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Updated: Feb 15, 2026

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

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Un marco unificado que combina características moleculares lineales y 3D para la predicción robusta de interacciones

Chang Sun¹, Zichen Qin², Minglei Li¹

¹Centre for Bioinformatics and Intelligent Medicine, College of Computer Science, Nankai University, Tianjin 300071, China.

Cell reports methods

|February 13, 2026

Abstract:

We develop PointDPI to predict drug-protein interactions by simultaneously exploiting their linear and 3D structural features. By aligning the features, PointDPI stereoscopically recognizes molecular properties and reduces reliance on 3D structures. Local topological relationships among molecules are further preserved for avoiding distortion. PointDPI predicts key regulatory sites based on the model's gradient. We demonstrate improved performance over several state-of-the-art (SOTA) methods, including increased accuracy in dealing with unseen molecules. Four predicted drug-protein interactions (DPIs) are experimentally validated at both mRNA and protein levels, highlighting the therapeutic potential of adenosine in inflammatory diseases, ondansetron and etodolac in neurological diseases, and neuroprotective action for dopamine.

Palabras clave:

estructura molecular 3D CP: biología computacional PDE4B alineación de estructuras multimodales preservación de relaciones topológicas experimento de laboratorio

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