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Keyword: protein docking ×Clear all

6 claims from 3 papers

1. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Protein complex prediction with AlphaFold-Multimer

   Evans, O’Neill, Pritzel et al. · bioRxiv (Cold Spring Harbor Laboratory) · 2021

   The authors trained AlphaFold-Multimer for multi-chain inputs and report better interface prediction than single-chain AlphaFold adapted for complexes, on two benchmark sets of protein complexes.

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   1. UncheckedOn 17 template-free heterodimers, AlphaFold-Multimer reached at least medium accuracy on 13 targets and high accuracy on 7, versus 9 and 4 for the prior system.“On a benchmark dataset of 17 heterodimer proteins without templates (introduced in [2]) we achieve at least medium accuracy (DockQ [3] ≥ 0.49) on 13 targets and high accuracy (DockQ ≥ 0.8) on 7 targets, compared to 9 targets of at least medium accuracy and 4 of high accuracy for the previous state…”
   2. UncheckedAlphaFold-Multimer predicts heteromeric protein interfaces correctly in 70% of cases and with high accuracy in 26%, beating a flexible-linker AlphaFold approach.“For heteromeric interfaces we successfully predict the interface (DockQ ≥ 0.23) in 70% of cases, and produce high accuracy predictions (DockQ ≥ 0.8) in 26% of cases, an improvement of +27 and +14 percentage points over the flexible linker modification of AlphaFold [4] respectively.”
   3. UncheckedAlphaFold-Multimer predicts the interface of homomeric protein complexes in 72% of cases, and to high accuracy in 36%, gains of 8 and 7 points.“For homomeric inter-faces we successfully predict the interface in 72% of cases, and produce high accuracy predictions in 36% of cases, an improvement of +8 and +7 percentage points respectively.”

2. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   Improved prediction of protein-protein interactions using AlphaFold2

   Bryant, Pozzati and Elofsson · Nature Communications · 2022

   The authors applied AlphaFold2 to predict heterodimeric protein complexes, and built a score from the predicted interfaces to judge model quality and to tell interacting from non-interacting protein pairs.

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   1. UncheckedAlphaFold2 with optimised sequence alignments produced acceptable-quality models (DockQ ≥ 0.23) for 63% of the heterodimeric protein complexes tested.“We find that the AlphaFold2 protocol together with optimised multiple sequence alignments, generate models with acceptable quality (DockQ ≥ 0.23) for 63% of the dimers.”
   2. Unchecked“From the predicted interfaces we create a simple function to predict the DockQ score which distinguishes acceptable from incorrect models as well as interacting from non-interacting proteins with state-of-art accuracy.”

3. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   DTC: A deep learning framework for ternary contact prediction in C3-symmetric homotrimers

   Yu, Xie, Han and Gong · Physical review. E · 2026

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   1. Unchecked“On an independent test set, DTC achieves a Top-1 accuracy of 0.6.”