Protein–Protein Interaction Prediction for Targeted Protein Degradation
Abstract
:1. Introduction
2. Methods
- Binding site prediction: One PDB file is used as model input, and the binary output describes whether a particular location on the protein surface constitutes a possible site for protein interactions (see Figure 2A).
- Interaction prediction: Two PDB files are processed, and the binary output describes whether the two proteins interact at a particular site (see Figure 2B).
2.1. Model Overview
2.2. (Pre-)Processing of 3D Structures into Graph Representations
2.3. Chemo-Geometric Feature Generation
2.3.1. Chemical Features
2.3.2. Geometric Features
2.4. Main DGRL Pipeline
2.5. Model Training
2.6. Implementation
3. Results
3.1. The Orthogonal Dataset
3.2. PPI Prediction on Protein Pairs
3.3. Evaluation on Ternary Complex Data
4. Discussion
4.1. Related Work
4.2. The Importance of Diverse Datasets for PPI Prediction
4.3. Using PPI Prediction for Targeted Protein Degradation
4.4. PPI Prediction and Complementary Experimental Methods
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
PPI | protein–protein interaction |
CNS | central nervous system |
POI | protein of interest |
PIC | proximity-inducing compound |
TPD | targeted protein degradation |
CRBN | Cereblon |
VHL | Von Hippel–Lindau tumor suppressor |
DGRL | deep graph representation learning |
PDB | Protein Data Bank |
k-NN | k nearest neighbors |
MLP | multilayer perceptron |
AUROC | area under the receiver operating characteristic curve |
Appendix A. Confusion Matrices on MaSIF and Orthogonal Datasets
Predicted | |||
---|---|---|---|
interaction | no interaction | ||
Actual | interaction | 3273 (32.7%) | 1380 (13.8%) |
no interaction | 882 (8.8%) | 4465 (44.6%) |
Predicted | |||
---|---|---|---|
interaction | no interaction | ||
Actual | interaction | 3418 (34.2%) | 1314 (13.1%) |
no interaction | 712 (7.1%) | 4556 (45.5%) |
Predicted | |||
---|---|---|---|
binding site | no binding site | ||
Actual | binding site | 3210 (32.1%) | 1714 (17.1%) |
no binding site | 926 (9.2%) | 4150 (41.5%) |
Predicted | |||
---|---|---|---|
interaction | no interaction | ||
Actual | interaction | 3503 (35.1%) | 914 (9.1%) |
no interaction | 1107 (11.0%) | 4476 (44.7%) |
Appendix B. Prediction Results for the Known Ternary Complexes
PDB ID | Chains | PPIs AUROC |
---|---|---|
5T35 | A, D | 0.40 |
6BN7 | B, C | 0.93 |
6BN8 | B, C | 0.95 |
6BN9 | B, C | 0.95 |
6BNB | B, C | 0.86 |
6BOY | B, C | 0.95 |
6HAX | A, B | 0.46 |
6HAY | E, F | 0.45 |
6HR2 | E, F | 0.51 |
6SIS | E, H | 0.38 |
6W7O | B, D | 0.72 |
6W8I | A, D | 0.89 |
6W8I | B, E | 0.80 |
6W8I | C, F | 0.81 |
6ZHC | A, D | 0.95 |
7KHH | C, D | 0.93 |
PDB ID | Chains | PPI AUROC |
---|---|---|
5T35 | A, D | 0.76 |
6BN7 | B, C | 0.78 |
6BN8 | B, C | 0.86 |
6BN9 | B, C | 0.78 |
6BNB | B, C | 0.83 |
6BOY | B, C | 0.81 |
6HAX | A, B | 0.67 |
6HAY | E, F | 0.66 |
6HR2 | E, F | 0.67 |
6SIS | E, H | 0.71 |
6W7O | B, D | 0.84 |
6W8I | A, D | 0.92 |
6W8I | B, E | 0.96 |
6W8I | C, F | 0.77 |
6ZHC | A, D | 0.91 |
7KHH | C, D | 0.78 |
PDB ID | Chains | PPI AUROC |
---|---|---|
5T35 | A, D | 0.76 |
6BN7 | B, C | 0.98 |
6BN8 | B, C | 0.99 |
6BN9 | B, C | 0.97 |
6BNB | B, C | 0.94 |
6BOY | B, C | 0.98 |
6HAX | A, B | 0.84 |
6HAY | E, F | 0.74 |
6HR2 | E, F | 0.69 |
6SIS | E, H | 0.72 |
6W7O | B, D | 0.81 |
6W8I | A, D | 0.86 |
6W8I | B, E | 0.87 |
6W8I | C, F | 0.91 |
6ZHC | A, D | 0.97 |
7KHH | C, D | 0.97 |
Predicted | |||
---|---|---|---|
interaction | no interaction | ||
Actual | interaction | 4423 (44.2%) | 112 (1.1%) |
no interaction | 92(1.0%) | 5373(53.7%) |
Predicted | |||
---|---|---|---|
interaction | no interaction | ||
Actual | interaction | 2943 (29.4%) | 2382 (27.8%) |
no interaction | 1108 (11.1%) | 3567 (35.6%) |
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Dataset | Task | Subset | PDB IDs | Resolution (Å) | Mol. w. per Model (kDa) | Tot. Polymer Residues per Model | Polymer Entity seq. Length | Mol. Entity w. (kDa) |
---|---|---|---|---|---|---|---|---|
MaSIF | binding site | train. | 2809 | 2.27 | 99.08 | 873.58 | 220.32 | 24.7 |
test | 368 | 2.35 | 142.42 | 1270.48 | 343.61 | 38.21 | ||
interactions | train. | 4833 | 2.35 | 117.92 | 1043.45 | 264.32 | 29.67 | |
test | 970 | 2.28 | 99.31 | 876.54 | 235.81 | 29.9 | ||
Orthogonal | binding site | train. | 2373 | 1.75 | 66.07 | 547.07 | 246.82 | 27.94 |
test | 1111 | 1.81 | 105.54 | 880.11 | 297.68 | 33.81 | ||
interactions | train. | 3201 | 1.77 | 80.86 | 657.90 | 214.36 | 26.82 | |
test | 1431 | 1.74 | 65.06 | 566.08 | 249.67 | 28.21 |
Dataset | Task | MaSIF [30] | dMaSIF [26] | Ours |
---|---|---|---|---|
MaSIF | binding site | 0.85 | 0.87 | 0.82 |
interactions | 0.81 | 0.82 | 0.88 | |
Orthogonal | binding site | - | 0.77 | 0.79 |
interactions | - | 0.77 | 0.88 |
PDB ID | Chains | E3 ligase | Target |
---|---|---|---|
5T35 | A, D | VHL | BRD4 BD2 |
6BN7 | B, C | CRBN | BRD4 BD1 |
6BN8 | B, C | CRBN | BRD4 BD1 |
6BN9 | B, C | CRBN | BRD4 BD1 |
6BNB | B, C | CRBN | BRD4 BD1 |
6BOY | B, C | CRBN | BRD4 BD1 |
6HAX | A, B | VHL | SMARCA2 |
6HAY | E, F | VHL | SMARCA2 |
6HR2 | E, F | VHL | SMARCA4 |
6SIS | E, H | VHL | BRD4 BD2 |
6W7O | B, D | cIAP1-BIR3 | BTK |
6W8I | A, D ∣ B, E ∣ C, F | cIAP1-BIR3 | BTK |
6ZHC | AD | VHL | Bcl-xL |
7KHH | CD | VHL | BRD4 BD1 |
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Orasch, O.; Weber, N.; Müller, M.; Amanzadi, A.; Gasbarri, C.; Trummer, C. Protein–Protein Interaction Prediction for Targeted Protein Degradation. Int. J. Mol. Sci. 2022, 23, 7033. https://doi.org/10.3390/ijms23137033
Orasch O, Weber N, Müller M, Amanzadi A, Gasbarri C, Trummer C. Protein–Protein Interaction Prediction for Targeted Protein Degradation. International Journal of Molecular Sciences. 2022; 23(13):7033. https://doi.org/10.3390/ijms23137033
Chicago/Turabian StyleOrasch, Oliver, Noah Weber, Michael Müller, Amir Amanzadi, Chiara Gasbarri, and Christopher Trummer. 2022. "Protein–Protein Interaction Prediction for Targeted Protein Degradation" International Journal of Molecular Sciences 23, no. 13: 7033. https://doi.org/10.3390/ijms23137033