ArticleBioinformatics advances2024
DeepRank-GNN-esm: a graph neural network for scoring protein-protein models using protein language model.
Article in Bioinformatics advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- ESpma: A method for assessing biological/non-biological interfaces using point-clouds-based structural features and protein language models.Protein science : a publication of the Protein Society · 2026Article
- AI-driven computational drug design: tools, workflow and challenges.RSC advances · 2026Review
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.Journal of chemical information and modeling · 2026Article
- AbTune: layer-wise selective fine-tuning of protein language models for antibodies.Briefings in bioinformatics · 2026Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.bioRxiv : the preprint server for biology · 2026Article
- DeepRank-Ab: a scoring function for antibody-antigen complexes based on geometric deep learning.Communications biology · 2026Article
- PepLM-GNN: A graph neural network framework leveraging pre-trained language models for peptide-protein binding prediction.PLoS computational biology · 2026Article
- A survey of downstream applications of evolutionary scale modeling protein language models.Quantitative biology (Beijing, China) · 2026Review
- IgPose: a generative data-augmented pipeline for robust immunoglobulin-antigen binding prediction.Bioinformatics (Oxford, England) · 2026Article
- Article
- Review
- Recent advances in deep learning for protein-protein interaction: a review.BioData mining · 2025Review
- OPUS-BFactor: Predicting Protein B-Factor with Sequence and Structure Information.Molecules (Basel, Switzerland) · 2025Article
- Compact Assessment of Molecular Surface Complementarities Enhances Neural Network-Aided Prediction of Key Binding Residues.Journal of chemical information and modeling · 2025Article
- Deep learning in GPCR drug discovery: benchmarking the path to accurate peptide binding.Briefings in bioinformatics · 2025Article
- Graph Neural Network-Based Approaches for Protein Function Prediction.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Large Context, Deeper Insights: Harnessing Large Language Models for Advancing Protein-Protein Interaction Analysis.Methods in molecular biology (Clifton, N.J.) · 2025Article
- EuDockScore: Euclidean graph neural networks for scoring protein-protein interfaces.Bioinformatics (Oxford, England) · 2024Article
- Protein A-like Peptide Design Based on Diffusion and ESM2 Models.Molecules (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Protein-Protein interactions (PPIs) play critical roles in numerous cellular processes. By modelling the 3D structures of the correspond protein complexes valuable insights can be obtained, providing, e.g. starting points for drug and protein design. One challenge in the modelling process is however the identification of near-native models from the large pool of generated models. To this end we have previously developed DeepRank-GNN, a graph neural network that integrates structural and sequence information to enable effective pattern learning at PPI interfaces. Its main features are related to the Position Specific Scoring Matrices (PSSMs), which are computationally expensive to generate, significantly limits the algorithm's usability. Results: We introduce here DeepRank-GNN-esm that includes as additional features protein language model embeddings from the ESM-2 model. We show that the ESM-2 embeddings can actually replace the PSSM features at no cost in-, or even better performance on two PPI-related tasks: scoring docking poses and detecting crystal artifacts. This new DeepRank version bypasses thus the need of generating PSSM, greatly improving the usability of the software and opening new application opportunities for systems for which PSSM profiles cannot be obtained or are irrelevant (e.g. antibody-antigen complexes). Availability and implementation: DeepRank-GNN-esm is freely available from https://github.com/DeepRank/DeepRank-GNN-esm.
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Registered trials
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 OpenQuestion graph.