---
title: "PRIME-ISP: A Unified Structure-Based Framework for Predicting Protein Interaction Sites"
id: "biorxiv-0-towards-a-unified-framework-for-protein-interaction-site-prediction-using"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-0-towards-a-unified-framework-for-protein-interaction-site-prediction-using"
content_type: "clinical_feed_article"
specialty: "Pharmacology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.10.18.759950v1?rss=1"
published_at: "2026-10-22T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# PRIME-ISP: A Unified Structure-Based Framework for Predicting Protein Interaction Sites
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-0-towards-a-unified-framework-for-protein-interaction-site-prediction-using
- **Specialty:** [Pharmacology](https://medichelpline.com/clinical-feed/pharmacology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.10.18.759950v1?rss=1)
- **Published At:** 2026-10-22T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The authors introduced **PRIME-ISP**, a single, structure-based architecture designed to predict interaction sites across multiple biomolecular classes. - PRIME-ISP encodes proteins at five organizational levels: solvent-excluded surfaces, atoms, residues, secondary-structure elements, and whole proteins; the source described coupled bottom-up and top-down propagation to integrate these scales. - The framework aims to capture both local geometry and global structural context, allowing prediction without interaction-specific feature engineering. - Investigators evaluated PRIME-ISP on benchmarks for protein, peptide, DNA, RNA, small-molecule, metal, and carbohydrate interaction-site prediction; the source reported consistent outperformance of a recent unified sequence-based predictor and comparable results to specialized methods. - The study team observed that PRIME-ISP required no task-specific modifications while addressing chemically and geometrically distinct binding problems. - Data and source code were made publicly available by the authors at a GitHub repository linked in the preprint. - The preprint status was explicitly noted; the source did not provide peer-review certification or granular training and hyperparameter details in the abstract. - The authors declared no competing interests in the preprint metadata. - The source did not report detailed limitations, external validation on prospective sets, or application-specific deployment results within the abstract; those elements may be in the full manuscript or supplementary materials.
## Clinical Analysis & Structured Key Points
Towards a Unified Framework for Protein Interaction Site Prediction Using Hierarchical Protein Representations | bioRxiv Skip to main content New Results Towards a Unified Framework for Protein Interaction Site Prediction Using Hierarchical Protein Representations Viet Thanh Duy Nguyen , John K. Johnstone , View ORCID Profile Truong-Son Hy doi: https://doi.org/10.64898/2026.10.18.759950 Viet Thanh Duy Nguyen 1 Universit of Alabama at Birmingham, United States; Find this author on Google Scholar Find this author on PubMed Search for this author on this site John K. Johnstone 2 University of Alabama at Birmingham, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site Truong-Son Hy 2 University of Alabama at Birmingham, United States Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Truong-Son Hy For correspondence: sonpascal93{at}gmail.com Abstract Info/History Metrics Data/Code Preview PDF Abstract Proteins interact with a wide range of biomolecular partners, yet identifying the interaction sites that mediate these events remains a major challenge for understanding cellular function and guiding drug discovery. Existing computational methods are typically designed for specific interaction classes and often rely on task-specific features. Here, we introduce PRIME-ISP, a structure-based framework for predicting interaction sites across diverse biomolecular interaction types using a unified architecture. PRIME-ISP represents proteins at five organizational levels, including solvent-excluded surfaces, atoms, residues, secondary-structure elements, and whole proteins, and integrates information across these scales through coupled bottom-up and top-down propagation. This hierarchical representation jointly captures local geometry and global structural context, enabling a single architecture to address chemically and geometrically distinct binding problems without task-specific modifications. We evaluate PRIME-ISP on protein, peptide, DNA, RNA, small-molecule, metal, and carbohydrate interaction-site prediction benchmarks. Across these tasks, PRIME-ISP consistently outperforms a recent unified sequence-based predictor and achieves performance comparable to specialized methods while requiring no interaction-specific features. These results demonstrate that hierarchical structural representations provide a flexible foundation for interaction-site prediction across diverse biomolecular interactions. Source code and data are publicly available at https://github.com/HySonLab/PRIME-ISP Competing Interest Statement The authors have declared no competing interest. Footnotes https://github.com/HySonLab/PRIME-ISP Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Back to top Previous Posted October 22, 2026. Download PDF Data/Code Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Towards a Unified Framework for Protein Interaction Site Prediction Using Hierarchical Protein Representations Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Towards a Unified Framework for Protein Interaction Site Prediction Using Hierarchical Protein Representations Viet Thanh Duy Nguyen , John K. Johnstone , Truong-Son Hy bioRxiv 2026.10.18.759950; doi: https://doi.org/10.64898/2026.10.18.759950 Share This Article: Copy Citation Tools Towards a Unified Framework for Protein Interaction Site Prediction Using Hierarchical Protein Representations Viet Thanh Duy Nguyen , John K. 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