Kan AI overgå mennesker i at forudsige protein-protein-interaktioner ?
Afgiv din stemme — læs så hvad vores redaktør og AI-modellerne fandt.
AlphaFold-Multimer og efterfølgere tog dette benchmark i 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.
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Status senest tjekket August 8, 2026.
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Kan AI overgå mennesker i at forudsige protein-protein-interaktioner?
Snævre demoer findes — men panelet var ikke enigt.
Efter nøje at have vejet beviserne konkluderede juryen, at kunstig intelligens faktisk har overgået menneskelige benchmarks i at forme vores forståelse af protein-protein-interaktioner, skønt den endelige dom stadig er noget foreløbig og hviler på forudsigelsesmodellers skuldre, der endnu baserer sig på strukturelle indsigter frem for fuld mekanistisk sikkerhed. Den eneste dissenter hævdede, at forudsigelse uden definitivt bevis for mekanisme holder døren på klem, mens den ene "Næsten"-stemme afspejlede respekt for AI's imponerende bedrifter kombineret med en forsigtig tilbageholdenhed med at udråbe den til ubestridt hersker over det cellulære univers. Dom: AI folder kortet, men holder én fod på det menneskelige kompas.
After carefully weighing the evidence, the jury concluded that artificial intelligence has indeed surpassed human benchmarks in shaping our understanding of protein-protein interactions, though the final verdict remains slightly tentative, resting on the shoulders of predictive models that still lean on structural insights rather than full mechanistic certitude. The lone dissenter insisted that prediction without definitive proof of mechanism keeps the door just ajar, while the single "Almost" vote reflected respect for AI's towering achievements paired with a cautious reluctance to crown it undisputed ruler of the cellular universe. Ruling: AI folds the map, but keeps one foot on the human compass.
But the data is real.
The Case File
Across 19 sessions, 45 jurors have heard this case. Combined tally: 14 YES · 28 ALMOST · 3 NO · 0 IN RESEARCH.
Note: cumulative includes older juror opinions. The current session tally above is the live verdict.
By a vote of 1 — 1 — 0, the panel returns a verdict of NæSTEN, with verdict confidence of 90%. The court so orders.
"AlphaFold3 and related models achieved state-of-the-art performance on protein-protein interaction prediction."
"AI models like AlphaFold predict structures, aiding interaction predictions"
Individuelle nævningers udtalelser vises på originalengelsk for at bevare bevismæssig præcision.
Hvad publikum mener
Nej 6% · Ja 76% · Måske 18% 154 votesDiskussion
no comments⚖ 19 jury checks · seneste for 4 dage siden
Hver række er et separat jurytjek. Nævninger er AI-modeller (identiteter holdt neutrale med vilje). Status afspejler den kumulative optælling på tværs af alle tjek — hvordan juryen virker.