Prediction of Protein-Protein Interactions: The Next Frontier Volume II

This Research topic is a second volume of the Research Topic “Prediction of Protein-Protein Interactions (PPIs): The Next Frontier”. Please see the first Volume here. PPIs underpin virtually all biological processes, including signal transduction, gene regulation, immune recognition, molecular transport, and disease progression. Many proteins function not as isolated molecules but through interactions with other proteins and biomolecules. Consequently, the prediction, characterization, and modulation of PPIs remain central challenges in structural biology, computational biology, molecular biophysics, and drug discovery.The first volume of this Research Topic highlighted significant advances and persistent challenges in the prediction and characterization of PPIs. Since then, the field has evolved rapidly, driven by breakthroughs in artificial intelligence and biomolecular modeling. Methods such as AlphaFold-Multimer, AlphaFold3, RoseTTAFold, and related approaches have expanded our ability to predict protein complexes and biomolecular assemblies. However, accurately modeling PPIs remains challenging due to the dynamic, context-dependent, and often transient nature of protein interactions, as well as the influence of conformational flexibility, post-translational modifications, and the cellular environment.This second volume aims to highlight the next generation of computational, experimental, and integrative approaches for understanding protein interactions and assemblies. We welcome studies that advance the prediction of protein complex structures, interaction interfaces, binding specificity, conformational dynamics, and interaction networks, as well as approaches that combine artificial intelligence, molecular simulations, structural bioinformatics, and experimental validation.The goal of this Research Topic is to provide a timely collection of original research articles, reviews, perspectives, and methodological advances that showcase emerging directions in PPI prediction and characterization. This collection will be of interest to researchers working in structural biology, computational biophysics, systems biology, and therapeutic discovery.Topics of interest include, but are not limited to:• AI-driven, deep learning, and protein language model approaches for PPI prediction and protein complex modeling.• Applications, benchmarking, and validation of emerging biomolecular modeling tools.• Protein-protein docking, molecular simulations, and integrative structural biology approaches.• Prediction of interaction interfaces, binding specificity, affinity, and mutational effects.• Modeling conformational flexibility, intrinsically disordered regions, transient interactions, and higher-order protein assemblies.• Integration of computational predictions with cryo-EM, NMR, mass spectrometry, proteomics, and other experimental methods.• Proteome-scale PPI prediction, interactome analysis, protein interaction networks, and database development.• Graph-based, sequence-based, and structure-based methods for PPI prediction.• Therapeutic targeting of PPIs, including biologics, peptides, molecular glues, and small molecules.• Applications of PPI prediction in disease biology, drug discovery, synthetic biology, and protein engineering.By bringing together contributions from both computational and experimental researchers, this Research Topic will help define the next frontier in the prediction, validation, and biological interpretation of PPIs. Topic editors: Amar Singh, Binh P. Nguyen, Ho Leung Ng Source: https://www.frontiersin.org/research-topics/82611/prediction-of-protein-protein-interactions-the-next-frontier-volume-ii