$\mathtt{Q^2SAR}$: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

Quantitative Structure-Activity Relationship ( $Q S A R$ ) modeling is a foundational computational methodology in early-stage drug discovery, heavily relied upon for predicting compound toxicity, bioavailability, and therapeutic potential. However, classical methods often struggle to effectively map the highly complex, non-linear, and high-dimensional interactions inherent in molecular data, leading to reduced predictive accuracy and costly late-stage clinical failures. In this paper, we present a Quantum Multiple Kernel Learning ( $Q M K L$ ) framework, dubbed Next-Gen $Q^{2} S A R$ , that leverages Quantum Support Vector Machines ( $Q S V M s$ ) to overcome these classical limitations. By encoding molecular descriptors into exponentially large quantum Hilbert spaces, our approach substantially enhances the expressiveness of non-linear modeling. Benchmarking our quantum-enhanced framework on a dataset targeting the $D Y R K 1 A$ kinase (a critical target for Alzheimer’s disease), the $Q M K L$ - $S V M$ achieves an impressive Area Under the Curve ( $A U C$ ) score of $0.8750$ , significantly outperforming classical state-of-the-art Gradient Boosting models ( $A U C = 0.8037$ ). Furthermore, we establish a theoretical and empirical pathway toward resolving classical data bottlenecks through projected quantum kernels ( $P Q K$ ) and measurement accelerators. As quantum computing architecture matures, this framework paves the way for autonomous cognitive architectures and self-improving drug discovery pipelines, promising to unlock deeper insights across vast chemical spaces and to accelerate the development of life-saving therapeutics.

$Q^{2} S A R$ : overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

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$Q^{2} S A R$ : overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

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Q2SARQ2SAR: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

文献摘要

讨论

|讲解博客

|AI智能校验

Q2SARQ2SAR: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

文献摘要

讨论

|讲解博客

|AI智能校验

$Q^{2} S A R$ : overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

讲解博客

AI智能校验

$Q^{2} S A R$ : overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning

讲解博客

AI智能校验