ReviewComputational and structural biotechnology journal2025
Multimeric protein interaction and complex prediction: Structure, dynamics and function.
Review in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.Journal of chemical information and modeling · 2026Article
- ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures.bioRxiv : the preprint server for biology · 2026Article
- Glutathione Peroxidase fromInternational journal of molecular sciences · 2026Article
- Computational Modeling of Cellulose Synthase Heterotrimer Assembly and Identification of Antimicrobial Compounds Targeting Interface Sites inJournal of fungi (Basel, Switzerland) · 2026Article
- Optimizing computational prediction of shrimp-WSSV protein interactions through integration of homology- and topology-based predictions.Molecular genetics and genomics : MGG · 2026Article
- Review
- Optimized Quantitative Bacterial Two-Hybrid (qB2H) for Protein-Protein Interaction Assessment.Computational and structural biotechnology journal · 2026Article
- UNKAI: A Protein Functional Identity Prediction Model Based on ESM-C Latent Representations and the Attention Mechanism.Computational and structural biotechnology journal · 2026Article
- Dual Cross-Attention Network for Hierarchical Feature Fusion in Protein-Protein Interaction Prediction.Computational and structural biotechnology journal · 2026Article
- Adversarial Sequence Mutations in AlphaFold and ESMFold Reveal Nonphysical Structural Invariance, Confidence Failures, and Concerns for Protein Design.Computational and structural biotechnology journal · 2026Article
- HVIface: sequence-based deep learning for decoding human-virus protein-protein interfaces.Frontiers in bioinformatics · 2026Article
- The Constrained Disorder Principle: A Paradigm Shift for Accurate Interactome Mapping and Information Analysis in Complex Biological Systems.Bioengineering (Basel, Switzerland) · 2025Review
- AlphaFold in protein structure and function prediction.Computational and structural biotechnology journal · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the structure, interactions, dynamics, and functions of multimeric protein complexes is essential for studying multimeric protein complexes, with broad implications for disease mechanisms and drug design, and other areas of biomedical research. Although remarkable achievements have been made in monomer prediction in recent years, protein multimers prediction remains a crucial yet challenging area due to their complex structures, diverse physicochemical properties, and limited experimental data. This review encompasses recent advancements in multimer research, providing an overview of classical concepts and methodologies and the key differences from monomer prediction methods. It further explores state-of-the-art advances in CASP16, including predictions of unknown stoichiometries, supercomplexes, conformational ensembles. This review also delves into the contributions of AlphaFold2 & 3 to multimer prediction, highlighting both the successes and limitations, particularly in handling functional protein-protein interactions and dynamical conformations. Recent deep learning methods and their applications in multimer interaction analysis and quality assessment are discussed, along with insights into future research directions, such as improving prediction accuracy, enabling functional interpretation of protein-protein interactions, and reconstructing protein mechanisms.
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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.