ArticleJournal of proteome research2022
PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein-Peptide and Protein-Protein Binding Affinity.
Article in Journal of proteome research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.
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Who cites it
50 citing papers in PubMed, 1 synthesis or guideline pooled it, 88 citations in OpenAlex.
- Peptides Evaluated In Silico, In Vitro, and In Vivo as Therapeutic Tools for Obesity: A Systematic Review.International journal of molecular sciences · 2024Pooled it
- Learning Protein-Protein Binding Free Energies from Interface Graphs and Physicochemical Descriptors.ACS physical chemistry Au · 2026Article
- Article
- PpF: a density functional fine-tuned for noncovalent interactions of protein and peptide residues.Chemical science · 2026Article
- A multiscale, Bayesian inference approach to augment mechanistic models of cell signaling with machine-learning predictions of binding affinity.PLoS computational biology · 2026Article
- Integrating Diffusion and Liquid AI Models for Predicting Peptide Affinity from mRNA Display Selections.bioRxiv : the preprint server for biology · 2026Article
- A paired sequence language model for protein-protein interaction modeling.Nature communications · 2026Article
- Computational nanobody design using graph neural networks and Metropolis Monte Carlo sampling.Briefings in bioinformatics · 2026Article
- In silico evaluation of (benzo)chromeno[3,4-c]pyridine derivative as dual EGFR/HER2 inhibitors for non-small cell lung cancer.Scientific reports · 2026Article
- Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026Review
- Analysing open-source protein folding models for nanobody binding prediction.Frontiers in bioinformatics · 2026Article
- Binding Affinity Prediction of Membrane Protein-Protein Complexes Using MPA-Pred.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Multimodal Learning of Protein-Protein Interactions for Accurate Binding Affinity Prediction.ACS omega · 2025Article
- Topological deep learning for enhancing peptide-protein complex prediction.Communications chemistry · 2025Article
- Reaction Engineering of In Vitro Natural Product Biosynthesis: Challenges and Strategies.Chembiochem : a European journal of chemical biology · 2025Review
- State-Specific Peptide Design Targeting G Protein-Coupled Receptors.Journal of chemical information and modeling · 2025Article
- Artificial Intelligence-Driven Nanoarchitectonics for Smart Targeted Drug Delivery.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Sequence-Based Protein-Protein Interaction Prediction and Its Applications in Drug Discovery.Cells · 2025Review
- PCANN Program for Structure-Based Prediction of Protein-Protein Binding Affinity: Comparison With Other Neural-Network Predictors.Proteins · 2025Article
- A Computational Perspective to Intermolecular Interactions and the Role of the Solvent on Regulating Protein Properties.Chemical reviews · 2025Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Virtual screening of protein-protein and protein-peptide interactions is a challenging task that directly impacts the processes of hit identification and hit-to-lead optimization in drug design projects involving peptide-based pharmaceuticals. Although several screening tools designed to predict the binding affinity of protein-protein complexes have been proposed, methods specifically developed to predict protein-peptide binding affinity are comparatively scarce. Frequently, predictors trained to score the affinity of small molecules are used for peptides indistinctively, despite the larger complexity and heterogeneity of interactions rendered by peptide binders. To address this issue, we introduce PPI-Affinity, a tool that leverages support vector machine (SVM) predictors of binding affinity to screen datasets of protein-protein and protein-peptide complexes, as well as to generate and rank mutants of a given structure. The performance of the SVM models was assessed on four benchmark datasets, which include protein-protein and protein-peptide binding affinity data. In addition, we evaluated our model on a set of mutants of EPI-X4, an endogenous peptide inhibitor of the chemokine receptor CXCR4, and on complexes of the serine proteases HTRA1 and HTRA3 with peptides. PPI-Affinity is freely accessible at https://protdcal.zmb.uni-due.de/PPIAffinity.
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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.