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🧬 Improving Protein Docking Accuracy with Iter-CONSRANK By Didier Barradas-Bautista, Visualization Scientist at KAUST Protein–protein docking generates thousands of possible interaction models—but only a few are correct. In our latest collaborative work, we introduce Iter-CONSRANK, an iterative scoring algorithm that filters out incorrect models and enriches the ensemble with correct ones. 📊 Tested on two challenging datasets, Iter-CONSRANK increased the fraction of correct models by up to 8× for medium-difficulty targets and outperformed over 150 scoring functions in ranking accuracy. 🎯 The method is available for use in pre-processing docking ensembles or as an independent scoring tool. 🔬 This work was led in collaboration with [KAUST PI Name Placeholder] and our partners at the University of Naples “Parthenope”. 🎥 [Video Placeholder: short explainer or animation of the workflow] 📎 Read the full paper: [Link Placeholder]