ReviewMolecular therapy : the journal of the American Society of Gene Therapy2025
Recent progress and future challenges in structure-based protein-protein interaction prediction.
Review in Molecular therapy : the journal of the American Society of Gene Therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Mapping the dynamic plant interactome: from in vitro assays to in vivo quantitative approaches.Plant methods · 2026Review
- BiMba: using Vision Mamba to predict protein sites that bind other proteins.Bioinformatics (Oxford, England) · 2026Article
- Disrupting the Undruggable: Emerging Modalities for Targeting Protein-Protein Interactions in Oncology.Biology · 2026Review
- Engineering Design of Artificial Phase-Separating Proteins.Biotechnology journal · 2026Review
- Protein structural dynamics in covalent drug design: insights from irreversible and reversible covalent inhibitors.RSC chemical biology · 2026Review
- A progressive fine-tuning framework with dynamic parameter selection for low-resource peptide-GPCR interaction prediction.Briefings in bioinformatics · 2026Article
- EZHIP in Pediatric Brain Tumors: From Epigenetic Mimicry to Therapeutic Vulnerabilities.International journal of molecular sciences · 2026Review
- Examining selection dynamics and limitations in multi-round protein selection of high diversity libraries.Protein engineering, design & selection : PEDS · 2026Article
- Article
- A Structure-Guided Kinase-Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome.bioRxiv : the preprint server for biology · 2025Article
- Technologies for Monoclonal Antibody Discovery and Development.International journal of molecular sciences · 2025Review
- Sequence-Based Protein-Protein Interaction Prediction and Its Applications in Drug Discovery.Cells · 2025Review
- Assessment of Protein Complex Predictions in CASP16: Are we making progress?bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Protein-protein interactions (PPIs) play a fundamental role in cellular processes, and understanding these interactions is crucial for advances in both basic biological science and biomedical applications. This review presents an overview of recent progress in computational methods for modeling protein complexes and predicting PPIs based on 3D structures, focusing on the transformative role of artificial intelligence-based approaches. We further discuss the expanding biomedical applications of PPI research, including the elucidation of disease mechanisms, drug discovery, and therapeutic design. Despite these advances, significant challenges remain in predicting host-pathogen interactions, interactions between intrinsically disordered regions, and interactions related to immune responses. These challenges are worthwhile for future explorations and represent the frontier of research in this field.
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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.