ReviewChemical reviews2024
Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments.
Review in Chemical reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- A tri-scale in silico framework integrating pharmacovigilance and mechanistic modeling suggests tepotinib-associated acute kidney injury risk.Renal failure · 2026Article
- Article
- Computational discovery of HIF-1α/VHL protein-protein interaction inhibitors for hypoxic cell protection.Molecular diversity · 2026Article
- MSCA-PLA: multi-scale cross-attention with differentiable pooling for protein-ligand binding affinity prediction.Molecular diversity · 2026Article
- Missense mutations on SynGAP C2 domain impair membrane diffusion.Protein science : a publication of the Protein Society · 2026Article
- Dual-channel graph learning reveals similarity and complementarity in protein-protein interaction networks.PLoS computational biology · 2026Article
- Targeting protein protein interactions and their modulators to enable new therapeutic strategies for human diseases.NPJ systems biology and applications · 2026Review
- Protein oxidation in crowded environments.The Biochemical journal · 2026Review
- Surface-Capped Protein Nanoparticles for Nonviral Gene Delivery.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Exploring neural networks to uncover information-richer features for protein interaction prediction.European biophysics journal : EBJ · 2026Article
- A progressive fine-tuning framework with dynamic parameter selection for low-resource peptide-GPCR interaction prediction.Briefings in bioinformatics · 2026Article
- Beyond contacts: The important role of the support region in protein complex assembly.Protein science : a publication of the Protein Society · 2026Article
- Molecular crowding effects on protein stability in a bacterial proteome.Scientific reports · 2026Article
- Unifying Summary Statistic Selection for Approximate Bayesian Computation.Statistics and computing · 2026Article
- Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026Review
- From genomes to interventions: computational strategies transforming parasitology.Frontiers in veterinary science · 2026Review
- Bridging Scales: Coarse-Grained Protein Models in Computational Biology.Advances in experimental medicine and biology · 2026Review
- Interactomics: Dissecting Protein Networks in Living Systems.Advances in experimental medicine and biology · 2026Review
- Protein Confinement Decouples Dynamical Heterogeneity from Structural Preordering in Supercooled Monolayer Water.JACS Au · 2025Article
- ProMoHGT: a heterogeneous graph transformer with graph contrastive learning for robust microbial protein function prediction.BMC genomics · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Investigating protein-protein interactions is crucial for understanding cellular biological processes because proteins often function within molecular complexes rather than in isolation. While experimental and computational methods have provided valuable insights into these interactions, they often overlook a critical factor: the crowded cellular environment. This environment significantly impacts protein behavior, including structural stability, diffusion, and ultimately the nature of binding. In this review, we discuss theoretical and computational approaches that allow the modeling of biological systems to guide and complement experiments and can thus significantly advance the investigation, and possibly the predictions, of protein-protein interactions in the crowded environment of cell cytoplasm. We explore topics such as statistical mechanics for lattice simulations, hydrodynamic interactions, diffusion processes in high-viscosity environments, and several methods based on molecular dynamics simulations. By synergistically leveraging methods from biophysics and computational biology, we review the state of the art of computational methods to study the impact of molecular crowding on protein-protein interactions and discuss its potential revolutionizing effects on the characterization of the human interactome.
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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.