QUPEX: A Streamlit-Based Framework for Visualizing Quantum-Mechanical Property Spaces of Organic Molecules

Abstract

The growing availability of quantum-mechanical (QM) datasets offers new opportunities to investigate structure-property and property-property relationships in drug-like molecules using data-driven methods. However, interactive tools that integrate molecular visualization, statistical analysis of QM properties, clustering, and machine learning (ML) remain limited, despite their value in facilitating dataset exploration and interpretation. To address this gap, we introduce QUPEX (QUantum Property EXplorer), an open-source Streamlit-based framework for the interactive exploration of QM property spaces in molecular systems. As a demonstration, we apply QUPEX to a subset of the QM7-X dataset comprising 41,537 equilibrium molecular structures containing up to seven non-hydrogen atoms (C, N, O, S, and Cl) and their 24 associated QM properties. In addition to property-space analysis, QUPEX incorporates an XGBoost regression pipeline for predicting PBE0 dipole moments from tight-binding-derived electronic descriptors, together with model evaluation and SHAP-based interpretability functionality. By combining interactive molecular visualization, data analysis, and predictive modeling, QUPEX provides an accessible and extensible environment for investigating molecular datasets and identifying patterns in their structural and electronic properties. These capabilities can support the exploration of chemical space and inform the rational design of drug-like molecules with targeted QM properties.