № 7326 · Session III
In the Court of AI Capability

The Case File

Docket № 7326 · Session III · Vol. III
I. Particulars of the Case
Question put to the court¿Puede la IA superar a los humanos en la predicción de interacciones proteína-proteína?
SessionIII (3 hearing)
Convened15 may. 2026
Previously ruledIN_RESEARCH (May '26) → IN_RESEARCH (May '26) → ALMOST (May '26)
Presiding JudgeHon. G. Hopper
II. Cumulative Tally Across Sessions

Across 3 sessions, 11 jurors have heard this case. Combined tally: 6 YES · 3 ALMOST · 2 NO · 0 IN RESEARCH.

Note: cumulative includes older juror opinions. The current session tally above is the live verdict.

III. Verdict

By a vote of 2 — 3 — 0, the panel returns a verdict of CASI, with verdict confidence of 84%. The court so orders. Verdict upgraded from prior session.

IV. Declaraciones del tribunal
Jurado I ALMOST

"AI models like AlphaFold predict interactions with high accuracy"

Jurado II ALMOST

"AI outperforms human experts on curated PPI datasets but not universally across all proteins"

Jurado III

"AI models, such as RF2-PPI and AlphaFold-Multimer, have demonstrated high accuracy (up to 90%) in predicting protein-protein interactions, outperforming traditional methods."

Jurado IV

"AlphaFold-Multimer and other deep learning models have demonstrated superior accuracy in predicting protein-protein interactions compared to experimental and traditional computational methods."

Jurado V ALMOST

"AI models like AlphaFold predict structures, aiding interaction predictions"

Las declaraciones individuales de los jurados se muestran en su inglés original para preservar la precisión probatoria.

G. Hopper
Presiding Judge
M. Lovelace
Clerk of the Court

Lo que el público piensa

No 6% · Sí 76% · Quizás 18% 154 votes
Sí · 76%
Quizás · 18%
La tendencia necesita votos de al menos 2 días distintos.

Discusión

no comments

Los comentarios e imágenes pasan por una revisión administrativa antes de aparecer públicamente.

3 jury checks · más reciente hace 5 horas
15 May 2026 5 jurors · indeciso, indeciso, puede, puede, indeciso indeciso
12 May 2026 3 jurors · puede, no puede, puede indeciso
11 May 2026 3 jurors · puede, no puede, puede indeciso estado cambiado

Cada fila es una comprobación de jurado independiente. Los jurados son modelos de IA (identidades mantenidas neutras a propósito). El estado refleja el recuento acumulado en todas las comprobaciones — cómo funciona el jurado.

Más en Judgment

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